Bayes Shrinkage Minimax Estimation in Inverse Gaussian Distribution

Bayes Shrinkage Minimax Estimation in Inverse Gaussian Distribution

The Inverse Gaussian distribution plays an important role in Reliability theory and Life testing problems. It has useful applications in a wide variety of fields such as Biology, Economics, and Medicine. It is used as an important mathematical model for the analysis of positively skewed data. The review article by Folks & Chhikara [1,2] and Seshadri [3] have proposed many interesting properties...

Shrinkage Estimation in the Inverse Rayleigh Distribution

Classic and Bayes Shrinkage Estimation in Rayleigh Distribution Using a Point Guess Based on Censored Data

Introduction      In classical methods of statistics, the parameter of interest is estimated based on a random sample using natural estimators such as maximum likelihood or unbiased estimators (sample information). In practice,  the researcher has a prior information about the parameter in the form of a point guess value. Information in the guess value is called as nonsample information. Thomp...

Minimax Estimation via Wavelet Shrinkage

We attempt to recover an unknown function from noisy, sampled data. Using orthonormal bases of compactly supported wavelets we develop a nonlinear method which works in the wavelet domain by simple nonlinear shrinkage of the empirical wavelet coe cients. The shrinkage can be tuned to be nearly minimax over any member of a wide range of Triebeland Besov-type smoothness constraints, and asymptoti...

Bayesian Estimation of Shift Point in Shape Parameter of Inverse Gaussian Distribution Under Different Loss Functions

In this paper, a Bayesian approach is proposed for shift point detection in an inverse Gaussian distribution. In this study, the mean parameter of inverse Gaussian distribution is assumed to be constant and shift points in shape parameter is considered. First the posterior distribution of shape parameter is obtained. Then the Bayes estimators are derived under a class of priors and using variou...