المؤلفون: Montoya, José A.

المصدر: Revista de la Facultad de Ciencias; Vol. 11 No. 2 (2022): Special Issue: Flat Likelihoods; 8-24 ; Revista de la Facultad de Ciencias; Vol. 11 Núm. 2 (2022): Número Especial: Verosimilitudes Planas; 8-24 ; 2357-5549 ; 0121-747X

مصطلحات موضوعية: Verosimilitud plana, parámetro umbral, modelo empotrado, distribución Poisson, contornos de verosimilitud, verosimilitud perfil, función de verosimilitud perfil, Flat likelihood, threshold parameter, embedded models, Poisson distribution, likelihood contours, profile likelihood function

وصف الملف: application/pdf

Relation: https://revistas.unal.edu.co/index.php/rfc/article/view/97888/85205; Aitkin, M. & Stasinopoulos, M. (1989). Likelihood analysis of a binomial sample size problem. Contributions to Probability and Statistics (pp. 399-411). Springer. New York.; Barndorff-Nielsen, O. E. & Cox, D. R. (1994). Inference and asymptotics. Chapman & Hall/CRC. Boca Raton.; Berger, J. O., Liseo, B. & Wolpert, R. L. (1999). Integrated likelihood methods for eliminating nuisance parameters. Statistical Science, 14(1), 1-28.; Breusch, T. S., Robertson, J. C. & Welsh, A. H. (1997). The emperor's new clothes: a critique of the multivariate t regression model. Statistica Neerlandica, 51(3), 269-286.; Carroll, R. J. & Lombard, F. (1985). A note on N estimators for the binomial distribution. Journal of the American Statistical Association, 80(390), 423-426.; Casella, G. (1986). Stabilizing binomial n estimators. Journal of the American Statistical Association, 81(393), 172-175.; Catchpole, E. A.& Morgan, B. J. (1997). Detecting parameter redundancy. Biometrika, 84(1), 187-196.; Cheng, R. C. H. & Iles, T. C. (1990). Embedded models in three-parameter distributions and their estimation. Journal of the Royal Statistical Society. Series B (Methodological), 52(1), 135-149.; Cole, S. R., Chu, H. & Greenland, S. (2013). Maximum likelihood, profile likelihood, and penalized likelihood: a primer. American Journal of Epidemiology, 179(2), 252-260.; DasGupta, A. & Rubin, H. (2005). Estimation of binomial parameters when both n, p are unknown. Journal of Statistical Planning and Inference, 130(1-2), 391-404.; Draper, N.; Guttman, I. (1971), Bayesian estimation of the binomial parameter. Technometrics, 13(3), 667-673.; El Adlouni, S., Ouarda, T. B., Zhang, X., Roy, R. & Bobée, B. (2007). Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resources Research, 43(3), W03410.; Farcomeni, A. & Tardella, L. (2012). Identifiability and inferential issues in capture-recapture experiments with heterogeneous detection probabilities. Electronic Journal of Statistics, 6, 2602-2626.; Fisher, R. A. (1941). The negative binomial distribution. Annals of Eugenics, 11(1), 182-187.; Frery, A. C., Cribari-Neto, F.& De Souza, M. O. (2004). Analysis of minute features in speckled imagery with maximum likelihood estimation. EURASIP Journal on Advances in Signal Processing, 2004(16), 2476-2491.; Ghosh, M., Datta, G. S., Kim, D. & Sweeting, T. J. (2006). Likelihood-based inference for the ratios of regression coeficients in linear models. Annals of the Institute of Statistical Mathematics, 58(3), 457-473.; Gupta, A. K., Nguyen, T. T. &Wang, Y. (1999). On maximum likelihood estimation of the binomial parameter n. Canadian Journal of Statistics, 27(3), 599-606.; Hall, P. (1994). On the erratic behavior of estimators of N in the binomial N, p distribution. Journal of the American Statistical Association, 89(425), 344-352.; Harter, H. L. & Moore, A. H. (1966). Local-maximum-likelihood estimation of the parameters of three-parameter lognormal populations from complete and censored samples. Journal of the American Statistical Association, 61(315), 842-851.; Kahn, W. D. (1987). A cautionary note for Bayesian estimation of the binomial parameter n. The American Statistician, 41(1), 38-40.; Kalbfleisch, J. G. (1985). Probability and Statistical Inference, Vol. 2. Springer-Verlag. New York.; Kreutz, C., Raue, A., Kaschek, D. & Timmer, J. (2013). Prole likelihood in systems biology. The FEBS Journal, 280(11), 2564-2571.; Li, R. & Sudjianto, A. (2005). Analysis of computer experiments using penalized likelihood in Gaussian Kriging models. Technometrics, 47(2), 111-120.; Lima, V. M. & Cribari-Neto, F. (2019). Penalized maximum likelihood estimation in the modified extended Weibull distribution. Communications in Statistics-Simulation and Computation, 48(2), 334-349.; Lindsey, J. K. (1996). Parametric statistical inference. Oxford University Press. New York.; Liu, S., Wu, H. & Meeker, W. Q. (2015). Understanding and addressing the unbounded likelihood problem. The American Statistician, 69(3), 191-200.; Martins, E. S. & Stedinger, J. R. (2000). Generalized maximum-likelihood generalized extreme value quantile estimators for hydrologic data. Water Resources Research, 36(3), 737-744.; Martins, E. S. & Stedinger, J. R. (2001). Generalized maximum likelihood Pareto-Poisson estimators for partial duration series. Water Resources Research, 37(10), 2551-2557.; Montoya, J. A., Díaz-Francés, E. & Sprott, D. A. (2009). On a criticism of the progile likelihood function. Statistical Papers, 50(1), 195-202.; Moran, P. A. P. (1951). A mathematical theory of animal trapping. Biometrika, 38(3-4), 307-311.; Murphy, S. A. & Van Der Vaart, A. W. (2000). On profile likelihood. Journal of the American Statistical Association, 95(450), 449-465.; Olkin, I., Petkau, A. J. & Zidek, J. V. (1981). A comparison of n estimators for the binomial distribution. Journal of the American Statistical Association, 76(375), 637-642.; Pawitan, Y. (2001). In All Likelihood: Statistical Modelling and Inference Using Likelihood. Oxford University Press. New York.; Pewsey, A. (2000). Problems of inference for Azzalini's skewnormal distribution. Journal of Applied Statistics, 27(7), 859-870.; Raftery, A. E. (1988). Inference for the binomial N parameter: A hierarchical Bayes approach. Biometrika, 75(2), 223-228.; Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U. & Timmer, J. (2009). Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15), 1923-1929.; Serfling, R. J. (2002). Approximation Theorems of Mathematical Statistics. John Wiley & Sons. New York.; Sprott, D. A. (2000). Statistical inference in science. Springer-Verlag. New York.; Sundberg, R. (2010). Flat and multimodal likelihoods and model lack of fit in curved exponential families. Scandinavian Journal of Statistics, 37(4), 632-643.; Tsionas, E. G. (2001). Likelihood and Posterior Shapes in Johnson's System. Sankhya: The Indian Journal of Statistics, Series B, 63(1), 3-9.; Tumlinson, S. E. (2015). On the non-existence of maximum likelihood estimates for the extended exponential power distribution and its generalizations. Statistics & Probability Letters, 107, 111-114; https://revistas.unal.edu.co/index.php/rfc/article/view/97888

