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1Academic Journal
المؤلفون: Blaheta, Radim, Béreš, Michal, Domesová, Simona, Pan, Pengzhi
مصطلحات موضوعية: keyword:inverse problems, keyword:Bayesian approach, keyword:stochastic Galerkin method, msc:60-08, msc:65C60, msc:65N21, msc:82-08, msc:86-08
وصف الملف: application/pdf
Relation: mr:MR3893005; zbl:Zbl 07031682; reference:[1] Babuška, I., Tempone, R., Zouraris, G. E.: Galerkin finite element approximations of Stochastic elliptic partial differential equations.SIAM J. Numer. Anal. 42 (2004), 800-825. Zbl 1080.65003, MR 2084236, 10.1137/S0036142902418680; reference:[2] Béreš, M., Domesová, S.: The stochastic Galerkin method for Darcy flow problem with log-normal random field coefficients.Adv. Electr. Electron. Eng. 15 (2017), 267-279. 10.15598/aeee.v15i2.2280; reference:[3] Blaheta, R., Béreš, M., Domesová, S.: A study of stochastic FEM method for porous media flow problem.Proc. Int. Conf. Applied Mathematics in Engineering and Reliability CRC Press (2016), 281-289. 10.1201/b21348-47; reference:[4] Blaheta, R., Kohut, R., Kolcun, A., Souček, K., Staš, L., Vavro, L.: Digital image based numerical micromechanics of geocomposites with application to chemical grouting.Int. J. Rock Mechanics and Mining Sciences 77 (2015), 77-88. 10.1016/j.ijrmms.2015.03.012; reference:[5] Boffi, D., Brezzi, F., Fortin, M.: Mixed Finite Element Methods and Applications.Springer Series in Computational Mathematics 44, Springer, Berlin (2013). Zbl 1277.65092, MR 3097958, 10.1007/978-3-642-36519-5; reference:[6] Carey, G. F., Chow, S. S., Seager, M. K.: Approximate boundary-flux calculations.Comput. Methods Appl. Mech. Eng. 50 (1985), 107-120. Zbl 0546.73057, MR 0802335, 10.1016/0045-7825(85)90085-4; reference:[7] Christen, J. A., Fox, C.: Markov chain Monte Carlo using an approximation.J. Comput. Graph. Statist. 14 (2005), 795-810. MR 2211367, 10.1198/106186005X76983; reference:[8] Domesová, S., Béreš, M.: Inverse problem solution using Bayesian approach with application to Darcy flow material parameters estimation.Adv. Electr. Electron. Eng. 15 (2017), 258-266. 10.15598/aeee.v15i2.2236; reference:[9] Domesová, S., Béreš, M.: A Bayesian approach to the identification problem with given material interfaces in the Darcy flow.Int. Conf. High Performance Computing in Science and Engineering, 2017 T. Kozubek et al. Springer International Publishing, Cham (2018), 203-216. 10.1007/978-3-319-97136-0_15; reference:[10] Foreman-Mackey, D., Hogg, D. W., Lang, D., Goodman, J.: emcee: The MCMC hammer.Publ. Astron. Soc. Pacific 125 (2013), 306-312. 10.1086/670067; reference:[11] Gatica, G. N.: A Simple Introduction to the Mixed Finite Element Method. Theory and Applications.SpringerBriefs in Mathematics, Springer, Cham (2014). Zbl 1293.65152, MR 3157367, 10.1007/978-3-319-03695-3; reference:[12] Haslinger, J., Blaheta, R., Hrtus, R.: Identification problems with given material interfaces.J. Comput. Appl. Math. 310 (2017), 129-142. Zbl 1347.49052, MR 3544595, 10.1016/j.cam.2016.06.023; reference:[13] Lord, G. J., Powell, C. E., Shardlow, T.: An Introduction to Computational Stochastic PDEs.Cambridge Texts in Applied Mathematics, Cambridge University Press, Cambridge (2014). Zbl 1327.60011, MR 3308418, 10.1017/CBO9781139017329; reference:[14] Mathworks: Matlab Optimization Toolbox User's Guide.Available at https://uk.mathworks.com/products/optimization.html (2017).; reference:[15] Powell, C. E., Silvester, D., Simoncini, V.: An efficient reduced basis solver for Stochastic Galerkin matrix equations.SIAM J. Sci. Comput. 39 (2017), A141--A163. Zbl 1381.35257, MR 3594329, 10.1137/15M1032399; reference:[16] Pultarová, I.: Hierarchical preconditioning for the stochastic Galerkin method: Upper bounds to the strengthened CBS constants.Comput. Math. Appl. 71 (2016), 949-964. MR 3461271, 10.1016/j.camwa.2016.01.006; reference:[17] Robert, C. P.: The Bayesian Choice. From Decision-Theoretic Foundations to Computational Implementation.Springer Texts in Statistics, Springer, New York (2007). Zbl 1129.62003, MR 2723361, 10.1007/0-387-71599-1; reference:[18] Robert, C. P., Casella, G.: Monte Carlo Statistical Methods.Springer Texts in Statistics, Springer, New York (2004). Zbl 1096.62003, MR 2080278, 10.1007/978-1-4757-4145-2; reference:[19] Sokal, A.: Monte Carlo methods in statistical mechanics: Foundations and new algorithms.Functional Integration: Basics and Applications, 1996 C. DeWitt-Morette et al. NATO ASI Series. Series B. Physics. 361, Plenum Press, New York (1997), 131-192. Zbl 0890.65006, MR 1477456, 10.1007/978-1-4899-0319-8_6; reference:[20] Stuart, A. M.: Inverse problems: A Bayesian perspective.Acta Numerica 19 (2010) 451-559. Zbl 1242.65142, MR 2652785, 10.1017/S0962492910000061; reference:[21] Thompson, M. B.: A comparison of methods for computing autocorrelation time.Available at https://arxiv.org/abs/1011.0175 (2010).; reference:[22] Vogel, C. R.: Computational Methods for Inverse Problems.Frontiers in Applied Mathematics 23, Society for Industrial and Applied Mathematics, Philadelphia (2002). Zbl 1008.65103, MR 1928831, 10.1137/1.9780898717570; reference:[23] Xiu, D.: Numerical Methods for Stochastic Computations. A Spectral Method Approach.Princeton University Press, Princeton (2010). Zbl 1210.65002, MR 2723020, 10.2307/j.ctv7h0skv
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2Academic Journal
المؤلفون: Boček, Pavel, Šiman, Miroslav
مصطلحات موضوعية: keyword:multivariate quantile, keyword:regression quantile, keyword:halfspace depth, keyword:regression depth, keyword:depth contour, msc:62-04, msc:62H05, msc:62J99, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR3684681; zbl:Zbl 06819619; reference:[1] Boček, P., Šiman, M.: modQR: Multiple-Output Directional Quantile Regression.R package version 0.1.0, 2015.; reference:[2] Boček, P., Šiman, M.: Directional quantile regression in Octave and MATLAB.Kybernetika 52 (2016), 28-51. MR 3482609, 10.14736/kyb-2016-1-0028; reference:[3] Chakraborty, B.: On multivariate quantile regression.J. Statist. Planning Inference 110 (2003), 109-132. MR 1944636, 10.1016/s0378-3758(01)00277-4; reference:[4] Charlier, I., Paindaveine, D., Saracco, J.: Multiple-output regression through optimal quantization.ECARES Working Paper 2016-18.; reference:[5] Chaudhury, P.: On a geometric notion of quantiles for multivariate data.J. Amer. Stat. Assoc. 91 (1996), 862-872. MR 1395753, 10.2307/2291681; reference:[6] Cheng, Y., Gooijer, J. G. De: On the $u$th geometric conditional quantile.J. Statist. Planning Inference 137 (2007), 1914-1930. Zbl 1118.62051, MR 2323873, 10.1016/j.jspi.2006.02.014; reference:[7] Došlá, Š.: Conditions for bimodality and multimodality of a mixture of two unimodal densities.Kybernetika 45 (2009) 279-292. Zbl 1165.62304, MR 2518152; reference:[8] Hallin, M., Lu, Z., Paindaveine, D., Šiman, M.: Local bilinear multiple-output quantile/depth regression.Bernoulli 21 (2015), 1435-1466. MR 3352050, 10.3150/14-bej610; reference:[9] Hallin, M., Paindaveine, D., Šiman, M.: Multivariate quantiles and multiple-output regression quantiles: From ${L}_1$ optimization to halfspace depth.Ann. Statist. 38 (2010), 635-669. MR 2604670, 10.1214/09-aos723; reference:[10] Hallin, M., Paindaveine, D., Šiman, M.: Rejoinder.Ann. Statist. 38 (2010), 694-703. MR 2604674, 10.1214/09-aos723rej; reference:[11] Koenker, R.: Quantile Regression.Cambridge University Press, New York 2005. Zbl 1236.62031, MR 2268657, 10.1017/cbo9780511754098; reference:[12] Koenker, R., Bassett, G. J.: Regression quantiles.Econometrica 46 (1978), 33-50. Zbl 0482.62023, MR 0474644, 10.2307/1913643; reference:[13] Koltchinskii, V.: ${M}$-estimation, convexity and quantiles.Ann. Statist. 25 (1997), 435-477. MR 1439309, 10.1214/aos/1031833659; reference:[14] Kong, L., Mizera, I.: Quantile tomography: Using quantiles with multivariate data.Statistica Sinica 22 (2012), 1589-1610. MR 3027100, 10.5705/ss.2010.224; reference:[15] McKeague, I. W., López-Pintado, S., Hallin, M., Šiman, M.: Analyzing growth trajectories.J. Developmental Origins of Health and Disease 2 (2011), 322-329. 