On some general distributions in terms of generalized functions
On some properties of ML and REML estimators in mixed normal models with two variance components
In the paper, the problem of estimation of variance components σ₁² and σ₂² by using the ML-method and REML-method in a normal mixed linear model 𝒩 {Y,E(Y) = Xβ, Cov(Y) = σ₁²V + σ₂²Iₙ} is considered. This paper deal with properties of estimators of variance components, particularly when an explicit form of these estimators is unknown. The conditions when the ML and REML estimators can be expressed in explicit forms are given, too. The simulation study for one-way classification unbalanced random...
On Special Case of Multiple Hypotheses Optimal Testing for Three Differently Distributed Random Variables
2000 Mathematics Subject Classification: 62P30.In this paper by using theory of large deviation techniques (LDT), the problem of hypotheses testing for three random variables having different distributions from three possible distributions is solved. Hypotheses identification for two objects having different distributions from two given probability distributions was examined by Ahlswewde and Haroutunian. We noticed Sanov's theorem and its applications in hypotheses testing.
On testing hypotheses approximable by cones
On Testing the Correlation Coefficient of a Bivariate Normal Distribution.
On testing variance components in unbalanced mixed linear model
The paper presents some approximate and exact tests for testing variance components in general unbalanced mixed linear model. It extends the results presented by Seifert (1992) with emphasis on the computational aspects of the problem.
On the admissibility of tests for extended hypotheses of fit
On the asymptotic probability for the deviations of dependent bootstrap means from the sample mean.
On the Bayes approach in general multiple autoregressive series
On the Bayes estimators of the parameters of inflated modified power series distributions
In this paper, we study the class of inflated modified power series distributions (IMPSD) where inflation occurs at any of support points. This class includes among others the generalized Poisson,the generalized negative binomial and the lost games distributions. We derive the Bayes estimators of parameters for these distributions when a parameter of inflation is known. First, we take as the prior distribution the uniform, Beta and Gamma distribution. In the second part of this paper, the prior...
On the Choice of Support of Re-Descending ...-Functions in Linear Models with Asymmetric Error Distributions.
On the compound Poisson-gamma distribution
The compound Poisson-gamma variable is the sum of a random sample from a gamma distribution with sample size an independent Poisson random variable. It has received wide ranging applications. In this note, we give an account of its mathematical properties including estimation procedures by the methods of moments and maximum likelihood. Most of the properties given are hitherto unknown.
On the Confidence Region for the One-Sample x2-Test.
On the confidence region of a vector parameter
On the continuity of the minimal -entropy
On the convergence of Bhattacharyya bounds in the multiparameter case
On the convergence of extreme distributions under power normalization
This paper deals with the convergence in distribution of the maximum of n independent and identically distributed random variables under power normalization. We measure the difference between the actual and asymptotic distributions in terms of the double-log scale. The error committed when replacing the actual distribution of the maximum under power normalization by its asymptotic distribution is studied, assuming that the cumulative distribution function of the random variables is known. Finally,...
On the convergence of the Bhattacharyya bounds in the multiparametric case
Shanbhag (1972, 1979) showed that the diagonality of the Bhattacharyya matrix characterizes the set of normal, Poisson, binomial, negative binomial, gamma or Meixner hypergeometric distributions. In this note, using Shanbhag's techniques, we show that if a certain generalized version of the Bhattacharyya matrix is diagonal, then the bivariate distribution is either normal, Poisson, binomial, negative binomial, gamma or Meixner hypergeometric. Bartoszewicz (1980) extended the result of Blight and...
On the Convergence of the Critical Values of Uniformly Most Powerful Unbiased Tests for Two-Sided Hypotheses.
On the coverage probability of confidence sets based on a prior distribution