الاتاحة: https://revistas.unal.edu.co/index.php/rfc/article/view/97888

المؤلفون: Montoya, José A., Figueroa-Preciado, Gudelia, Tocto-Erazo , Mayra Rosalia

المصدر: Revista de la Facultad de Ciencias; Vol. 11 No. 2 (2022): Special Issue: Flat Likelihoods; 74-99 ; Revista de la Facultad de Ciencias; Vol. 11 Núm. 2 (2022): Número Especial: Verosimilitudes Planas; 74-99 ; 2357-5549 ; 0121-747X

مصطلحات موضوعية: Función de verosimilitud plana, modelo EDO, modelo SIR, número reproductivo básico, contornos de verosimilitud, función de verosimilitud perfil, Flat likelihood function, ODE model, SIR model, basic reproductive number, likelihood contours, profile likelihood function

وصف الملف: application/pdf

Relation: https://revistas.unal.edu.co/index.php/rfc/article/view/100986/84230; Acuña-Zegarra, M. A., Díaz-Infante, S., Baca-Carrasco, D., Olmos-Liceaga, D. (2021). COVID-19 optimal vaccination policies: a modeling study on efficacy, natural and vaccine-induced immunity responses. Mathematical Biosciences, 6337, 108614.; Acuña-Zegarra, M. A., Santana-Cibrian, M. \& Velasco-Hernández, J. X. (2020). Modeling behavioral change and COVID-19 containment in Mexico: A trade-off between lockdown and compliance. Mathematical Biosciences, 325, 108370.; Arino, J. & Van den Driessche, P. (2003). A multi-city epidemic model. Mathematical Population Studies, 10(3), 175-193.; Barndorff-Nielsen, O.E. & Cox, D.R. (1994). Inference and asymptotics. Chapman & Hall/CRC. Boca Raton.; Camacho, A., Kucharski, A. J., Funk, S., Breman, J., Piot, P. & Edmunds, W. J. (2014). Potential for large outbreaks of Ebola virus disease. Epidemics, 9, 70-78.; Capistrán, M.A., Christen, J. A. & Velasco-Hernández, J. X. (2012). Towards uncertainty quantification and inference in the stochastic SIR epidemic model. \textit{Mathematical Biosciences}, 240(2), 250-259.; Chowell, G., Diaz-Dueñas, P., Miller, J. C., Alcazar-Velazco, A., Hyman, J. M., Fenimore, P. W. & Castillo-Chavez, C. (2007). Estimation of the reproduction number of dengue fever from spatial epidemic data. Mathematical Biosciences, 208(2), 571-589.; Chowell, G., Torre, C. A., Munayco-Escate, C., Suarez-Ognio, L., Lopez-Cruz, R., Hyman, J. M. & Castillo-Chavez, C. (2008). Spatial and temporal dynamics of dengue fever in Peru: 1994--2006. Epidemiology & Infection, 136(12), 1667-1677.; Chowell, G., Towers, S., Viboud, C., Fuentes, R., Sotomayor, V., Simonsen, L.,Miller, M. A., Lima, M., Villarroel, C., Chiu, M., Villarroel, J. E. & Olea, A. (2012). The influence of climatic conditions on the transmission dynamics of the 2009 A/H1N1 influenza pandemic in Chile. BMC Infectious Diseases, 12(1), 1-12.; Cole, D. J. (2020). Parameter redundancy and identifiability. Chapman & Hall/CRC. Boca Raton.; Cosner, C. (2015). Models for the effects of host movement in vector-borne disease systems. Mathematical Biosciences, 270, 192-197.; Funk, S., Kucharski, A. J., Camacho, A., Eggo, R. M., Yakob, L., Murray, L. M. & Edmunds, W. J. (2016). Comparative Analysis of Dengue and Zika Outbreaks Reveals Differences by Setting and Virus. PLoS Neglected Tropical Diseases, 10(12), e0005173.; Gábor, A., Villaverde, A. F. & Banga, J. R. (2017). Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems. BMC Systems Biology, 11(1), 1-16.; Ghosh, I., Sardar, T. & Chattopadhyay, J. (2017). A Mathematical Study to Control Visceral Leishmaniasis: An Application to South Sudan. Bulletin of Mathematical Biology, 79(5), 1100-1134.; Ghosh, I., Tiwari, P. K., Samanta, S., Elmojtaba, I. M., Al-Salti, N. & Chattopadhyay, J. (2018). A simple SI-type model for HIV/AIDS with media and self-imposed psychological fear. Mathematical Biosciences, 306, 160-169.; Guanghu, Z., Tao, L., Jianpeng, X., Bing, Z., Tie, S., Yonghui, Z., Lifeng, L., Zhiqiang, P., Aiping, D., Wenjun, M. & Yuantao, H. (2019). Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue. Science of The Total Environment, 651, 969-978.; Gui-Quan, S., Jun-Hui, X., Sheng-He, H., Zhen, J,; Ming-Tao, L. & Liqun, L. (2017). Transmission dynamics of cholera: Mathematical modeling and control strategies. Communications in Nonlinear Science and Numerical Simulation, 45, 235-244.; Hendron, R. W. S. & Bonsall, M. B. (2016). The interplay of vaccination and vector control on small dengue networks. Journal of Theoretical Biology, 407, 349-361.; Kalbfleisch, J. G. (1985). Probability and Statistical Inference, Vol. 2. Springer-Verlag. New York.; Kao, Y. H. & Eisenberg, M. C. (2018). Practical unidentifiability of a simple vector-borne disease model: Implications for parameter estimation and intervention assessment. Epidemics, 25, 89-100.; Kermack, W. O. & McKendrick, A. G. (1927). Contribution to the mathematical theory of epidemics. Proccedings of the Royal Society A, 115(772), 700--721.; Khan, A., Hassan, M. & Imran, M. (2014). Estimating the basic reproduction number for single-strain dengue fever epidemics. Infectious Diseases of Poverty, 3(1), 1-17.; Kim, J. E., Lee, H., Lee, C. H. & Lee, S. (2017). Assessment of optimal strategies in a two-patch dengue transmission model with seasonality. PLoS ONE, 12(3), e0173673.; Lee, S. & Castillo-Chavez, C. (2015). The role of residence times in two-patch dengue transmission dynamics and optimal strategies. Journal of Theoretical Biology, 374, 152-164.; Lloyd-Smith, J. O. (2007). Maximum likelihood estimation of the negative binomial dispersion parameter for highly overdispersed data, with applications to infectious diseases. PLoS ONE, 2(2), e180.; Ma, J. (2020). Estimating epidemic exponential growth rate and basic reproduction number. Infectious Disease Modelling, 5, 129-141.; Marquis, A.D., Arnold, A., Dean-Bernhoft, C., Carlson, B.E. & Olufsen, M. S. (2018). Practical identifiability and uncertainty quantification of a pulsatile cardiovascular model. Mathematical Biosciences, 304, 9-24.; Mishra, A., Ambrosio, B., Gakkhar, S. & Aziz-Alaoui, M. A. (2018). A network model for control of dengue epidemic using sterile insect technique. Mathematical Biosciences & Engineering, 15(2), 441-460.; Mishra, A. & Gakkhar, S. (2018). Non-linear dynamics of two-patch model incorporating secondary dengue infection. International Journal of Applied and Computational Mathematics, 4(19), 1-22.; Murphy, S. A. & Van Der Vaart, A. W. (2000). On profile likelihood. Journal of the American Statistical Association, 95(450), 449-465.; Nguyen, V. K., Parra-Rojas, C. & Hernandez-Vargas, E. A. (2018). The 2017 plague outbreak in Madagascar: Data descriptions and epidemic modelling. Epidemics, 25, 20-25.; Núñez-López, M., Ramos, L. A. & Velasco-Hernández, J. X. (2021). Migration rate estimation in an epidemic network. Applied Mathematical Modelling, 89, 1949-1964.; Pandey, A., Mubayi, A. & Medlock, J. (2013). Comparing vector-host and SIR models for dengue transmission. Mathematical Biosciences, 246(2), 252-259.; Pawitan, Y. (2001). In