10.1017/s2040174411000572; reference:[16] Paindaveine, D., Šiman, M.: On directional multiple-output quantile regression.J. Multivariate Anal. 102 (2011), 193-212. Zbl 1328.62311, MR 2739109, 10.1016/j.jmva.2010.08.004; reference:[17] Paindaveine, D., Šiman, M.: Computing multiple-output regression quantile regions.Comput. Statist. Data Anal. 56 (2012), 840-853. Zbl 1304.65060, MR 2888729, 10.1016/j.csda.2010.11.014; reference:[18] Paindaveine, D., Šiman, M.: Computing multiple-output regression quantile regions from projection quantiles.Comput. Statist. 27 (2012), 29-49. Zbl 1304.65060, MR 2877809, 10.1007/s00180-011-0231-y; reference:[19] Šiman, M.: On exact computation of some statistics based on projection pursuit in a general regression context.Commun. Statist. - Simulation and Computation 40 (2011), 948-956. Zbl 1219.62109, MR 2792475, 10.1080/03610918.2011.560730; reference:[20] Šiman, M.: Precision index in the multivariate context.Commun. Statist. - Theory and Methods 43 (2014), 377-387. MR 3171043, 10.1080/03610926.2012.661509
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3Academic Journal
المؤلفون: Boček, Pavel, Šiman, Miroslav
مصطلحات موضوعية: keyword:quantile regression, keyword:multivariate quantile, keyword:regression quantile, keyword:directional quantile, keyword:halfspace depth, keyword:regression depth, keyword:depth contour, keyword:Octave, keyword:MATLAB, msc:62-04, msc:62H05, msc:62J99, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR3482609; zbl:Zbl 1374.62002; reference:[1] Barber, C. B., Huhdanpaa, H.: The quickhull algorithm for convex hulls.ACM Trans. Math. Software 22 (1996), 469-483. Zbl 0884.65145, MR 1428265, 10.1145/235815.235821; reference:[2] Boček, P., Šiman, M.: Directional quantile regression in R.Submitted, 2016.; reference:[3] Chen, Z., Tyler, D. E.: On the behavior of Tukey's depth and median under symmetric stable distributions.J. Statist. Planning Inference 122 (2004), 111-124. Zbl 1040.62038, MR 2057917, 10.1016/j.jspi.2003.06.017; reference:[4] Cheng, Y., Gooijer, J. G. De: On the $u$th geometric conditional quantile.J. Statist. Planning Inference 137 (2007), 1914-1930. Zbl 1118.62051, MR 2323873, 10.1016/j.jspi.2006.02.014; reference:[5] Došlá, Š.: Conditions for bimodality and multimodality of a mixture of two unimodal densities.Kybernetika 45 (2009), 279-292. Zbl 1165.62304, MR 2518152; reference:[6] Dutta, S., Ghosh, A. K., Chaudhuri, P.: Some intriguing properties of Tukey's half-space depth.Bernoulli 17 (2011), 1420-1434. Zbl 1229.62063, MR 2854779, 10.3150/10-bej322; reference:[7] Eaton, J. W., Bateman, D., Hauberg, S.: GNU Octave Version 3.0.1 Manual: A High-Level Interactive Language for Numerical Computations.CreateSpace Independent Publishing Platform, 2009.; reference:[8] Hallin, M., Lu, Z., Paindaveine, D., Šiman, M.: Local bilinear multiple-output quantile/depth regression.Bernoulli 21 (2015), 1435-1466. MR 3352050, 10.3150/14-bej610; reference:[9] Hallin, M., Paindaveine, D., Šiman, M.: Multivariate quantiles and multiple-output regression quantiles: From $L_1$ optimization to halfspace depth.The Ann. Statist. 38 (2010), 635-669. Zbl 1183.62088, MR 2604670, 10.1214/09-aos723; reference:[10] Hallin, M., Paindaveine, D., Šiman, M.: Rejoinder.The Ann. Statist. 38 (2010), 694-703. MR 2604674, 10.1214/09-aos723rej; reference:[11] Koenker, R.: Quantile Regression.Cambridge University Press, New York 2005. Zbl 1236.62031, MR 2268657, 10.1017/cbo9780511754098; reference:[12] Koenker, R., Bassett, G. J.: Regression quantiles.Econometrica 46 (1978), 33-50. Zbl 0482.62023, MR 0474644, 10.2307/1913643; reference:[13] Koltchinskii, V.: $M$-estimation, convexity and quantiles.The Ann. Statist. 25 (1997), 435-477. Zbl 0878.62037, MR 1439309, 10.1214/aos/1031833659; reference:[14] Kong, L., Mizera, I.: Quantile tomography: Using quantiles with multivariate data.Statist. Sinica 22 (2012), 1589-1610. MR 3027100, 10.5705/ss.2010.224; reference:[15] McKeague, I. W., López-Pintado, S., Hallin, M., Šiman, M.: Analyzing growth trajectories.J. Developmental Origins of Health and Disease 2 (2011), 322-329. 10.1017/s2040174411000572; reference:[16] Paindaveine, D., Šiman, M.: On directional multiple-output quantile regression.J. Multivariate Anal. 102 (2011), 193-212. Zbl 1328.62311, MR 2739109, 10.1016/j.jmva.2010.08.004; reference:[17] Paindaveine, D., Šiman, M.: Computing multiple-output regression quantile regions.Comput. Statist. Data Anal. 56 (2012), 840-853. Zbl 1304.65060, MR 2888729, 10.1016/j.csda.2010.11.014; reference:[18] Paindaveine, D., Šiman, M.: Computing multiple-output regression quantile regions from projection quantiles.Computat. Statist. 27 (2012), 29-49. Zbl 1304.65060, MR 2877809, 10.1007/s00180-011-0231-y; reference:[19] Team, R Development Core: R: A Language and Environment for Statistical Computing.R Foundation for Statistical Computing, Vienna 2008.; reference:[20] Rousseeuw, P. J., Ruts, I.: The depth function of a population distribution.Metrika 49 (1999), 213-244. Zbl 1093.62540, MR 1731769; reference:[21] MathWorks, The, Inc.: MATLAB.Natick, Massachusetts 2013.; reference:[22] Sturm, J. F.: Using SeDuMi 1.02, a MATLAB Toolbox for Optimization over Symmetric Cones.Optimization Methods and Software 11-12 (1999), 625-653. Zbl 0973.90526, MR 1778433; reference:[23] Šiman, M.: On exact computation of some statistics based on projection pursuit in a general regression context.Comm. Statist. - Simul. Comput. 40 (2011), 948-956. Zbl 1219.62109, MR 2792475, 10.1080/03610918.2011.560730; reference:[24] Šiman, M.: Precision index in the multivariate context.Comm. Statist. - Theory and Methods 43 (2014), 377-387. MR 3171043, 10.1080/03610926.2012.661509
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4Academic Journal
المؤلفون: Slámová, Lenka, Klebanov, Lev B.
مصطلحات موضوعية: keyword:discrete stable distribution, keyword:parameter estimation, keyword:maximum likelihood, msc:60E07, msc:60E10, msc:62F12, msc:62G05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR3301786; zbl:Zbl 1308.60022; reference:[1] Devroye, L.: A triptych of discrete distributions related to the stable law.Stat. Probab. Lett. 18 (1993), 349-351. Zbl 0794.60007, MR 1247445, 10.1016/0167-7152(93)90027-G; reference:[2] Feuerverger, A., McDunnough, P.: On the efficiency of empirical characteristic function procedure.J. Roy. Stat. Soc. Ser. B 43 (1981), 20-27. MR 0610372; reference:[3] Gerlein, O. V., Kagan, A. M.: Hilbert space methods in classical problems of mathematical statistics.J. Soviet Math. 12 (1979), 184-213. Zbl 0354.62007, 10.1007/BF01262718; reference:[4] Kagan, A. M.: Fisher information contained in a finite-dimensional linear space, and a correctly posed version of the method of moments (in Russian).Problemy Peredachi Informatsii 12 (1976), 20-42. MR 0413340; reference:[5] Klebanov, L. B., Melamed, I. A.: Several notes on Fisher information in presence of nuisance parameters.Statistics: J. Theoret. Appl. Stat. 9 (1978), 85-90. Zbl 0381.62007, MR 0506482; reference:[6] Klebanov, L. B., Slámová, L.: Integer valued stable random variables.Stat. Probab. Lett. 83 (2013), 1513-1519. Zbl 1283.60022, MR 3048317, 10.1016/j.spl.2013.02.016; reference:[7] Slámová, L., Klebanov, L. B.: Modelling financial returns with discrete stable distributions.In: Proc. 30th International Conference Mathematical Methods in Economics (J. Ramík and D. Stavárek, eds.), Silesian University in Opava, School of Business Administration in Karviná, 2012, pp. 805-810.; reference:[8] Steutel, F. W., Harn, K. van: Discrete analogues of self-decomposability and stability.Ann. Probab. 7 (1979), 893-899. MR 0542141, 10.1214/aop/1176994950
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5Academic Journal
المؤلفون: Hušková, Marie, Meintanis, Simon G.
