Publicado

2022-07-01

FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE

VEROSIMILITUDES PLANAS: CASO DE LA DISTRIBUCIÓN NORMAL SESGADA

DOI:

https://doi.org/10.15446/rev.fac.cienc.v11n2.99967

Palabras clave:

Flat likelihood shape, parameter relationship, embedded models, likelihood contours, profile likelihood, simulation study (en)
Función de verosimilitud plana, relación entre parámetros, modelos empotrados, contornos de verosimilitud, verosimilitud perfil, estudio de simulación (es)

Descargas

Autores/as

  • José A. Montoya Universidad de Sonora, México
  • Gudelia Figueroa-Preciado Universidad de Sonora, México
Several references argue in favor of alternative estimation methods, rather than the likelihood one, when the likelihood function exhibits flat regions. However, in the case of the skew normal distribution we present a discussion describing the interpretation of those flat likelihoods. This distribution is widely used in several interesting applications and contains the normal distribution as a nested model and the half-normal as an embedded model. Here, we show that flat likelihoods provide relevant information that should be carefully analyzed before discarding its use and proposing other estimation methods. Two well-known examples, that have been reported as troublesome, are analyzed here, including also an exhaustive computational study. The analysis of different scenarios allows to understand not only the reason of this likelihood function shape, but also to discover the information this behavior provides.

 

Diversas referencias argumentan a favor de métodos de estimación alternativos al de verosimilitud, cuando la función de verosimilitud exhibe regiones planas. Sin embargo, para el caso de la distribución normal sesgada se presenta una discusión donde se describe la interpretación de esas verosimilitudes planas. Esta distribución es ampliamente utilizada en diversas aplicaciones interesantes y tiene a la distribución normal como modelo anidado y a la distribución half-normal como modelo empotrado. Aquí se muestra que las verosimilitudes planas proporcionan información relevante que debe analizarse cuidadosamente, antes de abandonar su uso y proponer otros métodos de estimación. Se analizan dos ejemplos muy conocidos, que han sido reportados como problemáticos y se incluye también un estudio computacional exhaustivo. El análisis de diferentes escenarios permite comprender no sólo la razón de esta forma de la función de verosimilitud, sino también descubrir la información que este comportamiento proporciona.

Referencias

Allard, D. & Naveau, P. (2008). A new spatial skew-normal random field model. Communications in Statistics - Theory and Methods, 36(9), 1821-1834. DOI: https://doi.org/10.1080/03610920601126290

Arellano-Valle, R. B. & Azzalini, A. (2008). The centred parametrization for the multivariate skew-normal distribution. Journal of multivariate analysis, 99(7), 1362-1382. DOI: https://doi.org/10.1016/j.jmva.2008.01.020

Arrué, J., Arellano-Valle, R. B. & Gómez, H. W. (2016). Bias reduction of maximum likelihood estimates for a modified skew-normal distribution, Journal of Statistical Computation and Simulation, 86(15), 2967-2984. DOI: https://doi.org/10.1080/00949655.2016.1143471

Azzalini, A. (1985). A class of distributions which includes the normal ones. Scandinavian Journal of Statistics, 12, 171-178.

Azzalini, A. (2005). The skew-normal distribution and related multivariate families. Scandinavian Journal of Statistics, 32(2), 159-188. DOI: https://doi.org/10.1111/j.1467-9469.2005.00426.x

Azzalini, A. & Arellano-Valle, R. B. (2013). Maximum penalized likelihood estimation for skew-normal and skew-t distributions. Journal of Statistical Planning and Inference, 143(2), 419-433. DOI: https://doi.org/10.1016/j.jspi.2012.06.022

Azzalini, A. & Capitanio, A. (1999). Statistical applications of the multivariate skew normal distribution. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 61(3), 579-602. DOI: https://doi.org/10.1111/1467-9868.00194

Barndorff-Nielsen, O. E. & Cox, D. R. (1994). Inference and asymptotics. Chapman & Hall/CRC. Boca Raton. DOI: https://doi.org/10.1007/978-1-4899-3210-5

Barndorff-Nielsen, O. E. (1988). Parametric Statistical Models and Likelihood. Lecture Notes in Statistics. Springer, New York. DOI: https://doi.org/10.1007/978-1-4612-3934-5

Cole, D. J. (2020). Parameter Redundancy and Identifiability. Chapman and Hall/CRC. New York. DOI: https://doi.org/10.1201/9781315120003

Figueiredo, F. & Gomes, M. I. (2013). The skew-normal distribution in SPC. REVSTAT - Statistical Journal, 11(1), 83-104.

Gupta, A. K., Nguyen, T. T. & Sanqui, J. A. (2004). Characterization of the skew-normal distribution. Annals of the Institute of Statistical Mathematics, 56, 351-360. DOI: https://doi.org/10.1007/BF02530549

Genton, M. G. (2004). Skew-elliptical Distributions and Their Applications: a Journey Beyond Normality. Chapman & Hall/CRC. Boca Raton.

