Nonparametric Bayesian Multiple Comparisons for Dependence Parameter in Bivariate Exponential Populations

Nonparametric Bayesian Multiple Comparisons for Dependence Parameter in Bivariate Exponential Populations

Estimating E-Bayesian of Parameters of two parameter Exponential Distribution

‎In this study‎, ‎E-Bayesian of parameters of two parameter exponential distribution under squared error loss function is obtained‎. ‎The estimated and the efficiency of the proposed method has been compared with Bayesian estimator using Monte Carlo simulation‎. 

Nonparametric Predictive Inference for Multiple Comparisons

This thesis presents Nonparametric Predictive Inference (NPI) for several multiple comparisons problems. We introduce NPI for comparison of multiple groups of data including right-censored observations. Different right-censoring schemes discussed are early termination of an experiment, progressive censoring and competing risks. Several selection events of interest are considered including selec...

A new bivariate exponential distribution for modeling moderately negative dependence

This paper introduces a new bivariate exponential distribution, called the Bivariate Affine-Linear Exponential distribution, to model moderately negative dependent data. The construction and characteristics of the proposed bivariate distribution are presented along with estimation procedures for the model parameters based on maximum likelihood and objective Bayesian analysis. We derive Jeffreys...

Nonparametric Bayesian inference on multivariate exponential families

We develop a model by choosing the maximum entropy distribution from the set of models satisfying certain smoothness and independence criteria; we show that inference on this model generalizes local kernel estimation to the context of Bayesian inference on stochastic processes. Our model enables Bayesian inference in contexts when standard techniques like Gaussian process inference are too expe...