مصطلحات موضوعية: keyword:empirical characteristic function, keyword:kernel regression estimators, msc:62F05, msc:62G10, msc:62J05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2650076; zbl:Zbl 1186.62029; reference:[1] M. Bilodeau and P. de Lafaye de Micheaux: A multivariate empirical characteristic function test of independence with normal marginals.J. Multivariate Anal. 95 (2005), 345–369. MR 2170401; reference:[2] H. D. Bondell: Testing goodness-of-fit in logistic case-control studies.Biometrika 94 (2007), 487–495. Zbl 1132.62020, MR 2380573; reference:[3] H. Dette: A consistent test for the functional form of a regression function based on a difference of variance estimators.Ann. Statist. 27 (1999), 1012–1040. MR 1724039; reference:[4] R. L. Eubank, Chin-Shang Li, and Suojin Wang: Testing lack-of-fit of parametric regression models using nonparametric regression techniques.Statistica Sinica 15 (2005), 135–152. MR 2125724; reference:[5] Jianqing Fan and Li-Shan Huang: Goodness-of-fit tests for parametric regression models.J. Amer. Statist. Assoc. 96 (2001), 640–652. MR 1946431; reference:[6] A. K. Gupta, N. Henze, and B. Klar: Testing for affine equivalence of elliptically symmetric distributions.J. Multivariate Anal. 88 (2004), 222–242. MR 2025611; reference:[7] W. Härdle and E. Mammen: Comparing nonparametric versus parametric regression fits.Ann. Statist. 21 (1993), 1926–1947. MR 1245774; reference:[8] N. Henze, B. Klar, and S. G. Meintanis: Invariant tests for symmetry about an unspecified point based on the empirical characteristic function.J. Multivariate Anal. 87 (2003), 275–297. MR 2016939; reference:[9] M. Hušková and S. G. Meintanis: Change point analysis based on empirical characteristic functions.Metrika 63 (2006), 145–168. MR 2242537; reference:[10] M. Hušková and S. G. Meintanis: Tests for the error distribution in nonparametric possibly heteroscedastic regression models.To appear in Test.; reference:[11] A. Kankainen and N. Ushakov: A consistent modification of a test for independence based on the empirical characteristic function.J. Math. Sci. 89 (1998), 1486–1494. MR 1632247; reference:[12] Qi Li and Suojin Wang: A simple consistent bootstrap test for a parametric regression function.J. Econometrics 87 (1998), 145–165. MR 1648892; reference:[13] S. G. Meintanis: Permutation tests for homogeneity based on the empirical characteristic function.J. Nonparametr. Statist. 17 (2005), 583–592. Zbl 1065.62084, MR 2141363; reference:[14] N. Neumeyer: A bootstrap version of the residual-based smooth empirical distribution function.J. Nonparametr. Statist. 20 (2008), 153–174. Zbl 1141.62027, MR 2407963; reference:[15] W. Stute, W. Gonzáles Manteiga, and M. Presedo Quindimil: Bootstrap approximation in model checks for regression.J. Amer. Statist. Assoc. 93 (1998), 141–149. MR 1614600; reference:[16] I. van Keilegom, W. Gonzáles Manteiga, and C. Sanchez Sellero: Goodness-of-fit tests in parametric regression based on the estimation of the error distribution.Test 17 (2008), 401–415. MR 2434335; reference:[17] G. A. F. Seber and C. J. Wild: Nonlinear Regression.Wiley, New York 1989, pp. 501–513. MR 0986070; reference:[18] Yoon-Jae Whang: Consistent bootstrap tests of parametric regression functions.J. Econometrics 98 (2000), 27–46. MR 1790649; reference:[19] H. White: Consequences and detection of misspecified nonlinear regression models.J. Amer. Statist. Assoc. 76 (1981), 419–433. Zbl 0467.62058, MR 0624344; reference:[20] H. White: Maximum likelihood estimation of misspecified models.Econometrica 50 (1982), 1–25. Zbl 0518.62092, MR 0640163; reference:[21] C. F. Wu: Asymptotic theory of nonlinear least-squares estimation.Ann. Statist. 9 (1981) 501–513. Zbl 0475.62050, MR 0615427; reference:[22] A. I. Zayed: Handbook of Function and Generalized Function Transformations.CRC Press, New York 1996. Zbl 0851.44002, MR 1392476
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6Academic Journal
المؤلفون: Meintanis, Simos G.
مصطلحات موضوعية: keyword:goodness-of-fit test, keyword:empirical moments, keyword:ageing distributions, keyword:Bahadur efficiency, msc:62E20, msc:62G10, msc:62G20, msc:62N05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2650075; zbl:Zbl pZbl 1186.62056; reference:[1] I. A. Ahmad: Moment inequalities of aging families of distributions with hypothesis testing applications.J. Statist. Plann. Infer. 92 (2001), 121–132. MR 1809700; reference:[2] R. R. Bahadur: Stochastic comparison of tests.Ann. Math. Statist. 31 (1960), 276–295. Zbl 0201.52203, MR 0116413; reference:[3] V. Bening and V. Korolev: Estimation problems for fractional stable distributions.In: Trans. XXIV Internat. Seminar on Stability Problems for Stochastic Models 2004 (Andronov et al., eds.), Transport and Telecommunication Institute, Riga, Latvia, pp. 270–276.; reference:[4] M. Carrasco and J.-P. Florens: Generalization of GMM to a continuum of moment conditions.Econometr. Theory 16 (2000), 797–834. MR 1803711; reference:[5] M. Carrasco and J.-P. Florens: Simulation-based method of moments and efficiency.J. Bus. Econom. Statist. 20 (2002), 482–492. MR 1945605; reference:[6] G. Chaudhuri: Testing exponentiality against $L$-distributions.J. Statist. Plann. Infer. 64 (1997), 249–255. Zbl 0914.62030, MR 1621616; reference:[7] H. Cramér: Mathematical Methods of Statistics.Princeton University Press, Princeton 1946. MR 0016588; reference:[8] R. D’Agostino and M. Stephens: Goodness-of-Fit Techniques.Marcel Dekker, New York 1986. MR 0874534; reference:[9] B. S. Dhillon: Lifetime distributions.IEEE Trans. Reliability 30 (1981), 457–459.; reference:[10] K. A. Doksum and B. S. Yandell: Tests for exponentiality.In: Handbook of Statistics 4: Nonparametric methods (Krishnaiah and Sen, eds.), North-Holland, Amsterdam 1984, pp. 579–611. MR 0831730; reference:[11] T. W. Epps and L. B. Pulley: A test for exponentiality vs.monotone hazard alternatives derived from the empirical characteristic function. J. Roy. Statist. Soc. B48 (1986), 206–213. MR 0867998; reference:[12] N. Henze and B. Klar: Testing exponentiality against the ${\cal {L}}$-class of life distributions.Math. Method. Statist. 10 (2001), 232–246. MR 1852070; reference:[13] N. Henze and S. G. Meintanis: Recent and classical tests for exponentiality: a partial review with comparisons.Metrika 61 (2005), 29–45. MR 2126435; reference:[14] B. Klar: A class of tests for exponentiality against HNBUE alternatives.Statist. Probab. Lett. 47 (2000), 199–207. Zbl 0977.62103, MR 1747107; reference:[15] S. G. Meintanis: Efficient moment-type estimation in exponentiated laws.Math. Methods Statist. 15 (2007), 444–455. MR 2301661; reference:[16] M. Mitra and S. K. Basu: On a nonparametric family of life distributions and its dual.J. Statist. Plann. Infer. 39 (1994), 385–397. MR 1278590; reference:[17] A. R. Mugdadi and I. A. Ahmad: Moment inequalities derived from comparing life with its equilibrium form.J. Statist. Plann. Infer. 134 (2005), 303–317. MR 2200060; reference:[18] Ya. Yu. Nikitin: Asymptotic Efficiency of Nonparametric Tests.Cambridge University Press, New York 1995. Zbl 1171.62031, MR 1415127; reference:[19] B. L. S. Prakasa Rao: Asymptotic Theory of Statistical Inference.Wiley, New York 1987. Zbl 0604.62025, MR 0874342; reference:[20] F. Rublík: On optimality of the LR tests in the sence of exact slopes.I. General case. Kybernetika 25 (1989), 13–25. MR 0987853; reference:[21] F. Rublík: On optimality of the LR tests in the sence of exact slopes.II. Application to individual distributions. Kybernetika 25 (1989), 117–135. MR 0995954; reference:[22] A. I. Zayed: Handbook of Function and Generalized Function Transformations.CRC Press, New York 1996. Zbl 0851.44002, MR 1392476
