On testing the log-gamma distribution hypothesis by bootstrap

Autor:	Olga Vladimirovna Panteleeva, Eduardo Gutiérrez González, José A. Villaseñor Alva, Humberto Vaquera Huerta
Rok vydání:	2013
Předmět:	Statistics and Probability Computational Mathematics Distribution (mathematics) Correlation coefficient Scale (ratio) Location test Goodness of fit Statistics Gamma distribution Estimator Statistics Probability and Uncertainty Shape parameter Mathematics
Zdroj:	Computational Statistics. 28:2761-2776
ISSN:	1613-9658 0943-4062
DOI:	10.1007/s00180-013-0427-4
Popis:	In this paper we propose two bootstrap goodness of fit tests for the log-gamma 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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::730c6e49fe12cbb9db43655b7b410f26 https://doi.org/10.1007/s00180-013-0427-4 Zobrazit plný text záznamu Full text from SpringerLink