SciELO - Scientific Electronic Library Online

 
vol.41 número2Using an Anchor to Improve Linear Predictions with Application to Predicting Disease ProgressionArtificial Neuronal Networks: A Bayesian Approach Using Parallel Computing índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Em processo de indexaçãoCitado por Google
  • Não possue artigos similaresSimilares em SciELO
  • Em processo de indexaçãoSimilares em Google

Compartilhar


Revista Colombiana de Estadística

versão impressa ISSN 0120-1751

Rev.Colomb.Estad. vol.41 no.2 Bogotá jul./dez. 2018

https://doi.org/10.15446/rce.v41n2.62233 

Artículos originales de investigación

Form-Invariance of the Non-Regular Exponential Family of Distributions

Distribuciones de forma invariante de la familia exponencial no regular

S. Ghorbanpour1  a 

R. Chinipardaz1  b 

1 Department of Statistics, Faculty of Mathematical Sciences and Computer, Shahid Chamran University of Ahvaz, Ahvaz, Iran.


Abstract

The weighted distributions are used when the sampling mechanism records observations according to a nonnegative weight function. Sometimes the form of the weighted distribution is the same as the original distribution except possibly for a change in the parameters that are called the form-invariant weighted distribution. In this paper, by identifying a general class of weight functions, we introduce an extended class of form-invariant weighted distributions belonging to the non-regular exponential family which included two common families of distribution: exponential family and non-regular family as special cases. Some properties of this class of distributions such as the su-cient and minimal su-cient statistics, maximum likelihood estimation and the Fisher information matrix are studied.

Key words: Fisher information matrix; Form-invariance; Non-regular exponential family; Maximum likelihood estimation; Weighted distribution

Resumen

Las distribuciones ponderadas son usadas cuando el mecanismo de muestreo registra observaciones de acuerdo a una función no negativa. En ocasiones la forma de la función ponderada es igual a la original, excepto, posiblemente, en un cambio de parámetros y se denominan distribuciones ponderadas de forma invariante. En este artículo identificamos una clase general de funciones ponderadas e introducimos una forma extendida de distribuciones ponderadas de forma invariante, la cual incluye dos familias comunes: la familia exponencial y la familia no regular como caso particular. Algunas propiedades de estas distribuciones como las estadísticas suficientes y máximas suficientes, la estimación de máxima verosimilitud y la matriz de información de Fisher son estudiadas.

Palabras clave: distribución ponderada; estimación de máxima verosimilitud; familia exponencial no regular; invarianza de forma; matriz de información de Fisher

Full text available only in PDF format.

References

Alavi, S. & Chinipardaz, R. (2009), `Form-invariance under weighted sampling', Statistics 43(1), 81-90. [ Links ]

Billingsley, P. (1979), Probability and Measure, Wiley, New York. [ Links ]

Esparza, L. (2013), `On size-biased matrix-geometric distributions', Performance Evaluation 70(9), 639-645. [ Links ]

Gupta, R. & Keating, J. (1986), `Relations for reliability measures under length biased sampling', Scandinavian Journal of Statistics 13(1), 49-56. [ Links ]

Gupta, R. & Kirmani, S. (1990), `The role of weighted distributions in stochastic modeling', Communications in Statistics - Theory and Methods 19(9), 3147- 3162. [ Links ]

Nair, N. & Sunoj, S. (2003), `Form-invariant bivariate weighted models', Statistics 37(3), 259-269. [ Links ]

Oluyede, B. & George, E. (2002), `On stochastic inequalities and comparisons of reliability measures for weighted distributions', Mathematical Problems in Engineering 8(1), 1-13. [ Links ]

Patil, G. & Ord, J. (1976), `On size-biased sampling and related form-invariant weighted distributions', Sankhy a: The Indian Journal of Statistics, Series B 38(1), 48-61. [ Links ]

Patil, G. & Rao, C. (1978), `Weighted distributions and size-biased sampling with applications to wildlife populations and human families', Biometrics 34(2), 179-189. [ Links ]

Patil, G. & Taillie, C. (1987), Weighted distributions and the effects of weight functions on sher informations, Technical report, Centre for Statistical Ecology and Environmental Statistics, Department of Statistics, Pennsylvania State University. [ Links ]

Rao, B. (1958), `On an analogue of Cramér-Rao's inequality', Scandinavian Actuarial Journal 1958(1-2), 57-67. [ Links ]

Rao, C. (1965), `On discrete distributions arising out of methods of ascertainment', Sankhy a: The Indian Journal of Statistics, Series A 27(2), 311-324 [ Links ]

Sankaran, P. & Nair, N. (1993), `On form invariant length biased models from Pearson family', Journal of the Indian Society for Probability and Statistics 31(1), 85-89 [ Links ]

Sindu, T. (2002), An extended Pearson system useful in reliability analysis., PhD Thesis, Cochin University of Science and Technology, Department of Statistics, Cochin. [ Links ]

Received: January 2017; Accepted: January 2018

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License