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7Academic Journal
المؤلفون: Mrkvička, Tomáš, Rataj, Jan
مصطلحات موضوعية: keyword:random closed set, keyword:convex ring, keyword:curvature measure, keyword:intrinsic volume, msc:60D05, msc:62G05, msc:62G07, msc:62G20, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2650074; zbl:Zbl 1186.62050; reference:[1] R. Klette, A. Rosenfeld: Digital Geometry.Elsevier, New York 2004. Zbl 1064.68090, MR 2095127; reference:[2] T. Mrkvička, J. Rataj: On estimation of intrinsic volume densities of stationary random closed sets.Stoch. Proc. Appl. 118 (2008), 2, 213–231. MR 2376900, 10.1016/j.spa.2007.04.004; reference:[3] T. Mrkvička: Estimation of intrinsic volume via parallel sets in plane and space.Inzynieria Materialowa 4 (2008), 392–395.; reference:[4] X.-X. Nguyen, H. Zessin: Ergodic theorems for spatial processes.Z. Wahrsch. Verw. Gebiete 48 (1979), 133–158 Zbl 0397.60080, MR 0534841, 10.1007/BF01886869; reference:[5] J. Ohser, F. Mücklich: Statistical Analysis of Microstructures in Materials Science.Wiley, Chichester 2000.; reference:[6] J. Rataj: Estimation of intrinsic volumes from parallel neighbourhoods.Rend. Circ. Mat. Palermo, Ser. II, Suppl. 77 (2006), 553–563. Zbl 1101.62084, MR 2245722; reference:[7] V. Schmidt, E. Spodarev: Joint estimators for the specific intrinsic volumes of stationary random sets.Stoch. Proc. Appl. 115 (2005), 959–981. Zbl 1075.60006, MR 2138810, 10.1016/j.spa.2004.12.007; reference:[8] R. Schneider, W. Weil: Stochastische Geometrie.Teubner, Stuttgart 2000. Zbl 0964.52009, MR 1794753
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8Academic Journal
المؤلفون: Kraus, David
مصطلحات موضوعية: keyword:Neyman's smooth test, keyword:proportional hazards, keyword:proportional odds, keyword:survival analysis, keyword:transformation model, keyword:two-sample test, msc:62N01, msc:62N02, msc:62N03, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2518151; zbl:Zbl 1165.62072; reference:[1] P. K. Andersen, O. Borgan, R. D. Gill, and N. Keiding: Statistical Models Based on Counting Processes.Springer, New York 1993. MR 1198884; reference:[2] P. K. Andersen and R. D. Gill: Cox’s regression model for counting processes: a large sample study.Ann. Statist. 10 (1982), 1100–1120. MR 0673646; reference:[3] V. Bagdonavičius and M. Nikulin: Generalized proportional hazards model based on modified partial likelihood.Lifetime Data Anal. 5 (1999), 329–350. MR 1758967; reference:[4] V. Bagdonavičius and N. Nikulin: On goodness-of-fit for the linear transformation and frailty models.Statist. Probab. Lett. 47 (2000), 177–188. MR 1747106; reference:[5] V. Bagdonavičius and M. Nikulin: Accelerated life models.Modeling and Statistical Analysis. Chapman & Hall/CRC, Boca Raton 2001.; reference:[6] K. Chen, Z. Jin, and Z. Ying: Semiparametric analysis of transformation models with censored data.Biometrika 89 (2002), 659–668. MR 1929170; reference:[7] D. Collett: Modelling Survival Data in Medical Research.Chapman & Hall/CRC, Boca Raton 2003. MR 1999899; reference:[8] D. M. Dabrowska and K. A. Doksum: Estimation and testing in a two-sample generalized odds-rate model.J. Amer. Statist. Assoc. 83 (19í8), 744–749. MR 0963802; reference:[9] J.-Y. Dauxois and S. N. U. A. Kirmani: Testing the proportional odds model under random censoring.Biometrika 90 (2003), 913–922. MR 2024766; reference:[10] T. R. Fleming and D. P. Harrington: Counting Processes and Survival Analysis.Wiley, New York 1991. MR 1100924; reference:[11] R. D. Gill and M. Schumacher: A simple test of the proportional hazards assumption.Biometrika 74 (1987), 289–300.; reference:[12] D. Kraus: Data-driven smooth tests of the proportional hazards assumption.Lifetime Data Anal. 13 (2007), 1–16. Zbl 1121.62086, MR 2355293; reference:[13] T. Ledwina: Data-driven version of Neyman’s smooth test of fit.J. Amer. Statist. Assoc. 89 (1994), 1000–1005. Zbl 0805.62022, MR 1294744; reference:[14] D. Y. Lin, L. J. Wei, and Z. Ying: Checking the Cox model with cumulative sums of martingale-based residuals.Biometrika 80 (1993), 557–572. MR 1248021; reference:[15] T. Martinussen and T. H. Scheike: Dynamic Regression Models for Survival Data.Springer, New York 2006. MR 2214443; reference:[16] S. A. Murphy, A. J. Rossini, and A. W. van der Vaart: Maximum likelihood estimation in the proportional odds model.J. Amer. Statist. Assoc. 92 (1997), 968–976. MR 1482127; reference:[17] J. C. W. Rayner and D. J. Best: Smooth Tests of Goodness of Fit.Oxford University Press, New York 1989. MR 1029526; reference:[18] D. Sengupta, A. Bhattacharjee, and B. Rajeev: Testing for the proportionality of hazards in two samples against the increasing cumulative hazard ratio alternative.Scand. J. Statist. 25 (1998), 637–647. MR 1666780; reference:[19] C. A. Struthers and J. D. Kalbfleisch: Misspecified proportional hazard models.Biometrika 73 (1986), 363–369. MR 0855896; reference:[20] A. W. van der Vaart and J. A. Wellner: Weak Convergence and Empirical Processes.With Applications to Statistics. Springer, New York 1996. MR 1385671; reference:[21] L. J. Wei: Testing goodness of fit for proportional hazards model with censored observations.J. Amer. Statist. Assoc. 79 (1984), 649–652. Zbl 0547.62070, MR 0763583
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9Academic Journal
المؤلفون: Vrbková, Jana
مصطلحات موضوعية: keyword:Linear models with constraints, keyword:compartmental analysis, keyword:nonlinear models, keyword:linearization via a Taylor series, msc:62F30, msc:62H12, msc:62H99, msc:62J02, msc:62J05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2641957; zbl:Zbl 1191.62120; reference:[1] Kubáček, L., Kubáčková, L.: Statistics and Metrology.Vyd. Univ. Palackého, Olomouc, 2000 (in Czech).; reference:[2] Fišerová, E., Kubáček, L., Kunderová, P.: Linear Statistical Models, Regularity and Singularities.Academia, Praha, 2007.; reference:[3] Rao, C. R., Mitra, S. K.: Generalized Inverse of Matrices and its Applications.J. Wiley, New York–London–Sydney–Toronto, 1971. Zbl 0236.15005, MR 0338013; reference:[4] Hagiwara, M., Rusinek, H., Lee, V. S., Losada, M., Bannan, M. A., Krinsky, G. A., Taouli, B.: Advanced Liver Fibrosis: Diagnosis with 3D Whole-Liver Perfusion MR Imaging?Initial Experience.Radiology 246 (2008), 926–934.; reference:[5] Holčík, J.: Modelování a simulace biologických systémů.ČVUT, Praha, 2006 (in Czech).
