We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test
Frequently, contingency tables are generated in a multinomial sampling. Multinomial probabilities ar...
This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC me...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...
Testing for the independence between two categorical variables R and S forming a contingency table i...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
A condition needed for testing nested hypotheses from a Bayesianviewpoint is that the prior for the ...
The main purpose of this work is to describe three well-known statistical tests of independence in t...
The analysis of R×C contingency tables usually features a test for independence between row and colu...
The display of the data by means of contingency tables is used in different approaches to statistica...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
In this paper we present a method of computing the posterior probability of conditional independence...
iAbstract We consider estimating the cell probabilities and testing hypotheses in a two-way continge...
A Monte Carlo exact conditional test of quasi-independence in two-way incomplete contingency tables ...
nonparametric regression; conditional independence; adjusted Nadaraya-Watson estimator; long-range d...
In a multinomial sampling, contingency tables can be parametrized by probabilities of each cell. The...
Frequently, contingency tables are generated in a multinomial sampling. Multinomial probabilities ar...
This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC me...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...
Testing for the independence between two categorical variables R and S forming a contingency table i...
AbstractTesting for the independence between two categorical variables R and S forming a contingency...
A condition needed for testing nested hypotheses from a Bayesianviewpoint is that the prior for the ...
The main purpose of this work is to describe three well-known statistical tests of independence in t...
The analysis of R×C contingency tables usually features a test for independence between row and colu...
The display of the data by means of contingency tables is used in different approaches to statistica...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
In this paper we present a method of computing the posterior probability of conditional independence...
iAbstract We consider estimating the cell probabilities and testing hypotheses in a two-way continge...
A Monte Carlo exact conditional test of quasi-independence in two-way incomplete contingency tables ...
nonparametric regression; conditional independence; adjusted Nadaraya-Watson estimator; long-range d...
In a multinomial sampling, contingency tables can be parametrized by probabilities of each cell. The...
Frequently, contingency tables are generated in a multinomial sampling. Multinomial probabilities ar...
This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC me...
AbstractConsider an r × c contingency table under the full multinomial model where each category is ...