Add to ORKGThe aim of this work is to highlight some interesting connections between contingency tables analysis and design of experiments. In particular, we consider two-way tables in correspondence to two-factor designs.We provide a condition that characterizes the estimability of the independence model for all saturated fractions
Diaconis-Sturmfels developed an algorithm for sampling from conditional distributions for a statisti...
AbstractA contingency table summarizes the conditional frequencies of two attributes and shows how t...
The goal of the paper is to recall a recently introduced concept of con-ditional independence in evi...
The aim of this work is to highlight some interesting connections between contingency tables analysi...
The aim of this work is to highlight some interesting connections between contingency tables analysi...
In this paper we study a new class of statistical models for contingency tables. We define this clas...
We use a close connection between the theory of Markov fields and that of log-linear interaction mod...
The Diaconis-Sturmfels algorithm is a method for sampling from conditional distributions, based on t...
The Diaconis-Sturmfels algorithm is a method for sampling from conditional distributions, based on t...
This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC me...
Frequently, contingency tables are generated in a multinomial sampling. Multinomial probabilities ar...
The analysis of R×C contingency tables usually features a test for independence between row and colu...
We propose a class of multiplicative models to describe the dependence of the response count on the ...
In this paper we study the computation of Markov bases for contingency tables whose cell entries hav...
Log-linear models are a classical tool for the analysis of contingency tables. In particular, the su...
Diaconis-Sturmfels developed an algorithm for sampling from conditional distributions for a statisti...
AbstractA contingency table summarizes the conditional frequencies of two attributes and shows how t...
The goal of the paper is to recall a recently introduced concept of con-ditional independence in evi...
The aim of this work is to highlight some interesting connections between contingency tables analysi...
The aim of this work is to highlight some interesting connections between contingency tables analysi...
In this paper we study a new class of statistical models for contingency tables. We define this clas...
We use a close connection between the theory of Markov fields and that of log-linear interaction mod...
The Diaconis-Sturmfels algorithm is a method for sampling from conditional distributions, based on t...
The Diaconis-Sturmfels algorithm is a method for sampling from conditional distributions, based on t...
This thesis is mainly concerned with conditional inference for contingency tables, where the MCMC me...
Frequently, contingency tables are generated in a multinomial sampling. Multinomial probabilities ar...
The analysis of R×C contingency tables usually features a test for independence between row and colu...
We propose a class of multiplicative models to describe the dependence of the response count on the ...
In this paper we study the computation of Markov bases for contingency tables whose cell entries hav...
Log-linear models are a classical tool for the analysis of contingency tables. In particular, the su...
Diaconis-Sturmfels developed an algorithm for sampling from conditional distributions for a statisti...
AbstractA contingency table summarizes the conditional frequencies of two attributes and shows how t...
The goal of the paper is to recall a recently introduced concept of con-ditional independence in evi...