AbstractGeneral formulas of the asymptotic cumulants of a studentized parameter estimator are given up to the fourth order with the added higher-order asymptotic variance. Using the sample counterparts of the asymptotic cumulants, formulas for the Cornish–Fisher expansions with third-order accuracy are obtained. Some new methods of monotonic transformations of the studentized estimator are presented. In addition, similar transformations of a fixed normal deviate are proposed up to the same order with some asymptotic comparisons to the transformations of the studentized estimator. Applications to a mean and a binomial proportion are shown with simulations for estimation of the proportion
Cornish and Fisher were the firsts scholars who have analysed transformations of the random variable...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
Asymptotic cumulants of functions of multinomial sample proportions with and without studentization ...
This paper presents discussion of properties of asymptotic confidence intervals based on a normalizi...
AbstractAsymptotic expansions of the distributions of parameter estimators in mean and covariance st...
The asymptotic cumulants of the parameter estimators for the three-parameter logistic model in item ...
Accurate distributions of the estimator of the tetrachoric correlation coefficient and, more general...
AbstractAn asymptotic expansion of the null distribution of the Wilks’ lambda statistic is derived w...
Abstract. Suppose that a statistic S is asymptotically distributed as a distri-bution function G(x) ...
This paper applies a regularization procedure called increasing rearrangement to monotonize Edgewort...
AbstractWe derive asymptotic expansions for the distributions of the normal theory maximum likelihoo...
AbstractAccurate distributions of the estimator of the tetrachoric correlation coefficient and, more...
Cornish and Fisher were the firsts scholars who have analysed transformations of the random variable...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
An asymptotic expansion of the Student t distribution is derived by expanding the standardized Stude...
Asymptotic cumulants of functions of multinomial sample proportions with and without studentization ...
This paper presents discussion of properties of asymptotic confidence intervals based on a normalizi...
AbstractAsymptotic expansions of the distributions of parameter estimators in mean and covariance st...
The asymptotic cumulants of the parameter estimators for the three-parameter logistic model in item ...
Accurate distributions of the estimator of the tetrachoric correlation coefficient and, more general...
AbstractAn asymptotic expansion of the null distribution of the Wilks’ lambda statistic is derived w...
Abstract. Suppose that a statistic S is asymptotically distributed as a distri-bution function G(x) ...
This paper applies a regularization procedure called increasing rearrangement to monotonize Edgewort...
AbstractWe derive asymptotic expansions for the distributions of the normal theory maximum likelihoo...
AbstractAccurate distributions of the estimator of the tetrachoric correlation coefficient and, more...
Cornish and Fisher were the firsts scholars who have analysed transformations of the random variable...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...
Abstract. This paper provides a uni\u85ed and comprehensive approach that is useful in deriving expr...