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10Academic Journal
المؤلفون: Čížek, Pavel
مصطلحات موضوعية: keyword:asymptotic efficiency, keyword:least weighted squares, keyword:robust regression, keyword:time series, msc:62F10, msc:62F12, msc:62F35, msc:62J05, msc:62L12, msc:62M10, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2411129; zbl:Zbl 1189.62140; reference:[1] Balke, N. S., Fomby, T. B.: Large shocks, small shocks, and economic fluctuations: outliers in macroeconomic time series.J. Appl. Econom. 9 (1994), 181-200. 10.1002/jae.3950090205; reference:[2] Čížek, P.: Least trimmed squares in nonlinear regression under dependence.J. Statist. Plann. Inference 136 (2006), 3967-3988. Zbl 1103.62061, MR 2299174, 10.1016/j.jspi.2005.05.004; reference:[3] Čížek, P.: General trimmed estimation: robust approach to nonlinear and limited dependent variable models. CentER discussion paper.Econom. Theory (to appear). MR 2456536; reference:[4] Čížek, P.: Efficient robust estimation of regression models. CentER discussion paper Vol. 87.CentER Tilburg University Tilburg (2007).; reference:[5] Genton, M. G., Lucas, A.: Comprehensive definitions of breakdown points for independent and dependent observations.J. R. Stat. Soc., Stat. Methodol. Ser. B 65 (2003), 81-94. Zbl 1063.62038, MR 1959094, 10.1111/1467-9868.00373; reference:[6] Gervini, D., Yohai, V. J.: A class of robust and fully efficient regression estimators.Ann. Stat. 30 (2002), 583-616. Zbl 1012.62073, MR 1902900, 10.1214/aos/1021379866; reference:[7] Mašíček, L.: Diagnostics and sensitivity of robust models.Unpublished Ph.D. Thesis Faculty of Mathematics and Physics, Charles University Prague (2004).; reference:[8] Preminger, A., Franck, R.: Foreign exchange rates: a robust regression approach.Int. J. Forecasting 23 (2007), 71-84. 10.1016/j.ijforecast.2006.04.009; reference:[9] Rousseeuw, P. J.: Multivariate estimation with high breakdown point.Mathematical statistics and applications, Vol. B W. Grossman, G. Pflug, I. Vincze, W. Wertz Reidel Dordrecht (1985), 283-297. Zbl 0609.62054, MR 0851060; reference:[10] Rousseeuw, P. J., Leroy, A. M.: Robust Regression and Outlier Detection.John Wiley & Sons New York (1987). Zbl 0711.62030, MR 0914792; reference:[11] Sakata, S., White, H.: High breakdown point conditional dispersion estimation with application to S&P 500 daily returns volatility.Econometrica 66 (1998), 529-567. 10.2307/2998574; reference:[12] Temple, J. R. W.: Robustness tests of the augmented Solow model.J. Appl. Econometrics 13 (1998), 361-375. 10.1002/(SICI)1099-1255(199807/08)13:43.0.CO;2-1; reference:[13] Dijk, D. Van, Franses, P. H., Lucas, A.: Testing for ARCH in the presence of additive outliers.J. Appl. Econom. 14 (1999), 539-562. 10.1002/(SICI)1099-1255(199909/10)14:53.0.CO;2-W; reference:[14] Víšek, J. Á.: The least weighted squares II. Consistency and asymptotic normality.Bulletin of the Czech Econom. Soc. 9 (2002), 1-28. MR 2208518; reference:[15] Víšek, J. Á.: Instrumental weighted variables.Austr. J. Stat. 35 (2006), 379-387.; reference:[16] Woo, J.: Economic, political, and institutional determinants of public deficits.J. Public Economics 87 (2003), 387-426. 10.1016/S0047-2727(01)00143-8
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11Academic Journal
المؤلفون: Antoch, Jaromír, Legát, David
مصطلحات موضوعية: keyword:change point estimation, keyword:Markov chain Monte Carlo (MCMC), keyword:Metropolis-Hastings algorithm, keyword:Gibbs sampler, keyword:Bayesian statistics, keyword:Klementinum temperature series, msc:62F40, msc:62P12, msc:65C05, msc:65C40, msc:65C60, msc:86A10
وصف الملف: application/pdf
Relation: mr:MR2433722; zbl:Zbl 1199.65016; reference:[1] Antoch, J., Hušková, M., Jarušková, D.: Off-line statistical process control.In: Multivariate Total Quality Control, Chapter 1 Physica-Verlag/Springer Heidelberg (2002), 1-86. Zbl 1039.62110, MR 1886416; reference:[2] Antoch, J., Hušková, M.: Estimators of changes.Asymptotics, Nonparametrics, and Time Series Marcel Dekker Basel (1999), 533-577. MR 1724708; reference:[3] Barry, D., Hartigan, J.: A Bayesian analysis for change-point problems.J. Am. Stat. Assoc. 88 (1993), 309-319. Zbl 0775.62065, MR 1212493; reference:[4] Carlin, B. P., Gelfand, A. E., Smith, A. F. M.: Hierarchical Bayesian analysis of change point problems.Appl. Stat. 41 (1992), 389-405. 10.2307/2347570; reference:[5] Csörgő, M., Horváth, L.: Limit Theorems in Change-Point Analysis.J. Wiley & Sons New York (1997). MR 2743035; reference:[6] Gilks, W. R., Richardson, S., (eds.), D. J. Spiegelhalter: Markov Chain Monte Carlo in Practice.Chapman & Hall/CRC London (1995). MR 1397966; reference:[7] Hastings, W. K.: Monte Carlo sampling methods using Markov chains and their applications.Biometrika 57 (1970), 97-109. Zbl 0219.65008, 10.1093/biomet/57.1.97; reference:[8] Hinkley, D. V.: Inference about the intersection in two-phase regression.Biometrika 56 (1969), 495-504. Zbl 0183.48505, 10.1093/biomet/56.3.495; reference:[9] Janžura, M., Nielsen, J.: Segmentation method and change-point problem.ROBUST'02 J. Antoch, G. Dohnal, J. Klaschka JČMF Praha 163-177 Czech.; reference:[10] Jarušková, D.: Some problems with application of change point detection methods to enviromental data.Environmetrics 8 (1997), 469-483. 10.1002/(SICI)1099-095X(199709/10)8:53.0.CO;2-J; reference:[11] Legát, D.: MCMC methods.Master thesis Charles University Praha (2004), Czech.; reference:[12] Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., Teller, E.: Equations of state calculations by fast computing machines.J. Chem. Phys. 21 (1953), 1087-1092. 10.1063/1.1699114; reference:[13] O'Hogan, A., Foster, J.: Kendall's Advanced Theory of Statistics, Bayesian Inference.Arnold London (1999).; reference:[14] Robert, Ch. P., Casella, G.: Monte Carlo Statistical Methods, 2nd ed.Springer Heidelberg (2005). MR 2080278
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12Academic Journal
المؤلفون: Chochola, Ondřej
مصطلحات موضوعية: keyword:sequential test for change in scale, msc:62E20, msc:62J05, msc:62L10, msc:62P20, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2479314; zbl:Zbl 1177.62100; reference:[1] Chochola O.: Rekurzivní postupy pro detekci změny rozdělení (Recursive Procedures for Detection of Changes).Master’s Thesis. Faculty of Mathematics and Physics, Charles University, Prague 2007; reference:[2] Chow Y. S., Teicher H.: Probability Theory: Independence, Interchangeability, Martingales.Third edition. Springer, New York 2003 Zbl 1049.60001; reference:[3] Chu C.-S. J., Stinchcombe, M., White H.: Monitoring structural change.Econometrica 64 (1996), 1045–1065 Zbl 0856.90027; reference:[4] Horváth L., Hušková M., Kokoszka, M., Steinebach J.: Monitoring changes in linear models.J. Stat. Plann. Inference 126 (2004), 225–251 Zbl 1075.62054, MR 2090695; reference:[5] Horváth L., Kokoszka, P., Steinebach J.: On sequential detection of parameter changes in linear regression.Statist. Probab. Lett. 77 (2007), 885–895 Zbl 1117.62079, MR 2363438; reference:[6] Koubková A.: Sequential Change-Point Analysis.Ph.D. Thesis. Faculty of Mathematics and Physics, Charles University, Prague 2006; reference:[7] Leisch F., Hornik, K., Kuan E. M.: Monitoring structural changes with the generalized fluctuation test.Econometric Theory 16 (2000), 835–854 Zbl 0967.62067, MR 1803712; reference:[8] Zeileis A., Kleiber C., Krämer, W., Hornik K.: Testing and dating of structural changes in practice.Comput. Statist. Data Anal. 44 (2003), 1–2, 109–123 MR 2019790; reference:[9] Zeileis A., Leisch F., Hornik, K., Kleiber C.: Strucchange: An $r$ package for testing for structural change in linear regression models.J. Statist. Software 7 (2002), 2; reference:[10] Zeileis A., Leisch F., Kleiber, C., Hornik K.: Monitoring structural change in dynamic econometric models.J. Appl. Econometrics 20 (1005), 99–121 MR 2138205
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13Academic Journal
المؤلفون: Somol, Petr, Novovičová, Jana, Pudil, Pavel
مصطلحات موضوعية: keyword:feature selection, keyword:branch & bound, keyword:sequential search, keyword:mixture model, msc:62G05, msc:62H30, msc:65C60, msc:68T10
