Small-sample one-sided testing in extreme value regression models
| Autor: | Eliane C. Pinheiro, Silvia Ferrari |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Statistics and Probability
Score test Economics and Econometrics 021103 operations research Applied Mathematics Monte Carlo method 0211 other engineering and technologies Regression analysis 02 engineering and technology 01 natural sciences MODELOS NÃO LINEARES 010104 statistics & probability Gumbel distribution Sample size determination Modeling and Simulation Likelihood-ratio test Statistics Generalized extreme value distribution Econometrics 0101 mathematics Extreme value theory Social Sciences (miscellaneous) Analysis Mathematics |
| Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP |
| Popis: | We derive adjusted signed likelihood ratio statistics for a general class of extreme value regression models. The adjustments reduce the error in the standard normal approximation to the distribution of the signed likelihood ratio statistic. We use Monte Carlo simulations to compare the finite-sample performance of the different tests. Our simulations suggest that the signed likelihood ratio test tends to be liberal when the sample size is not large and that the adjustments are effective in shrinking the size distortion. Two real data applications are presented and discussed. |
| Databáze: | OpenAIRE |
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