يعرض 1 - 20 نتائج من 299 نتيجة بحث عن '"Datos funcionales"', وقت الاستعلام: 0.61s تنقيح النتائج
  1. 1
    Dissertation/ Thesis

    المؤلفون: Bermeo Ayerbe, Miguel Ángel

    Thesis Advisors: Ocampo-Martínez, Carlos, Díaz Rozo, Javier, Institut de Robòtica i Informàtica Industrial

    المصدر: TDX (Tesis Doctorals en Xarxa)

    وصف الملف: application/pdf

  2. 2
    Dissertation/ Thesis

    المؤلفون: Barahona Albiol, Sònia

    المساهمون: University/Department: Universitat Jaume I. Escola de Doctorat

    Thesis Advisors: Simó Vidal, Amelia, Ibáñez Gual, María Victoria

    المصدر: TDX (Tesis Doctorals en Xarxa)

    وصف الملف: application/pdf

  3. 3
    Dissertation/ Thesis

    المؤلفون: Rodríguez Rubio, Pere Ramón

    Thesis Advisors: Bagur Calafat, Caritat, Girabent Farrés, Montserrat, Departament de Fisioteràpia

    المصدر: TDX (Tesis Doctorals en Xarxa)

    وصف الملف: application/pdf

  4. 4
    Academic Journal
  5. 5
    Academic Journal
  6. 6
    Academic Journal
  7. 7
    Academic Journal

    المصدر: TecnoLógicas; Vol. 27 No. 59 (2024); e2986 ; TecnoLógicas; Vol. 27 Núm. 59 (2024); e2986 ; 2256-5337 ; 0123-7799