وصف الملف: application/pdf
Relation: mr:MR2376333; zbl:Zbl 1134.62041; reference:[1] Das S.: Filters, wrappers and a boosting-based hybrid for feature selection.In: Proc. 18th Internat. Conference Machine Learning, 2001, pp. 74–81; reference:[2] Dash M., Choi K., Scheuermann, P., Liu H.: Feature selection for clustering – a Filter solution.In: Proc. Second Internat. Conference Data Mining, 2002, pp. 15–122; reference:[3] Devijver P. A., Kittler J.: Pattern Recognition: A Statistical Approach.Prentice-Hall, Englewood Cliffs, NJ 1982 Zbl 0542.68071, MR 0692767; reference:[4] Ferri F. J., Pudil P., Hatef, M., Kittler J.: Comparative study of techniques for large-scale feature selection.In: Pattern Recognition in Practice IV (E. S. Gelsema and L. N. Kanal, eds.), Elsevier Science B.V., 1994, pp. 403–413; reference:[5] Fukunaga K.: Introduction to Statistical Pattern Recognition.Academic Press, New York 1990 Zbl 0711.62052, MR 1075415; reference:[6] Graham M. W., Miller D. J.: Unsupervised learning of parsimonious mixtures on large spaces with integrated feature and component selection.IEEE Trans. Signal Process. 54 (2006), 4, 1289–1303; reference:[7] Hodr R., Nikl J., Řeháková B., Veselý, A., Zvárová J.: Possibilities of a prognostic assessment quoad vitam in low birth weight newborns.Acta Facult. Med. Univ. Brunesis 58 (1977), 345–358; reference:[8] Chen X.: An improved branch and bound algorithm for feature selection.Pattern Recognition Lett. 24 (2003), 12, 1925–1933; reference:[9] Jain A. K., Zongker D.: Feature selection: Evaluation, application and small sample performance.IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997), 2, 153–158; reference:[10] Jain A. K., Duin R. P. W., Mao J.: Statistical pattern eecognition: A review.IEEE Trans. Pattern Anal. Mach. Intell. 22 (2000), 2, 4–37; reference:[11] Kohavi R., John G. H.: Wrappers for feature subset selection.Artificial Intelligence 97 (1997), 1–2, 273–324 Zbl 0904.68143; reference:[12] Kudo M., Sklansky J.: Comparison of algorithms that select features for pattern classifiers.Pattern Recognition 33 (2000), 1, 25–41; reference:[13] Law M. H., Figueiredo M. A. T., Jain A. K.: Simultaneous feature selection and clustering using mixture models.IEEE Trans. Pattern Anal. Mach. Intell. 26 (2004), 1154–1166; reference:[14] Liu H., Yu L.: Toward integrating feature selection algorithms for classification and clustering.IEEE Trans. Knowledge Data Engrg. 17 (2005), 491–502; reference:[15] Mayer H. A., Somol P., Huber, R., Pudil P.: Improving statistical measures of feature subsets by conventional and evolutionary approaches.In: Proc. 3rd IAPR Internat. Workshop on Statistical Techniques in Pattern Recognition, Alicante 2000, pp. 77–81 Zbl 0996.68593; reference:[16] McKenzie P., Alder M.: Initializing the EM Algorithm for Use in Gaussian Mixture Modelling.University of Western Australia, 1994; reference:[17] McLachlan G. J.: Discriminant Analysis and Statistical Pattern Recognition.Wiley, New York 1992 Zbl 1108.62317, MR 1190469; reference:[18] McLachlan G. J., Peel D.: Finite Mixture Models.Wiley, New York 2000 Zbl 0963.62061, MR 1789474; reference:[19] Murphy P. M., Aha D. W.: UCI Repository of Machine Learning Databases [ftp.ics.uci.edu]. University of California, Depart ment of Information and Computer Science, Irvine 1994; reference:[20] Narendra P. M., Fukunaga K.: A branch and bound algorithm for feature subset selection.IEEE Trans. Computers 26 (1977), 917–922; reference:[21] Novovičová J., Pudil, P., Kittler J.: Divergence based feature selection for multimodal class densities.IEEE Trans. Pattern Anal. Mach. Intell. 18 (1996), 2, 218–223; reference:[22] Novovičová J., Pudil P.: Feature selection and classification by modified model with latent structure.In: Dealing With Complexity: Neural Network Approach, Springer–Verlag, Berlin 1997, pp. 126–140; reference:[23] Pudil P., Novovičová, J., Kittler J.: Floating search methods in feature selection.Pattern Recognition Lett. 15 (1994), 11, 1119–1125; reference:[24] Pudil P., Novovičová, J., Kittler J.: Feature selection based on approximation of class densities by finite mixtures of special type.Pattern Recognition 28 (1995), 1389–1398; reference:[25] Pudil P., Novovičová, J., Kittler J.: Simultaneous learning of decision rules and important attributes for classification problems in image analysis.Image Vision Computing 12 (1994), 193–198; reference:[26] Sardo L., Kittler J.: Model complexity validation for PDF estimation using Gaussian mixtures.In: Proc. 14th Internat. Conference on Pattern Recognition, Vol. 2, 1998, pp. 195–197; reference:[27] Sebban M., Nock R.: A Hybrid filter/wrapper approach of feature selection using information theory.Pattern Recognition 35 (2002), 835–846 Zbl 0997.68115; reference:[28] Siedlecki W., Sklansky J.: On automatic feature selection.Internat. J. Pattern Recognition Artif. Intell. 2 (1988), 2, 197–220; reference:[29] Somol P., Pudil P., Novovičová, J., Paclík P.: Adaptive floating search methods in feature selection.Pattern Recognition Lett. 20 (1999), 11 – 13, 1157–1163; reference:[30] Somol P., Pudil P.: Oscillating search algorithms for feature selection.In: Proc. 15th IAPR Internat. Conference on Pattern Recognition, 2000, pp. 406–409; reference:[31] Somol P., Pudil P.: Feature Selection Toolbox.Pattern Recognition 35 (2002), 12, 2749–2759 Zbl 1029.68606; reference:[32] Somol P., Pudil. P., Kittler J.: Fast branch & bound algorithms for optimal feature selection.IEEE Trans. Pattern Anal. Mach. Intell. 26 (2004), 7, 900–912; reference:[33] Somol P., Pudil, P., Grim J.: On prediction mechanisms in fast branch & bound algorithms.In: Lecture Notes in Computer Science 3138, Springer–Verlag, Berlin 2004, pp. 716–724 Zbl 1104.68694; reference:[34] Somol P., Novovičová, J., Pudil P.: Flexible-hybrid sequential floating search in statistical feature selection.In: Lecture Notes in Computer Science 4109, Springer–Verlag, Berlin 2006, pp. 632–639; reference:[35] Theodoridis S., Koutroumbas K.: Pattern Recognition.Second edition. Academic Press, New York 2003 Zbl 1093.68103; reference:[36] Wang Z., Yang, J., Li G.: An improved branch & bound algorithm in feature selection.In: Lecture Notes in Computer Science 2639, Springer, Berlin 2003, pp. 549–556 Zbl 1026.68591; reference:[37] Webb A.: Statistical Pattern Recognition.Second edition. Wiley, New York 2002 Zbl 1237.68006, MR 2191640; reference:[38] Yu B., Yuan B.: A more efficient branch and bound algorithm for feature selection.Pattern Recognition 26 (1993), 883–889; reference:[39] Yu L., Liu H.: Feature selection for high-dimensional data: A fast correlation-based filter solution.In: Proc. 20th Internat. Conf. Machine Learning, 2003, pp. 856–863; reference:[40] Benda J. Zvárová a J.: Systém programů TIBIS.Ústav hematologie a krevní transfuze, Praha 1975 (in Czech); reference:[41] Zvárová J., Perez A., Nikl, J., Jiroušek R.: Data reduction in computer-aided medical decision-making.In: MEDINFO 83 (J. H. van Bemmel, M. J. Ball, and O. Wigertz, eds.), North Holland, Amsterdam 1983, pp. 450–453; reference:[42] Zvárová J., Studený M.: Information theoretical approach to constitution and reduction of medical data.Internat. J. Medical Informatics 45 (1997), 1 – 2, 65–74
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14Academic Journal
المؤلفون: Martinková, Patrícia, Zvára, Karel