All Likelihood: Statistical Modelling and Inference Using Likelihood. Oxford University Press. New York.; Phaijoo, G. R. & Gurung, D. B. (2016). Mathematical study of dengue disease transmission in multi-patch environment. Applied Mathematics, 7(14), 1521-1533.; Qi, L., Xue, M., Cui, J.A., Wang, Q. & Wang, T. (2018). Schistosomiasis transmission model and its control in Anhui province. Bulletin of Mathematical Biology, 80(9), 2435-2451.; Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U. & Timmer, J. (2009). Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15), 1923-1929.; Rosenbaum, E. A., Pechen De D'angelo, A. M., Bergoc, R. M. & Venturino, A. (1999). Modelling acetylcholinesterase kinetics: The identifiability problem in parameter estimation. Journal of Biological Systems, 7(01), 95-111.; Saccomani, M. P. & Thomaseth, K. (2018). The union between structural and practical identifiability makes strength in reducing oncological model complexity: a case study. Complexity, 2018.; Saldaña, F., Flores-Arguedas, H., Camacho-Gutiérrez, J. A. & Barradas, I. (2020). Modeling the transmission dynamics and the impact of the control interventions for the COVID-19 epidemic outbreak. Mathematical Biosciences and Engineering, 17(4), 4165-4183.; Sasmal, S. K., Ghosh, I., Huppert, A. & Chattopadhyay, J. (2018). Modeling the spread of Zika virus in a stage-structured population: effect of sexual transmission. Bulletin of Mathematical Biology, 80(11), 3038-3067.; Serfling, R. J. (2002). Approximation Theorems of Mathematical Statistics. John Wiley & Sons. New York.; Sprott, D. A. (2000), Statistical inference in science. Springer-Verlag. New York.; Tocto-Erazo, M. R., Espíndola-Zepeda, J. A., Montoya-Laos, J. A., Acuña-Zegarra, M. A., Olmos-Liceaga, D., Reyes-Castro, P. A. & Figueroa-Preciado, G. (2020), Lockdown, relaxation, and acme period in COVID-19: A study of disease dynamics in Hermosillo, Sonora, Mexico. PLoS ONE, 15(12), e0242957.; Tocto-Erazo, M. R., Olmos-Liceaga, D. & Montoya, J. A. (2021). Effect of daily periodic human movement on dengue dynamics: The case of the 2010 outbreak in Hermosillo, Mexico. Applied Mathematical Modelling, 97, 559-567.; Towers, S., Brauer, F., Castillo-Chavez, C., Falconar, A.K., Mubayi, A. & Romero-Vivas, C. M. (2016). Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission. Epidemics, 17, 50-55.; Tuncer, N., Gulbudak, H., Cannataro, V. L. & Martcheva, M. (2016). Structural and practical identifiability issues of immuno-epidemiological vector-host models with application to rift valley fever. \textit{Bulletin of Mathematical Biology, 78(9), 1796-1827.; Tuncer, N., Mohanakumar, C., Swanson, S. & Martcheva, M. (2018). Efficacy of control measures in the control of Ebola, Liberia 2014-2015. Journal of Biological Dynamics, 12(1), 913-937.; Vinh, D. N., Ha, D.T.M., Hanh, N.T., Thwaites, G., Boni, M. F., Clapham, H. E. & Thuong, N. T. T. (2018). Modeling tuberculosis dynamics with the presence of hyper-susceptible individuals for Ho Chi Minh City from 1996 to 2015. BMC Infectious Diseases, 18(1), 1-13.; Xiao, Y. & Zou, X. (2014). Transmission dynamics for vector-borne diseases in a patchy environment. Journal of Mathematical Biology, 69(1), 113-146.; Zhan, C., Li, B.Y.S. & Yeung, L.F. (2015). Structural and practical identifiability analysis of S-system. IET Systems Biology, 9(6), 285-293.; https://revistas.unal.edu.co/index.php/rfc/article/view/100986