    وصف الملف: application/pdf; text/xml; application/zip; text/html

    Relation: https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2986/3216; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2986/3299; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2986/3300; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2986/3301; T. Górecki and Ł. Smaga, “A comparison of tests for the one-way ANOVA problem for functional data,” Comput. Stat., vol. 30, no. 4, pp. 987–1010, Dec. 2015. https://doi.org/10.1007/s00180-015-0555-0; J. T. Zhang, Analysis of variance for functional data, 1st ed. New York, NY, USA: Chapman and Hall/CRC, 2013. https://doi.org/10.1201/b15005; F. Ferraty, P. Vieu, and S. Viguier-Pla, “Factor-based comparison of groups of curves,” Comput. Stat. Data Anal., vol. 51, no. 10, pp. 4903–4910, Jun. 2007. https://doi.org/https://doi.org/10.1016/j.csda.2006.10.001; M. L. Bourbonnais et al., “Characterizing spatial-temporal patterns of landscape disturbance and recovery in western Alberta, Canada using a functional data analysis approach and remotely sensed data,” Ecol. Inform., vol. 39, pp. 140–150, May. 2017. https://doi.org/https://doi.org/10.1016/j.ecoinf.2017.04.010; A. Roy, T. Nelson, and P. Turaga, “Functional data analysis approach for mapping change in time series: A case study using bicycle ridership patterns,” Transp. Res. Interdiscip. Perspect., vol. 17, p. 100752, Jan. 2023. https://doi.org/https://doi.org/10.1016/j.trip.2022.100752; J. M. Torres, P. J. G. Nieto, L. Alejano, and A. N. Reyes, “Detection of outliers in gas emissions from urban areas using functional data analysis,” J. Hazard. Mater., vol. 186, no. 1, pp. 144–149, Feb. 2011. https://doi.org/https://doi.org/10.1016/j.jhazmat.2010.10.091; M. Tang, Z. Li, and G. Tian, “A Data-Driven-Based Wavelet Support Vector Approach for Passenger Flow Forecasting of the Metropolitan Hub,” IEEE Access, vol. 7, pp. 7176-7183, Jan. 2019. https://ieeexplore.ieee.org/abstract/document/8600312; Z. Jin-Ting, and X. Liang, “One-way ANOVA for functional data via globalizing the pointwise F-test,” Scand. Stat. Theory Appl., vol. 41, no. 1, pp. 51–71, Mar. 2014. https://doi.org/10.1111/sjos.12025; A. Cuevas, M. Febrero, and R. Fraiman, “An anova test for functional data,” Comput. Stat. Data Anal., vol. 47, no. 1, pp. 111–122, Aug. 2004. https://doi.org/https://doi.org/10.1016/j.csda.2003.10.021; J. O. Ramsay, and B. W. Silverman, Functional Data Analysis, 2nd ed. New York, NY, USA: Springer-Verlag New York, 2005. https://doi.org/10.1007/b98888; C. G. Kaufman, and S. R. Sain, “Bayesian Functional ANOVA Modeling Using Gaussian Process Prior Distributions,” Bayesian Anal., vol. 5 no. 1, pp. 123–149, Mar. 2010. https://doi.org/10.1214/10-BA505; Q. Shen, and J. J. Faraway, “An F test for linear models with functional responses,” Statistica Sinica, vol. 14, pp. 1239–1257, 2004. https://api.semanticscholar.org/CorpusID:55106079; P. Delicado, “Functional k-sample problem when data are density functions,” Comput. Stat., vol. 22, no. 3, pp. 391–410, Sep. 2007. https://doi.org/10.1007/s00180-007-0047-y; M. Myllymäki, T. Mrkvička, P. Grabarnik, H. Seijo, and U. Hahn, “Global envelope tests for spatial processes,” J. R. Stat. Soc. Series B Stat. Methodol., vol. 79, no. 2, pp. 381–404, Mar. 2017. https://doi.org/10.1111/rssb.12172; O. A. Vsevolozhskaya, M. C. Greenwood, and D. B. Holodov, “Pairwise comparison of treatment levels in functional analysis of variance with application to erythrocyte hemolysis,” Ann. Appl. Stat., vol. 8, pp. 905–925, Jun. 2014. https://api.semanticscholar.org/CorpusID:38476665; A. Pini, S. Vantini, B. M. Colosimo, and M. Grasso, “Domain-selective functional analysis of variance for supervised statistical profile monitoring of signal data,” J. R. Stat. Soc. Ser. C Appl. Stat., vol. 67, no. 1, pp. 55–81, Jan. 2018. https://doi.org/10.1111/rssc.12218; A. B. Kashlak, S. Myroshnychenko, and S. Spektor, “Analytic Permutation Testing for Functional Data ANOVA,” J. Comput. Graph. Stat., vol. 32, no. 1, pp. 294–303, May. 2023. https://doi.org/10.1080/10618600.2022.2069780; M. Hollander, D. A. Wolfe, and E. Chicken, “The onw-Way Layout Introduction,” in Nonparametric Statistical Methods, D. J. Balding et al., Eds., Hoboken, New Jersey: John Wiley & Sons, 2013. https://books.google.es/books?hl=es&lr=&id=Y5s3AgAAQBAJ&oi=fnd&pg=PP10&dq=E.+Hollander,+M.,+Wolfe,+d.+and+Chicken,+Nonparametric+statistical+methods,+John+Wiley.+Londres,+2013.&ots=a-h-k6diyR&sig=I_655cMRqPSiDdGABrn8nLSOa98; D. Achlioptas, “Database-friendly random projections,” in Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, New York, NY, USA, 2001. https://api.semanticscholar.org/CorpusID:2640788; A. Nieto-Reyes, “Random Projections: Applications to Statistical Data Depth and Goodness of Fit Test,” BEIO Rev. Of. la Soc. Estadística e Investig. Oper., vol. 35, no. 1, pp. 7–22, Mar. 2019. https://www.seio.es/beio/BEIOVol35Num1.pdf#page=13; J. A. Cuesta-Albertos, R. Fraiman, and T. Ransford, “Random projections and goodness-of-fit tests in infinite-dimensional spaces,” Bull. Brazilian Math. Soc., vol. 37, no. 4, pp. 477–501, Dec. 2006. https://doi.org/10.1007/s00574-006-0023-0; R. Ihaka, R. Gentleman. The R Project for Statistical Computing. (V R.4.2.1 2022). Accessed: Apr. 16, 2023. [Online]. Available: https://cran.r-project.org/bin/windows/base/old/4.2.1/; J. Ramsay, G. Hooker, and S. Graves, Functional Data Analysis with R and MATLAB. New York, NY, USA: Springer New York, 2009. https://doi.org/10.1007/978-0-387-98185-7; T. Pohlert, The Pairwise Multiple Comparison of Mean Ranks Package (PMCMR) v4.4. 2016. Accessed: Apr.16, 2023. [Online]. Available: http://cran.r-project.org/package=PMCMR; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2986