Gupta, R. C. & Brown, N. (2001). Reliability studies of the skew-normal distribution and its application to a strength-stress model. Communications in Statistics-Theory and Methods, 30, 2427-2445. DOI: https://doi.org/10.1081/STA-100107696

Hollander, M., Wolfe, Douglas A. & Chicken, E. (2014). Nonparametric Statistical Methods. Wiley. New Jersey. DOI: https://doi.org/10.1002/9781119196037

Hossain, A. & Beyene, J. (2015). Application of skew-normal distribution for detecting differential expression to microRNA data, Journal of Applied Statistics, 42(3), 477-491. DOI: https://doi.org/10.1080/02664763.2014.962490

Huber, P. J. (1981). Robust Statistics. Wiley. New York DOI: https://doi.org/10.1002/0471725250

Jones, M. C. (2015). On families of distributions with shape parameters. International Statistical Review, 83(2), 175-192. DOI: https://doi.org/10.1111/insr.12055

Jurecková J. & Picek, J. (2006). Robust Statistical Methods with R. Chapman & Hall/CRC. New York. DOI: https://doi.org/10.1201/9781420035131

Kalbfleisch, J. G. (1985). Probability and Statistical Inference, Vol. 2. Springer-Verlag. New York. DOI: https://doi.org/10.1007/978-1-4612-1096-2

Murphy, S. A. & Van Der Vaart, A. W. (2000). On profile likelihood. Journal of the American Statistical Association, 95(450), 449-465. DOI: https://doi.org/10.1080/01621459.2000.10474219

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 skew normal distribution, Journal of Applied Statistics, 27(2), 859-870. DOI: https://doi.org/10.1080/02664760050120542

Rieder, H. (1994). Robust Asymptotic Statistics. Springer-Verlag. New York. DOI: https://doi.org/10.1007/978-1-4684-0624-5

Rubio, F. J. & Genton, M. G. (2016). Bayesian linear regression with skew-symmetric error distributions with applications to survival analysis. Statistics in Medicine, 35(14), 2441-2454. DOI: https://doi.org/10.1002/sim.6897

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.

Cómo citar

APA

Montoya, J. A. y Figueroa-Preciado, G. . (2022). FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE. Revista de la Facultad de Ciencias, 11(2), 54–73. https://doi.org/10.15446/rev.fac.cienc.v11n2.99967

ACM

[1]
Montoya, J.A. y Figueroa-Preciado, G. 2022. FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE. Revista de la Facultad de Ciencias. 11, 2 (ago. 2022), 54–73. DOI:https://doi.org/10.15446/rev.fac.cienc.v11n2.99967.

ACS

(1)
Montoya, J. A.; Figueroa-Preciado, G. . FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE. Rev. Fac. Cienc. 2022, 11, 54-73.

ABNT

MONTOYA, J. A.; FIGUEROA-PRECIADO, G. . FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE. Revista de la Facultad de Ciencias, [S. l.], v. 11, n. 2, p. 54–73, 2022. DOI: 10.15446/rev.fac.cienc.v11n2.99967. Disponível em: https://revistas.unal.edu.co/index.php/rfc/article/view/99967. Acesso em: 5 sep. 2024.

Chicago

Montoya, José A., y Gudelia Figueroa-Preciado. 2022. «FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE». Revista De La Facultad De Ciencias 11 (2):54-73. https://doi.org/10.15446/rev.fac.cienc.v11n2.99967.

Harvard

Montoya, J. A. y Figueroa-Preciado, G. . (2022) «FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE», Revista de la Facultad de Ciencias, 11(2), pp. 54–73. doi: 10.15446/rev.fac.cienc.v11n2.99967.

IEEE

[1]
J. A. Montoya y G. . Figueroa-Preciado, «FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE», Rev. Fac. Cienc., vol. 11, n.º 2, pp. 54–73, ago. 2022.

MLA

Montoya, J. A., y G. . Figueroa-Preciado. «FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE». Revista de la Facultad de Ciencias, vol. 11, n.º 2, agosto de 2022, pp. 54-73, doi:10.15446/rev.fac.cienc.v11n2.99967.

Turabian

Montoya, José A., y Gudelia Figueroa-Preciado. «FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE». Revista de la Facultad de Ciencias 11, no. 2 (agosto 4, 2022): 54–73. Accedido septiembre 5, 2024. https://revistas.unal.edu.co/index.php/rfc/article/view/99967.

Vancouver

1.
Montoya JA, Figueroa-Preciado G. FLAT LIKELIHOODS: THE SKEW NORMAL DISTRIBUTION CASE. Rev. Fac. Cienc. [Internet]. 4 de agosto de 2022 [citado 5 de septiembre de 2024];11(2):54-73. Disponible en: https://revistas.unal.edu.co/index.php/rfc/article/view/99967

Descargar cita

CrossRef Cited-by

CrossRef citations0

Dimensions

PlumX

Visitas a la página del resumen del artículo

189

Descargas

Los datos de descargas todavía no están disponibles.