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The present paper investigates the properties of a testimator of scale of an exponential distribution under Linex loss function. The risk function of testimator is derived and compared with that of an admissible estimator relative to Linex loss function. The shrinkage testimator is proposed which is the extension of testimator and its properties have been discussed. The level of significance of testimator is decided on the basis of Akaike information criterion following Hirano (1977, 1978). It is found that the testimator and shrinkage testimator dominates the admissible estimator in terms of risk in certain parametric space.

The Bayesian estimator for the shape parameter of Pareto distribution using LINEX loss function has been obtained. The properties of the estimator in respect of risk have been studied and it is found that the LINEX estimator is preferable to the squared error estimator for specific values of c nearer to zero.

The Bayesian shrinkage estimation for a measure of dispersion with known mean is studied for the inverse Gaussian distribution. An optimum choice of the shrinkage factor and the properties of the proposed Bayesian shrinkage estimators are being studied. It is shown that these estimators have smaller risk than the usual estimator of the reciprocal measure of dispersion.

In this paper, the Bayes estimators for mean and square of mean ol a normal distribution with mean μ and vaiiance σ r2 (known), relative to LINEX loss function are obtained Comparisons in terms of risk functions and Bayes risks of those under LINEX loss and squared error loss functions with their respective alternative estimators viz, UMVUE and Bayes estimators relative to squared error loss function, are made. It is found that Bayes estimators relative to LINEX loss function dominate the alternative estimators m terms of risk function snd Bayes risk. It is also found that if t2 is unknown the Bayes estimators are still preferable over alternative estimators.

A weighted estimator for the variance of a normal distribution using a point guess value of the population variance σ2 is proposed. The weight considered is a function of the scalars a, b (0≤a≤1, b>0) and the test statistic used for testing the hypothesis . Keeping b fixed (a small number), three different estimates of amin(for which the mean square error of the weighted estimator is minimum) have been obtained and the corresponding estimators are proposed. The properties of the proposed estimators are studied and recommendations for their use are made.

This paper provides the modified likelihood ratio criterion for testing whether the mean of the inverse Gaussian distribution can be set to unity giving rise to Standard form of the Wald distribution. Estimates of probability of correct selection has been obtained on the basis of a Monte Carlo study of 1,000 samples. Finally a set of adaptive estimators for the parameters are proposed and studied on the basis of data generated from the two distributions.

In this paper we propose some shrinkage testimators for the shape parameter of the Weibull distribution when censored samples are available and study their properties. Comparison of the testimators with Singh and Bhatkulikar (1978) and with the usual estimator, interms of mean squared error are made. It is shown that the proposed testimators

Some shrunken estimators of the normal population variance 2 are proposed and compared with the usual estimator, s2, in terms of mean squared error.