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...

background & aim: in the survival data with long-term survivors the event has not occurred for all the patients despite long-term follow-up, so the survival time for a certain percent is censored at the  end  of the  study.  mixture  cure  model  was  introduced  by boag,  1949  for  reaching  a  more efficient analysis of this set of data. because of some disadvantages of this model non-mixtur...

an estimation problem of the mean µ of an inverse gaussian distribution ig(µ, c µ) with known coefficient of variation c is treated as a decision problem with entropy loss function. a class of bayes estimators is constructed, and shown to include mrse estimator as its closure. two important members of this class can easily be computed using continued fractions

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...

An estimation problem of the mean µ of an inverse Gaussian distribution IG(µ, C µ) with known coefficient of variation c is treated as a decision problem with entropy loss function. A class of Bayes estimators is constructed, and shown to include MRSE estimator as its closure. Two important members of this class can easily be computed using continued fractions