## Bayesian Assessment of Goodness-of-Fit against Nonparametric Alternatives (2000)

### BibTeX

@MISC{Conigliani00bayesianassessment,

author = {C. Conigliani and J. I. Castro and A. O'Hagan},

title = {Bayesian Assessment of Goodness-of-Fit against Nonparametric Alternatives},

year = {2000}

}

### OpenURL

### Abstract

The classical chi-square test of goodness-of-fit compares the hypothesis that data arise from some parametric family of distributions, against the nonparametric alternative that they arise from some other distribution. However, the chi-square test requires continuous data to be grouped into arbitrary categories. Furthermore, as the test is based upon an approximation, it can only be used if there is su#cient data. In practice, these requirements are often wasteful of information and overly restrictive. The authors explore the use of the fractional Bayes factor to obtain a Bayesian alternative to the chi-square test when no specific prior information is available. They consider the extent to which their methodology can handle small data sets and continuous data without arbitrary grouping.