Point and interval estimation for extreme-value regression model under Type-II censoring
Computational Statistics & Data Analysis
Improved estimators for a general class of beta regression models
Computational Statistics & Data Analysis
Improved point and interval estimation for a beta regression model
Computational Statistics & Data Analysis
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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.