In this paper, the reliability of stress-strength model is derived for probability P( <X< ) a component strength X between two stresses , when and are independent Gompertz Fréchet distribution with unknown known shape parameters common scale parameters. Different methods used to estimate R which [Maximum Likelihood, Least square, Weighted Regression Ranked set sampling methods], compariso...

Estimation methods are proposed for fitting logistic regression in which outcome and covariate variables are missing separately or simultaneously. One of the two proposed estimators is an extension of the validation likelihood estimator of BreslowandCain (1988). The other is a joint conditional likelihood estimator that uses both validation and nonvalidation data. Large sample properties of the...

In this paper we obtain robust estimators for copula parameters through the minimization of weighted goodness of ̄t statistics. Di®erent weight functions emphasize di®erent regions on the unit square and are able to handle di®erent locations of model violation. The resultingWMDE estimators are compared to the classical maximum likelihood estimatorsMLE, and to their weighted version WMLE, an est...

This paper addresses the problem of estimating the mean vector of a singular multivariate normal distribution with an unknown singular covariance matrix. The maximum likelihood estimator is shown to be minimax relative to a quadratic loss weighted by the Moore-Penrose inverse of the covariance matrix. An unbiased risk estimator relative to the weighted quadratic loss is provided for a Baranchik...

Tthe Zografos–Balakrishnan-log-logistic (ZBLL) distribution is a new distribution of three parameters that has been introduced by Ramos et el. [1], and They presented some properties of the new distribution such as its probability density function, The cumulative distribution function, The  moment generating function, its hazard (failure) rate function, quantiles and moments, Rényi and Shannon ...

In this paper, we consider the problem of estimating and testing a general linear hypothesis in a general multivariate linear model, the so called Growth Curve model, when the p×N observation matrix is normally distributed with an unknown covariance matrix. The maximum likelihood estimator (MLE) for the mean is a weighted estimator with the inverse of the sample covariance matrix which is unsta...

Abstract The exponentiated Burr Type XII (EBXII) distribution has wide applications in reliability and economic studies. In this article, the estimation of probability density function cumulative EBXII is considered. We examine maximum likelihood estimator, uniformly minimum variance unbiased least squares weighted product spacing Cramér–von-Mises Anderson–Darling estimator. derive analytical f...

The Pareto distribution is often used in many areas of economics to model the right tail of heavytailed distributions. However, the standard method of estimating the shape parameter (the Pareto index) of this distribution– the maximum likelihood estimator (MLE) – is non-robust, in the sense that it is very sensitive to extreme observations, data contamination or model deviation. In recent years...

In this paper, we have executed a new model of Power Quasi Lindley distribution known as Weighted by introducing the weighted technique. We also its various mathematical and statistical properties like order statistics, likelihood Ratio test, moments, harmonic mean, Income curves, entropy reliability measures. discussed parameter estimation applying method maximum estimator obtained Fisher’s ...