  8. 8
    Academic Journal

    المؤلفون: Andreozzi, Lucia, Ribotta, Bruno

    المصدر: Astrolabio; No. 31 (2023): Neoliberal post-feminism and feminist activisms in the current capitalist and pandemic conjuncture; 254-279 ; Astrolabio; Núm. 31 (2023): Julio - Diciembre: El posfeminismo neoliberal y los activismos feministas en la coyuntura capitalista y pandémica actual; 254-279 ; Astrolabio; n. 31 (2023): Pós-feminismo neoliberal e ativismos feministas na atual conjuntura capitalista e pandêmica; 254-279 ; 1668-7515 ; 10.55441/1668.7515.n31

    وصف الملف: application/pdf; text/html

  9. 9
    Book

    المؤلفون: MELENDEZ SURMAY, RAFAEL

    وصف الملف: 95 páginas; application/pdf

    Relation: Cuevas, A., Febrero, M. and Fraiman, R. (2006) On the use of the bootstrap for estimating functions with functional data. Computational Statistics and Data Analysis, In press.; Cuevas, A., Febrero, M., Fraiman, R., (2004), An ANOVA test for functional data. Computational Statistics and Data Analysis 47, 111–122.; Cattell, R. B. (1999). The scree test for the number of factors. Journal of Multivariate Behavioral Research, 1, 245-276.; Cox, D.D., Lee, J.S., 2008. Pointwise testing with functional data using the Westfall–Young randomization method. Biometrika 95 (3), 621–634.; Croux, C. & Ruiz-Gazen, A. (2005), `High breakdown estimators for principal components: the projection-pursuit approach revisited', Journal of Multivariate Analysis 95(1), 206-226. http://ideas.repec.org/a/eee/jmvana/v95y2005i1p206-226.html; Febrero, M., Galeano, P. & Gonzalez-Manteiga, W. (2007), A functional analysis of NOx levels: location and scale estimation and outlier detection', Computational Statistics 22(3), 411- 427.http://www.springerlink.com/content/146v81216v078582; Febrero, M., Galeano, P. & Gonzalez-Manteiga, W. (2008), “Outlier detection in functional data by depth measures, with application to identify abnormal NOx levels”, Environmetrics 19(4), 331-341.; Ferraty, F. and P. Vieu (2001). The functional nonparametric model and its applications to spectometric data. Computational Statistics 17, 545–564.; Ferraty, F. and Vieu, P. (2006) Nonparametric Functional Data Analysis: methods, theory, applications and implementations. Springer-Verlag, London.; Fraiman, R. and Muniz, G. (2001) Trimmed means for functional data. Test, 10, 419-440.; Gorecki, T., y Smaga,L.,(2015) Comparison of tests for the one-way anova problem for functional data, Comput. Stat. 30 (4), 987–1010.; Gorecki, T. y Smaga, L.,(2015), Comparison of tests for the one-way anova problem for functional data, Comput. Stat. 30 (4) 987–1010.; Horváth, L. and Kokoszka, P. (2012). Inference for Functional Data with Applications. Springer.; Hyndman, R. J. (1996), `Computing and graphing highest density regions', The American Statistician 50(2), 120-126.http://www.jstor.org/stable/2684423; Hyndman, R. J. & Ullah, M. S. (2007), `Robust forecasting of mortality and fertility rates: A functional data approach', Computational Statistics & Data Analysis 51(10), 4942-4956. http://ideas.repec.org/a/eee/csdana/v51y2007i10p4942-4956.html; Hyndman, R. J. (1996), `Computing and graphing highest density regions', The American Statistician 50(2), 120-126. http://www.jstor.org/stable/2684423; Hyndman, R. J. & Ullah, M. S. (2007), `Robust forecasting of mortality and fertility rates: A functional data approach', Computational Statistics & Data Analysis 51(10), 4942-4956. http://ideas.repec.org/a/eee/csdana/v51y2007i10p4942-956.html; Hsing, T. and Eubank, R. (2015). Theoretical foundations of functional data analysis, with an introduction to linear operators, volume 997. John Wiley & Sons.; Jones, M. C. & Rice, J. A. (1992), `Displaying the important features of large collections of