الاتاحة: https://revistas.unal.edu.co/index.php/rfc/article/view/100986

المؤلفون: Espindola Zepeda, Jorge, Montoya, José A.

المصدر: Revista de la Facultad de Ciencias; Vol. 11 No. 2 (2022): Special Issue: Flat Likelihoods; 25-38 ; Revista de la Facultad de Ciencias; Vol. 11 Núm. 2 (2022): Número Especial: Verosimilitudes Planas; 25-38 ; 2357-5549 ; 0121-747X

مصطلحات موضوعية: Shape of the likelihood function, nested models, linear regression model, profile likelihood function, Forma de la función de verosimilitud, modelos anidados, modelo de regresión lineal, función de verosimilitud perfil

وصف الملف: application/pdf

Relation: https://revistas.unal.edu.co/index.php/rfc/article/view/97782/85207; Berger, J. O., Liseo, B. & Wolpert, R. L. (1999). Integrated likelihood methods for eliminating nuisance parameters. Statistical Science, 14(1), 1-22.; Breusch, T. S., Robertson, J. C. & Welsh, A. H. (1997). The emperor's new clothes: a critique of the multivariate t regression model. Statistica Neerlandica, 51(3), 269-286.; Casella, G. & Berger, R. L. (2002). Statistical inference. Duxbury. Pacific Grove, CA.; Casella, G., Berger, R. L. & Santana, D. (2001). Solutions Manual for Statistical Inference.; Catchpole, E. A. & Morgan, B. J. (1997). Detecting parameter redundancy. Biometrika, 84(1), 187-196.; Cheng, R. C. H. & Iles, T. C. (1990). Embedded models in three-parameter distributions and their estimation. Journal of the Royal Statistical Society. Series B (Methodological), 52(1), 135-149.; Cole, S. R., Chu, H. & Greenland, S. (2013). Maximum likelihood, profile likelihood, and penalized likelihood: a primer. American Journal of Epidemiology, 179(2), 252-260.; Cox, D. R. (2006). Principles of statistical inference. Cambridge university Press. Cambridge.; El Adlouni, S., Ouarda, T. B., Zhang, X., Roy, R. & Bobée, B. (2007). Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resources Research, 43 (3), W03410.; Farcomeni, A.& Tardella, L. (2012). Identifiability and inferential issues in capture-recapture experiments with heterogeneous detection probabilities. Electronic Journal of Statistics, 6, 2602-2626.; Fay, M. P., Noubary, F. & Saul, A. (2009). Robust Noninferiority Tests for Potency of a Test Drug Against a Reference Drug. Statistics in Biopharmaceutical Research, 1(3), 291-300.; Frery, A. C., Cribari-Neto, F. & De Souza, M. O. (2004). Analysis of minute features in speckled imagery with maximum likelihood estimation. EURASIP Journal on Advances in Signal Processing, 2004(16), 2476-2491.; Ghosh, M., Datta, G. S., Kim, D. & Sweeting, T. J. (2006). Likelihood-based inference for the ratios of regression coeficients in linear models. Annals of the Institute of Statistical Mathematics, 58(3), 457-473.; Ghosh, M., Yin, M. & Kim, Y. H. (2003). Objective Bayesian inference for ratios of regression coeficients in linear models. Statistica Sinica, 13(2), 409-422.; Harter, H. L. & Moore, A. H. (1966). Local-maximum-likelihood estimation of the parameters of three-parameter lognormal populations from complete and censored samples. Journal of the American Statistical Association, 61(315), 842-851.; Hirschberg, J. & Lye, J. (2010). A reinterpretation of interactions in regressions. Applied Economics Letters, 17(5), 427-430.; Kalbfleisch, J. G. (1985). Probability and Statistical Inference, Vol. 2. Springer-Verlag. New York.; Kreutz, C., Raue, A., Kaschek, D.& Timmer, J. (2013). Profile likelihood in systems biology. The FEBS journal, 280(11), 2564-2571.; Li, R. & Sudjianto, A. (2005). Analysis of computer experiments using penalized likelihood in Gaussian Kriging models. Technometrics, 47(2), 111-120.; Lima, V. M. & Cribari-Neto, F. (2019). Penalized maximum likelihood estimation in the modified extended Weibull distribution. Communications in Statistics-Simulation and Computation, 48(2), 334-349.; Liu, S., Wu, H. & Meeker, W. Q. (2015). Understanding and addressing the unbounded "likelihood" problem. The American Statistician, 69(3), 191-200.; Martins, E. S. & Stedinger, J. R. (2000). Generalized maximum-likelihood generalized extreme value quantile estimators for hydrologic data. Water Resources Research, 36(3), 737-744.; Martins, E. S. & Stedinger, J. R. (2001). Generalized maximum likelihood Pareto-Poisson estimators for partial duration series. Water Resources Research, 37(10), 2551-2557.; Montoya, J. A., Díaz-Francés, E.& Sprott, D. A. (2009). On a criticism of the profile likelihood function. Statistical Papers, 50(1), 195-202.; Pewsey, A. (2000). Problems of inference for Azzalini's skewnormal distribution. Journal of Applied Statistics, 27(7), 859-870.; Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U. & Timmer, J. (2009). Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15), 1923-1929.; Rawlings, J. O., Pantula, S. G. & Dickey, D. A. (1998). Applied regression analysis: a research tool. Springer-Verlag. New York.; Rosenblad, A. K. (2020). The mean, variance, and bias of the OLS based estimator of the extremum of a quadratic regression model for small samples. Communications in Statistics-Theory and Methods, 51(9), 2870-2886.; Searle, S. R. & Gruber, M. H. (1971). Linear models. John Wiley & Sons. New York.; Sprott, D. A. (2008). Statistical inference in science. Springer-Verlag. New York.; Sundberg, R. (2010). Flat and multimodal likelihoods and model lack of fit in curved exponential families. Scandinavian Journal of Statistics, 37(4), 632-643.; Tsionas, E. G. (2001). Likelihood and Posterior Shapes in Johnson's System. Sankhya: The Indian Journal of Statistics, Series B, 63(1), 3-9.; Tumlinson, S. E. (2015). On the non-existence of maximum likelihood estimates for the extended exponential power distribution and its generalizations. Statistics & Probability Letters, 107, 111-114.; https://revistas.unal.edu.co/index.php/rfc/article/view/97782

الاتاحة: https://revistas.unal.edu.co/index.php/rfc/article/view/97782

المؤلفون: Montoya, José A., Figueroa-Preciado, Gudelia

المصدر: Revista de la Facultad de Ciencias; Vol. 11 No. 2 (2022): Special Issue: Flat Likelihoods; 39-53 ; Revista de la Facultad de Ciencias; Vol. 11 Núm. 2 (2022): Número Especial: Verosimilitudes Planas; 39-53 ; 2357-5549 ; 0121-747X

مصطلحات موضوعية: Flat likelihood function, threshold parameter, embedded models, GEV distribution, likelihood contours, profile likelihood function, Función de verosimilitud plana, parámetro umbral, modelo empotrado, contornos de verosimilitud, función de verosimilitud perfil, Distribución de VEG

