Bias and skewness in a general extreme-value regression model
In this paper we introduce a general extreme-value regression model and derive Cox and Snell's (1968) general formulae for second-order biases of maximum likelihood estimates (MLEs) of the parameters. We obtain formulae which can be computed by means of weighted linear regressions. Furthermore, we give the skewness of order n-1/2 of the maximum likelihood estimators of the parameters by using Bowman and Shenton's (1988) formula. A simulation study with results obtained with the use of Cox and Snell's (1968) formulae is discussed. Practical uses of this model and of the derived formulae for bias correction are also presented.
Year of publication: |
2011
|
---|---|
Authors: | Barreto-Souza, Wagner ; Vasconcellos, Klaus L.P. |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 55.2011, 3, p. 1379-1393
|
Publisher: |
Elsevier |
Keywords: | Extreme-value regression model Dispersion covariates Maximum likelihood estimates Bias correction Skewness |
Saved in:
Saved in favorites
Similar items by person
-
Influence analysis with homogeneous linear restrictions
Vasconcellos, Klaus L.P., (2009)
-
Some restriction tests in a new class of regression models for proportions
Melo, Tatiane F.N., (2009)
-
Ospina, Raydonal, (2011)
- More ...