مصطلحات موضوعية: keyword:Cronbach’s alpha, keyword:Rasch model, keyword:reliability, msc:62F10, msc:62N05, msc:62P25, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2362721; zbl:Zbl 1136.62409; reference:[1] Agresti A.: Categorical Data Analysis.Wiley, New York 2002 MR 1914507; reference:[2] Allison P. D.: A simple proof of the Spearman–Brown formula for continuous test lengths.Psychometrika 40 (1975), 135–136 MR 0488586; reference:[3] Bravo G., Potvin L.: Estimating the reliability of continuous measures with Cronbach’s alpha or the intraclass correlation coefficient: Toward the integration of two traditions.J. Clin. Epidemiol. 44 (1991), 381–390; reference:[4] Christmann A., Aelst S. Van: Robust estimation of Cronbach’s alpha.J. Multivariate Anal. 97 (2006), 1660–1674 MR 2256235; reference:[5] Commenges D., Jacqmin H.: The intraclass correlation coefficient distribution-free definition and test.Biometrics 50 (1994), 517–526 Zbl 0821.62029; reference:[6] Cronbach L. J.: Coefficient alpha and the internal structure of tests.Psychometrika 16 (1951), 297–334; reference:[7] Feldt L. S.: The approximate sampling distribution of Kuder–Richardson reliability coefficient twenty.Psychometrika 30 (1965), 357–370; reference:[8] Guttman L. A.: A basis for analyzing test-retest reliability.Psychometrika 30 (1945), 357–370 Zbl 0060.30902, MR 0014672; reference:[9] Richardson G. Kuder, M.: The theory of estimation of test reliability.Psychometrika 2 (1937), 151–160; reference:[10] Neter J., Wasserman, W., Kutner M. H.: Applied Linear Statistical Models.Richard D. Irwin, Homewood, Il. 1985; reference:[11] Novick M. R., Lewis C.: Coefficient alpha and the reliability of composite measurement.Psychometrika 32 (1967), 1–13; reference:[12] Rasch G.: Probabilistic Models for Some Intelligence and Attainment Tests.The Danish Institute of Educational Research, Copenhagen 1960; reference:[13] Berge J. M. F. ten, Zegers F. E.: A series of lower bounds to the reliability of a test.Psychometrika 43 (1978), 575–579 MR 0521905; reference:[14] Wilcox R. R.: Robust generalizations of classical test reliability and Cronbach’s alpha.British J. Math. Statist. Psych. 45 (1992), 239–254; reference:[15] Zvára K.: Measuring of reliability: Beware of Cronbach.(Měření reliability aneb bacha na Cronbacha, in Czech.) Inform. Bull. Czech Statist. Soc. 12 (2002), 13–20
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15Academic Journal
المؤلفون: Wimmer, Gejza, Witkovský, Viktor
مصطلحات موضوعية: keyword:linear calibration, keyword:analysis function, keyword:regression with errors- in-variables, keyword:Kenward–Roger type approximation, msc:60F05, msc:62E10, msc:62F10, msc:62F25, msc:62H12, msc:62J05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2377922; zbl:Zbl 1135.62059; reference:[3] Casella G., Berger R. L.: Statistical Inference.Duxbury Advanced Series, Belmont 1990 Zbl 0699.62001, MR 1051420; reference:[4] Gleser L. J.: Assessing uncertainty in measurement.Statistical Science 13 (1998), 277–290 Zbl 1099.62502, MR 1665642; reference:[5] Kenward M. G., Roger J. H.: Small sample inference for fixed effects from restricted maximum likelihood.Biometrics 53 (1997), 983–997 Zbl 0890.62042; reference:[6] Kubáček L., Kubáčková L.: One of the calibration Problems.Acta Univ. Palacki. Olomuc., Fac. rer. nat., Mathematica 36 (1997), 117–130 Zbl 0959.62052, MR 1620541; reference:[7] Kubáček L., Kubáčková L.: Statistics and Metrology (in Czech).Univerzita Palackého v Olomouci, Olomouc 2000; reference:[8] Kubáčková L.: Foundations of Experimental Data Analysis.CRC–Press, Boca Raton – Ann Arbor – London – Tokyo 1992 Zbl 0875.62016, MR 1244322; reference:[9] Rao C. R., Mitra K. S.: Generalize Inverse of Matrices and Its Applications.Wiley, New York 1971 MR 0338013; reference:[10] Wimmer G., Witkovský, V., Savin A.: Confidence region for parameters in replicated errors in variables model.In: COMPSTAT: Proc. in Computational Statistics – 16th Symposium, Prague (J. Antoch, ed.), Physica–Verlag, Heidelberg 2004, pp. 1987–1994 MR 2173229
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16Academic Journal
المؤلفون: Martin, Nirian, Pardo, Leandro
مصطلحات موضوعية: keyword:multinomial sampling, keyword:restricted maximum likelihood estimator, keyword:goodness-of-fit, keyword:$I_r$-divergence measure, keyword:Rényi’s divergence measure, msc:62B10, msc:62F03, msc:62F30, msc:62G10, msc:62H15, msc:62H17, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2296510; zbl:Zbl 1245.62011; reference:[1] Agresti A.: Categorical Data Analysis.Wiley, New York 2002 MR 1914507; reference:[2] Andersen E. B.: The Statistical Analysis of Categorical Data.Springer, New York 1990 Zbl 0871.62050; reference:[3] Ali S. M., Silvey S. D.: A general class of coefficient of divergence of one distribution from another.J. Roy. Statist. Soc. 28 (1966), 131–142 MR 0196777; reference:[4] Csiszár I.: Eine Informationstheoretische Ungleichung und ihre Anwendung auf den Bewis der Ergodizität on Markhoffschen Ketten.Publ. Math. Inst. Hungar. Acad. Sci. 8 (1963), 84–108; reference:[5] Dale J. R.: Asymptotic normality of goodness-of-fit statistics for sparse product multinomials.J. Roy. Statist. Soc. Ser. B 41 (1986), 48–59 Zbl 0611.62017, MR 0848050; reference:[6] Haber M., Brown M. B.: Maximum likelihood methods for log-linear models when expected frequencies are subject to linear constraints.J. Amer. Statist. Assoc. 81 (1986), 477–482 Zbl 0604.62058, MR 0845886; reference:[7] Kullback S.: Kullback information.In: Encyclopedia of Statistical Sciences (S. Kotz and N. L. Johnson, eds.), Wiley, New York 1985, Volume 4, pp. 421–425 MR 1044999; reference:[8] Liese F., Vajda I.: Convex Statistical Distances.Teubner, Leipzig 1987 Zbl 0656.62004, MR 0926905; reference:[9] Pardo L., Menéndez M. L.: Analysis of divergence in loglinear models when expected frequencies are subject to linear constraints.Metrika 64 (2006), 63–76 Zbl 1098.62092, MR 2242558, 10.1007/s00184-006-0034-2; reference:[10] Powers D. A., Xie Y.: Statistical Methods for Categorical Data Analysis.Academic Press, San Diego 2000 Zbl 0967.62101, MR 1735454; reference:[11] Rényi A.: On measures of entropy and information.Proc. Fourth Berkeley Symposium on Mathematical Statistics and Probability 1 (1961), pp. 547–561; reference:[12] Vajda I.: Theory of Statistical Inference and Information.Kluwer Academic Publishers, Dordrecht 1989 Zbl 0711.62002
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17Academic Journal
المؤلفون: Kubáček, Lubomír, Marek, Jaroslav
وصف الملف: application/pdf
Relation: mr:MR2181785; zbl:Zbl 1107.62051; reference:[1] KUBÁČEK L.: Two stage regression model.Math Slovaca 38 (1988), 383-393. Zbl 0662.62057, MR 0978769; reference:[2] KUBÁČEK L.: Two stage linear model with constraints.Math. Slovaca 43 (1993), 643-658. Zbl 0793.62036, MR 1273716; reference:[3] KUBÁČEK L.-KUBÁČKOVÁ L.-VOLAUFOVÁ J.: Statistical Models with Linear Structures.Veda, Bratislava, 1995.; reference:[4] KUBÁČEK L.-KUBÁČKOVÁ L.: Statistics and Metrology.Publishing House of Palacký Universitу, Olomouc, 2000. (Czech); reference:[5] KUBÁČEK L.-KUBÁČKOVÁ L.: Two stage networks with constraints of the type I and II.In: Profesor Josef Vуkutil - 90; Sborník příspěvků spolupracovníků a žáku k devadesátinám pana profesora (K. Raděj, ed.), Hlavní úřad vojenské geografie Praha, Vojenský zeměpisný ústav Praha 2002, pp. 58-72. (Czech); reference:[6] MAREK J.: Estimation in connecting measurements.Acta Univ. Palack. Olomuc. Fac. Rerum Natur. Máth. 42 (2003), 69-88. Zbl 1060.62062, MR 2056023; reference:[7] MAREK J.: A digger and surveyor.(From the series "A Statistician's View on Measurement in the Czech and World Literature"), Folia Fac. Sci. Natur. Univ. Masarуk. Brun. Math. 15 (2004), 193-208. MR 2159129; reference:[8] PÁZMAN A.: Nonlinear Statistical Model.Kluwer Academic Press/Ister Science Press, Dordrecht-Boston-London/Bratislava, 1993. MR 1254661; reference:[9] RAO C. R.-MITRA S. K.: Generalized Inverse of Matrices and its Applications.J. Wileу, New York, 1971. Zbl 0236.15005, MR 0338013
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18Academic Journal
المؤلفون: Rublík, František