وصف الملف: application/pdf

Relation: https://revistas.unal.edu.co/index.php/rfc/article/view/98450/84228; Barnard, G. A. (1967). The use of the likelihood function in statistical practice. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1, 27--40.; Barnard, G. A. & Sprott D. A. (1983). Likelihood. In: Kotz S, Johnson NL (eds) Encyclopedia of statistical science, Vol 4. Wiley, New York, pp 639--644.; Barndorff-Nielsen, O. E. & Cox, D. R. (1994). Inference and asymptotics. Chapman & Hall/CRC. Boca Raton.; Berger, J. O., Liseo, B. & Wolpert, R. L. (1999). Integrated likelihood methods for eliminating nuisance parameters. Statistical Science, 14(1), 1-28.; Bolívar-Cimé, A., Díaz-Francés, E. & Ortega, J. (2015). Optimality of profile likelihood intervals for quantiles of extreme value distributions: application to environmental disasters. Hydrological Sciences Journal, 60(4), 651-670.; Breusch, T. S., Robertson, J. C. & Welsh, A. H. (1997). The emperor's new clothes: a critique of the multivariate t regression model. Statistica Neerlandica, 51(3), 269-286.; Catchpole, E. A. & Morgan, B. J. (1997). Detecting parameter redundancy. Biometrika, 84(1), 187-196.; Cheng, R. C. H. & Iles, T. C. (1990). Embedded models in three-parameter distributions and their estimation. Journal of the Royal Statistical Society. Series B (Methodological), 52(1), 135-149.; Cole, S. R., Chu, H. & Greenland, S. (2013). Maximum likelihood, profile likelihood, and penalized likelihood: a primer. American Journal of Epidemiology, 179(2), 252-260.; Cousineau, D., Goodman, V. W. & Shiffrin, R. M. (2002). Extending statistics of extremes to distributions varying in position and scale and the implications for race models. Journal of Mathematical Psychology, 46(4), 431-454.; De Haan, L. (1990). Fighting the arch-enemy with mathematics. Statistica neerlandica, 44(2), 45-68.; Deng, B., Jiang, D. & Gong, J. (2018). Is a three-parameter Weibull function really necessary for the characterization of the statistical variation of the strength of brittle ceramics?. Journal of the European Ceramic Society, 38(4), 2234-2242.; El Adlouni, S., Ouarda, T. B., Zhang, X., Roy, R. & Bobée, B. (2007). Generalized maximum likelihood estimators for the nonstationary generalized extreme value model. Water Resources Research, 43(3), W03410.; Elmahdy, E. E. & Aboutahoun, A. W.(2013). A new approach for parameter estimation of finite Weibull mixture distributions for reliability modeling. Applied Mathematical Modelling, 37(4), 1800-1810.; Elmahdy, E. E. (2015). A new approach for Weibull modeling for reliability life data analysis. Applied Mathematics and computation, 250, 708-720.; Farcomeni, A. & Tardella, L. (2012). Identifiability and inferential issues in capture-recapture experiments with heterogeneous detection probabilities. Electronic Journal of Statistics, 6, 2602-2626.; Frery, A. C., Cribari-Neto, F. & De Souza, M. O. (2004). Analysis of minute features in speckled imagery with maximum likelihood estimation. EURASIP Journal on Advances in Signal Processing, 2004(16), 2476-2491.; Ghosh, M., Datta, G. S., Kim, D. & Sweeting, T. J. (2006). Likelihood-based inference for the ratios of regression coefficients in linear models. Annals of the Institute of Statistical Mathematics, 58(3), 457-473.; Green, E. J., Roesch, F. A., Smith, A. F. & Strawderman, W. E. (1994). Bayesian Estimation for the Three-Parameter Weibull Distribution with Tree Diameter Data. Biometrics, 50(1), 254-269.; Harter, H. L. & Moore, A. H. (1966). Local-maximum-likelihood estimation of the parameters of three-parameter lognormal populations from complete and censored samples. Journal of the American Statistical Association, 61(315), 842-851.; Hirose, H. & Lai, T. L. (1997). Inference from grouped data in