A quantitative procedure to decide whether a model provides a good descriptionof data is often based on a specific test statistic and a p-value summarizingboth the data and the statistic's sampling distribution. We provide a Bayesianmotivation for using p-values in the goodness-of-fit problem with no explicitalternative models considered. Some typical pitfalls encountered with commonstatistics are reviewed for Poisson and Gaussian uncertainties. Finally, wepresent a new test statistic for ordered Gaussian data, the runs statistic
The P value was introduced as a value to evaluate the results of statistical tests. The basic concep...
This work deals with a decision-theoretic evaluation of p-value rules. A test statistic is judged on...
Abstract: P-splines are a popular approach for fitting nonlinear effects of continuous covariates in...
Deciding whether a model provides a good description of data is often based on a goodness-of-fit cri...
Deciding whether a model provides a good description of data is often based on a goodness-of-fit cri...
Bayesian analysis provides a consistent logical framework for processing data, inferring parameters ...
A p-value is the probability of observing a result as extreme or more extreme than that observed giv...
Two procedures for checking Bayesian models are compared using a simple test problem based on the lo...
Bayesian p values are a popular and important class of approaches for Bayesian model Checking. They ...
In this thesis, two areas of goodness-of fit are discussed and new methodology proposed. In the fir...
Models are the venue for much of the work of the economics profession. We use them to express, compa...
This article addresses issues of model choice in Bayesian contexts, and focusses on the use of the s...
This paper reviews recent contributions from a Bayesian-oriented perspective, after the ASA statemen...
The p-value has dominated research in education and related fields and a statistically non-significa...
We\u27ve all heard about the serious limitations of frequentist statistics: p-hacking, misinterprete...
The P value was introduced as a value to evaluate the results of statistical tests. The basic concep...
This work deals with a decision-theoretic evaluation of p-value rules. A test statistic is judged on...
Abstract: P-splines are a popular approach for fitting nonlinear effects of continuous covariates in...
Deciding whether a model provides a good description of data is often based on a goodness-of-fit cri...
Deciding whether a model provides a good description of data is often based on a goodness-of-fit cri...
Bayesian analysis provides a consistent logical framework for processing data, inferring parameters ...
A p-value is the probability of observing a result as extreme or more extreme than that observed giv...
Two procedures for checking Bayesian models are compared using a simple test problem based on the lo...
Bayesian p values are a popular and important class of approaches for Bayesian model Checking. They ...
In this thesis, two areas of goodness-of fit are discussed and new methodology proposed. In the fir...
Models are the venue for much of the work of the economics profession. We use them to express, compa...
This article addresses issues of model choice in Bayesian contexts, and focusses on the use of the s...
This paper reviews recent contributions from a Bayesian-oriented perspective, after the ASA statemen...
The p-value has dominated research in education and related fields and a statistically non-significa...
We\u27ve all heard about the serious limitations of frequentist statistics: p-hacking, misinterprete...
The P value was introduced as a value to evaluate the results of statistical tests. The basic concep...
This work deals with a decision-theoretic evaluation of p-value rules. A test statistic is judged on...
Abstract: P-splines are a popular approach for fitting nonlinear effects of continuous covariates in...