مصطلحات موضوعية: keyword:multisample rank test for location and scale, keyword:Lepage statistic, keyword:consistency, keyword:non-centrality parameter, keyword:multiple comparisons for location and scale parameters, msc:62E20, msc:62G10, msc:62J15, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2193861; zbl:Zbl 1245.62047; reference:[1] Ansari A. R., Bradley R. A.: Rank-sum test for dispersions.Ann. Math. Statist. 31 (1960), 1174–1189 MR 0117835, 10.1214/aoms/1177705688; reference:[2] Chernoff H., Savage I. R.: Asymptotic normality and efficiency of certain non-parametric test statistics.Ann. Math. Statist. 29 (1958), 972–994 MR 0100322, 10.1214/aoms/1177706436; reference:[3] Conover W. J.: Practical Nonparametric Statistics.Wiley, New York 1999; reference:[4] Critchlow D. E., Fligner M. A.: On distribution-free multiple comparisons in the one-way analysis of variance.Commun. Statist. Theory Meth. 20 (1991), 127–139 MR 1114636, 10.1080/03610929108830487; reference:[5] Goria M. N., Vorlíčková D.: On the asymptotic properties of rank statistics for the two-sample location and scale problem.Aplikace matematiky 30 (1985), 425–434 MR 0813531; reference:[6] Govindajarulu Z., Cam, L. Le, Raghavachari M.: Generalizations of theorems of Chernoff and Savage on the asymptotic normality of test statistics.In: Proc. Fifth Berkeley Symposium on Math. Statist. and Probab., Vol. 1 (1966) (J. Neyman and L. Le Cam, eds.), Univ. of California Press, Berkeley 1967, pp. 609–638 MR 0214193; reference:[7] Hájek J., Šidák Z.: Theory of Rank Tests.Academia, Prague 1967 Zbl 0944.62045, MR 0229351; reference:[8] Harter H. L.: Tables of range and studentized range.Ann. Math. Statist. 31 (1960) 1122–1147 Zbl 0106.13602, MR 0123384, 10.1214/aoms/1177705684; reference:[9] Hayter A. J.: A proof of the conjecture that the Tukey–Kramer multiple comparison procedure is conservative.Ann. Statist. 12 (1984), 61–75 MR 0733499, 10.1214/aos/1176346392; reference:[10] Hollander M., Wolfe D. A.: Nonparametric Statistical Methods.Wiley, New York 1999 Zbl 0997.62511, MR 1666064; reference:[11] Koziol J. A., Reid N.: On the asymptotic equivalence of two ranking methods for $k$-sample linear rank statistics.Ann. Statist. 5 (1977), 1099–1106 Zbl 0391.62053, MR 0518897, 10.1214/aos/1176343998; reference:[12] Kruskal W. H.: A nonparametric test for the several sample problem.Ann. Math. Statist. 23 (1952), 525–540 Zbl 0048.36703, MR 0050850, 10.1214/aoms/1177729332; reference:[13] Kruskal W. H., Wallis W. A.: Use of ranks in one-criterion variance analysis.J. Amer. Statist. Assoc. 47 (1952), 583–621 Zbl 0048.11703, 10.1080/01621459.1952.10483441; reference:[14] Lepage Y.: A combination of Wilcoxon’s and Ansari–Bradley’s statistics.Biometrika 58 (1971), 213–217 Zbl 0218.62039, MR 0408101, 10.1093/biomet/58.1.213; reference:[15] Lepage Y.: A table for a combined Wilcoxon Ansari–Bradley statistic.Biometrika 60 1973), 113–116 Zbl 0256.62041, MR 0331625, 10.1093/biomet/60.1.113; reference:[16] Mann H. B., Whitney D. R.: On a test whether one of two random variables is stochastically larger than the other.Ann. Math. Statist. 18 (1947), 50–60 MR 0022058, 10.1214/aoms/1177730491; reference:[17] Miller R. G., Jr.: Simultaneous Statistical Inference.Second edition. Springer–Verlag, New York – Heidelberg 1985 Zbl 0463.62002, MR 0612319; reference:[18] Puri M. L.: On some tests of homogeneity of variances.Ann. Inst. Stat. Math. 17 (1965), 323–330 Zbl 0161.16202, MR 0196863, 10.1007/BF02868176; reference:[19] Puri M. L., Sen P. K.: Nonparametric Methods in Multivariate Analysis.Wiley, New York 1971 Zbl 0237.62033, MR 0298844; reference:[20] Rao C. R., Mitra S. K.: Generalised Inverse of Matrices and its Applications.Wiley, New York 1971 MR 0338013; reference:[21] Rublík F.: On optimality of the LR tests in the sense of exact slopes.Part II. Application to individual distributions. Kybernetika 25 (1989), 117–135 Zbl 0692.62016, MR 0995954; reference:[22] Rublík F.: Asymptotic distribution of the likelihood ratio test statistic in the multisample case.Math. Slovaca 49 (1999), 577–598 Zbl 0957.62011, MR 1746901; reference:[23] Tsai W. S., Duran B. S., Lewis T. O.: Small-sample behavior of some multisample nonparametric tests for scale.J. Amer. Statist. Assoc. 70 (1975), 791–796 Zbl 0322.62048, 10.1080/01621459.1975.10480304; reference:[24] Wilcoxon F.: Individual comparisons by ranking methods.Biometrics Bull. 1 (1945), 80–83 10.2307/3001968
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19Academic Journal
المؤلفون: Omelka, Marek
مصطلحات موضوعية: keyword:testing statistical hypothesis, keyword:locally most powerful tests, msc:62F03, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2193860; zbl:Zbl 1244.62018; reference:[1] Brown L. D., Marden J. M.: Local admissibility and local unbiasedness in hypothesis testing problems.Ann. Statist. 20 (1992), 832–852 Zbl 0767.62006, MR 1165595, 10.1214/aos/1176348659; reference:[2] Chibisov D. M.: Asymptotic expansions for some asymptotically pptimal tests.In: Proc. Prague Symp. on Asymptotic Statistics, Volume II (J. Hájek, ed.), Charles University, Prague 1973, pp. 37–68 MR 0400501; reference:[3] Efron B.: Defining the curvature of a statistical problem (with application to second order efficiency).Ann. Statist. 3 (1975), 1189–1242 MR 0428531, 10.1214/aos/1176343282; reference:[4] Gupta A. S., Vermeire L.: Locally optimal tests for multiparameter hypotheses.J. Amer. Statist. Assoc. 81 (1986), 819–825 Zbl 0635.62020, MR 0860517, 10.1080/01621459.1986.10478340; reference:[5] Isaacson S. L.: On the theory of unbiased tests of simple statistical hypothesis specifying the values of two or more parameters.Ann. Math. Statist. 22 (1951), 217–234 MR 0041401, 10.1214/aoms/1177729642; reference:[6] Jurečková J.: $L_1$-derivatives, score function and tests.In: Statistical Data Analysis Based on the $L_1$-Norm and Related Methods (Y. Dodge, ed.), Birkhäuser, Basel 2002, pp. 183–189; reference:[7] Kallenberg W. C. M.: The shortcomming of locally most powerful test in curved exponential families.Ann. Statist. 9 (1981), 673–677 MR 0615444, 10.1214/aos/1176345472; reference:[8] Lehmann E. L.: Testing Statistical Hypothesis.Second edition. Chapman & Hall, New York 1994; reference:[9] Littel R. C., Folks J. L.: A test of equality of two normal population means and variances.J. Amer. Statist. Assoc. 71 (1976), 968–971 MR 0420945, 10.1080/01621459.1976.10480978; reference:[10] Peers H. W.: Likelihood ratio and associated test criteria.Biometrika 58 (1971), 577–587 Zbl 0245.62026, 10.1093/biomet/58.3.577; reference:[11] Ramsey F. L.: Small sample power functions for nonparametric tests of location in the double exponential family.J. Amer. Statist. Assoc. 66 (1971), 149–151 Zbl 0215.26402, 10.1080/01621459.1971.10482236; reference:[12] Witting H.: Mathematische Statistik I.Teubner–Verlag, Stuttgart 1985 Zbl 0581.62001, MR 0943833; reference:[13] Wong P. G., Wong S. P.: A curtailed test for the shape parameter of the Weibull distribution.Metrika 29 (1982), 203–209 Zbl 0492.62022, MR 0685566, 10.1007/BF01893380
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20Academic Journal
المؤلفون: Marek, Jaroslav
مصطلحات موضوعية: keyword:two stage regression models, keyword:uncertainty of the type A and B, keyword:BLUE, keyword:$\mathbf{H}$–optimum estimators, msc:62H12, msc:62J05, msc:65C60
وصف الملف: application/pdf
Relation: mr:MR2124609; zbl:Zbl 1060.62062; reference:[1] Kubáček L.: Two stage regression models with constraints.Math. Slovaca 43 (1993), 643–658. MR 1273716; reference:[2] Kubáček L.: Štatistické modely pripojovacích meraní.In. Celoslovenský seminár “Modernizácia geodetických základov Slovenska”, zborník prednášok (ed. M. Petrovič), VÚGK Bratislava, 1993, 28–40.; reference:[3] Kubáček L., Kubáčková L.: Dvouetapové sítě s podmínkami typu I a II.In: Sborník příspěvků spolupracovníků k devadesátinám pana profesora Josefa Vykutila. (Ed. D. Dušátko), Praha–Brno, Vojenský zeměpisný ústav Praha 2002, 58–72.; reference:[4] Kubáčková L.: Foundations of Experimental Data Analysis. : CRC-Press, Boca Raton–Ann Arbor–London–Tokyo., 1992. MR 1244322; reference:[5] Kubáček L., Marek J.: Partial optimum estimator in two stage regression model with constraints and a problem of equivalence.Math. Slovaca 54 (2004), (to appear). Zbl 1107.62051, MR 2181785; reference:[6] Marek J.: Estimation in connecting measurement.Acta Univ. Palacki. Olomuc., Fac. rer. nat., Math. 43 (2003), 69–86. MR 2056023; reference:[7] Marek J.: Statistical view on measurement in Czech and world literature.(submitted to proceedings of Datastat’03).; reference:[8] Kubáček L., Kubáčková L.: Statistics, Metrology (in Czech). Olomouc. : Publishing House of Palacký University., 2000.