three-parameter Weibull models with applications to breakdown-voltage experiments. Technometrics, 39(2), 199-210.; Khan, H. M., Albatineh, A., Alshahrani, S., Jenkins, N. & Ahmed, N. U. (2011). Sensitivity analysis of predictive modeling for responses from the three-parameter Weibull model with a follow-up doubly censored sample of cancer patients. Computational Statistics & Data Analysis, 55(12), 3093-3103.; Kalbfleisch, J. G. (1985). Probability and Statistical Inference, Vol. 2. Springer-Verlag. New York.; Koutsoyiannis, D. (2004). Statistics of extremes and estimation of extreme rainfall: I. Theoretical investigation/Statistiques de valeurs extrêmes et estimation de précipitations extrêmes: I. Recherche théorique. Hydrological Sciences Journal, 49(4).; Kreutz, C., Raue, A., Kaschek, D. & Timmer, J. (2013). Profile likelihood in systems biology. The FEBS journal, 280(11), 2564-2571.; Li, R. & Sudjianto, A. (2005). Analysis of computer experiments using penalized likelihood in Gaussian Kriging models. Technometrics, 47(2), 111-120.; Lima, V. M. & Cribari-Neto, F. (2019). Penalized maximum likelihood estimation in the modified extended Weibull distribution. Communications in Statistics-Simulation and Computation, 48(2), 334-349.; Liu, S., Wu, H. & Meeker, W. Q. (2015). Understanding and addressing the unbounded ``likelihood'' problem. The American Statistician}, 69(3), 191-200.; Martins, E. S. & Stedinger, J. R. (2000). Generalized maximum-likelihood generalized extreme-value quantile estimators for hydrologic data. Water Resources Research, 36(3), 737-744.; Martins, E. S. & Stedinger, J. R. (2001). Generalized maximum likelihood Pareto-Poisson estimators for partial duration series. Water Resources Research, 37(10), 2551-2557.; Montoya, J. A. (2008). La verosimilitud perfil en la Inferencia Estadística. Centro de Investigación en Matemáticas, A. C., Guanajuato, Gto., México.; Montoya, J. A., Díaz-Francés, E. & Sprott, D.A. (2009). On a criticism of the profile likelihood function. Statistical Papers, 50(1), 195-202.; Murphy, S. A. & Van Der Vaart, A. W. (2000). On profile likelihood. Journal of the American Statistical Association, 95(450), 449-465.; Pawitan, Y. (2001). In All Likelihood: Statistical Modelling and Inference Using Likelihood. Oxford University Press. New York.; Pewsey, A. (2000). Problems of inference for Azzalini's skewnormal distribution. Journal of Applied Statistics, 27(7), 859-870.; Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U. & Timmer, J. (2009). Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood. Bioinformatics, 25(15), 1923-1929.; Serfling, R. J. (2002). Approximation Theorems of Mathematical Statistics. John Wiley & Sons. New York.; Silva, H. P. T. N. & Peiris, T. S. G.(2017). Statistical modeling of weekly rainfall: a case study in Colombo city in Sri Lanka. Proceedings of the Engineering Research Conference (MERCon), Moratuwa, IEEE, 241-246.; Smith, R. L. & Naylor, J. C. (1987). A comparison of maximum likelihood and Bayesian estimators for the three parameter Weibull distribution. Journal of the Royal Statistical Society, 36(3), 358--369.; Sprott, D. A. (2000). Statistical inference in science. Springer-Verlag. New York.; Sundberg, R. (2010). Flat and multimodal likelihoods and model lack of fit in curved exponential families. Scandinavian Journal of Statistics, 37(4), 632-643.; Tsionas, E. G. (2001). Likelihood and Posterior Shapes in Johnson's System. Sankhya: The Indian Journal of Statistics, Series B, 63(1), 3-9.; Tumlinson, S. E. (2015). On the non-existence of maximum likelihood estimates for the extended exponential power distribution and its generalizations. Statistics & Probability Letters, 107, 111-114.; https://revistas.unal.edu.co/index.php/rfc/article/view/98450

