Título
On testing the log-gamma distribution hypothesis by bootstrap
Autor
EDUARDO GUTIERREZ GONZALEZ
OLGA VLADIMIROVNA PANTELEEVA
HUMBERTO VAQUERA HUERTA
Nivel de Acceso
Acceso Abierto
Materias
Shape parameter - ([Computational Statistics (0943-4062) vol. 28(2) (2013)]) Sample correlation coefficient - ([Computational Statistics (0943-4062) vol. 28(2) (2013)]) Location scale invariant statistic - ([Computational Statistics (0943-4062) vol. 28(2) (2013)]) Goodness of fit test - ([Computational Statistics (0943-4062) vol. 28(2) (2013)]) Parametric bootstrap - ([Computational Statistics (0943-4062) vol. 28(2) (2013)]) CIENCIAS SOCIALES - (CTI)
Resumen o descripción
"In this paper we propose two bootstrap goodness of fit tests for the loggamma distribution with three parameters, location, scale and shape. These tests are built using the properties of this distribution family and are based on the sample correlation coefficient which has the property of invariance with respect to location and scale transformations. Two estimators are proposed for the shape parameter and show that both are asymptotically unbiased and consistent in mean squared error.
The test size and power is estimated by simulation. The power of the two proposed tests against several alternative distributions is compared to that of the Kolmogorov Smirnov, Anderson Darling, and chi square tests. Finally, an application to data from a production process of carbon fibers is presented."
Editor
Springer Science and Business Media
Fecha de publicación
2013
Tipo de publicación
Artículo
Recurso de información
Formato
application/pdf
Fuente
Computational Statistics (0943-4062) vol. 28(2) (2013)
Idioma
Inglés
Repositorio Orígen
REPOSITORIO UPIICSA IPN
Descargas
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