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This article presents procedures for testing hypothesis and interval estimation of the common mean vector in MANOVA models when the covariance matrices are unknown and unequal. The methods are based on the concepts of generalized p -value and generalized confidence interval. Some important...
We carried out a simulation study based on the methodology of Newcombe (1998) to compare tests for the difference of two binomial proportions by applying different continuity corrections on saddlepoint approximation to tail probabilities. In this article, we proposed a new continuity correction...
Robust Bayesian analysis is connected with the effect of changing a prior within a class Γ instead of being specified exactly. The multiplicity of prior leads to a collection or a range of Bayes actions. It is interesting not only to investigate the range of estimators but also to recommend the...
The Schl milch transformation, long used by mathematicians for integral evaluation, allows probability mass to be redistributed, thus transforming old distributions to new ones. The transformation is used to introduce some new families of distributions on R + . Their general properties are...
Distributional equations of the form are studied, where X and Y are neighboring generalized order statistics based on distribution function F , and V is a power function or Pareto distributed random variable, independent of Y . Characterizations of distributions via random contraction and random...
Varying-coefficient models are useful extensions of classical linear models. They arise from multivariate nonparametric regression, nonlinear time series modeling and forecasting, longitudinal data analysis, and others. This article proposes the penalized spline estimation for the...
We derive general formulae for the second-order biases of maximum likelihood estimates of the parameters in generalized nonlinear models with dispersion covariates. This result generalizes previous work by Botter and Cordeiro (1998) and Cordeiro and McCullagh (1991). The practical use of such...
This article investigates the possible use of our newly defined extended projection depth (abbreviated to EPD) in nonparametric discriminant analysis. We propose a robust nonparametric classifier, which relies on the intuitively simple notion of EPD. The EPD-based classifier assigns an...
We study the problem of selecting the optimal functional form among a set of non nested, nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...
In this work we re-examine some classical bounds for non negative integer-valued random variables by means of information theoretic or maxentropic techniques using fractional moments as constraints. The proposed new bound, no more analytically expressible in terms of moments or moment generating...
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