similar curves', The American Statistician 46(2), 140-145 http://www.jstor.org/stable/2684184; Jones, M. C. & Rice, J. A. (1992), `Displaying the important features of large collections of similar curves', The American Statistician 46(2), 140-145.; Ramsay, J.O., Heckman, N. & Silverman, B.W. Spline smoothing with modelbased penalties. Behavior Research Methods, Instruments, & Computers 29, 99– 106 (1997). https://doi.org/10.3758/BF03200573; Ramsay, J. O. and Silverman, B. W. (2005), Functional Data Analysis. Springer- Verlag, New York.; Ramsay, J., Hooker, G., and Graves, S. (2009), Functional Data Analysis with R and MATLABR_. Springer, London.; Ramsay, J. O. and B. W. Silverman (2005). Functional Data Analysis, Second Edition. New York: Springer.; Ramsay, J., y Silverman, B., (1997), Functional Data Analysis. Springer.; R Core Team, (2016), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.; Rice, J. & Silverman, B. (1991). Estimating the mean and covariance structure nonparametrically when the data are curves, Journal of the Royal, Statistical Society. Series B (Methodological), 53, 233-243.; Rousseeuw, P., Ruts, I. & Tukey, J. W. (1999), `The bagplot: A bivariate boxplot', The American Statistician 53(4), 382-387.; Scott, D. W. (1992), Multivariate density estimation: theory, practice, and visualization, Wiley, New York. http://www.wiley.com/WileyCDA/WileyTitle/productCd- 0471547700.html; Sara López-Pintado & Juan Romo (2009) On the Concept of Depth for Functional Data, Journal of the American Statistical Association, 104:486, 718-734,DOI:10.1198/jasa.2009.0108; Shen, Q., Faraway, J., (2004), An F test for linear models with functional responses. Statistica Sinica 14, 1239–1257.; Sood, A., James, G. M. & Tellis, G. J. (2009), `Functional regression: a new model for predicting market penetration of new products', Marketing Science 28(1), 36-51. http://mktsci.journal.informs.org/cgi/content/abstract/mksc.1080.0382v1; Tukey, J. W. (1975) Mathematics and the picturing of data. Proceedings of the International Congress of Mathematicians (R. D. James, Ed.), Vol. 2, pp. 523- 531, Vancouver, 1975.; Vsevolozhskaya, O. A., Greenwood, M. C., Bellante, G. J., Powell, S. L., Lawrence, R. L. and Repasky, K. S. (2013). Combining functions and the closure principle for performing follow-up tests in functional analysis of variance. Comput. Statist. Data Anal. 67 175–184.; Vsevolozhskaya, O.A, et al (2013), Combining functions and the closure principle for performing follow-up tests in functional analysis of variance, Computational Statistics & Data Analysis Volume 67, November 2013, Pages 175-184.; Wahba, G., (1990), Spline Models for Observational Data. CBMS-NSF Regional Conference Series in Applied Mathematics. SIAM, Philadelphia.; Zhang, C., Peng, H., and Zhang, J.-T.(2010), Two sample tests for functional data. Communications in Statistics–Theory and Methods, 39(4):559–578.; Zhang, J.-T. (2011), Statistical inferences for linear models with functional responses. Statistica Sinica, 21:1431–1451.; Zhang, J. T., & Chen, J. (2007). Statistical inferences for functional data. The Annals of Statistics, 35(3), 1052-1079.; Zhang, J., (2014), Analysis of Variance for Functional Data, CRC Press.; https://repositoryinst.uniguajira.edu.co/handle/uniguajira/1451

  10. 10
    Academic Journal
  11. 11
    Academic Journal
  12. 12
    Academic Journal
  13. 13
    Book
  14. 14
    Dissertation/ Thesis

    Thesis Advisors: Berrendero Díaz, José Ramón (tutor), Suárez, Alberto (tutor), UAM. Departamento de Ingeniería Informática

  15. 15
    Dissertation/ Thesis
  16. 16
    Dissertation/ Thesis
  17. 17
    Dissertation/ Thesis
  18. 18
    Dissertation/ Thesis
  19. 19
    Dissertation/ Thesis
  20. 20
    Academic Journal