الاتاحة: https://revistas.unal.edu.co/index.php/rfc/article/view/98450

المؤلفون: Castillo Cabay, Luis Cornelio

المساهمون: Díaz-Francés Murguía, Eloisa

المصدر: Centro de Investigación en Matemáticas
CIMAT
Repositorio Institucional CIMAT

مصطلحات موضوعية: Estimación / Censura / Verosimilitud / Contornos / Verosimilitud perfil / Gráficas P-P / Gráficas Q-Q / Curvas ROC / Densidad estimada / Neurobiología, 12 [cti], msc:Estimación / Censura / Verosimilitud / Contornos / Verosimilitud perfil / Gráficas P-P / Gráficas Q-Q / Curvas ROC / Densidad estimada / Neurobiología, 1 [cti]

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2a39134ff0dce972dccc800ae7fc1fd1
http://cimat.repositorioinstitucional.mx/jspui/handle/1008/210

المؤلفون: Jimenez Jimenez, Laura

المصدر: Centro de Investigación en Matemáticas
CIMAT
Repositorio Institucional CIMAT

مصطلحات موضوعية: msc:biodiversidad, especies, detectabilidad, verosimilitud perfil, cuadrante, intervalo de verosimilitud, 1 [cti]

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______3056::0525b479f790692d2fa2624aa9b43009
http://cimat.repositorioinstitucional.mx/jspui/handle/1008/459