Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures
نویسندگان
چکیده
منابع مشابه
Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions
A Bayesian analysis of stochastic volatility (SV) models using the class of symmetric scale mixtures of normal (SMN) distributions is considered. In the face of non-normality, this provides an appealing robust alternative to the routine use of the normal distribution. Specific distributions examined include the normal, student-t, slash and the variance gamma distributions. Using a Bayesian para...
متن کاملRobust Regression Credibility Models for Heavy-Tailed Claims
In actuarial practice, regression models serve as a popular statistical tool for analyzing insurance data and tariff ratemaking. In this paper, we consider classical credibility models that can be embedded within the framework of mixed linear models. For inference about fixed effects and variance components, likelihood-based methods such as (restricted) maximum likelihood estimators are commonl...
متن کاملBayesian Model Selection in Finite Mixtures by Marginal Density Decompositions
We consider the problem of estimating the number of components d and the unknown mixing distribution in a nite mixture model, in which d is bounded by some xed nite number N . Our approach relies on the use of a prior over the space of mixing distributions with at most N components . By decomposing the resulting marginal density under this prior, we discover a weighted Bayes factor method...
متن کاملComparing Bayesian Model Class Selection Criteria by Discrete Finite Mixtures
We investigate the problem of computing the posterior probability of a model class, given a data sample and a prior distribution for possible parameter settings. By a model class we mean a group of models which all share the same parametric form. In general this posterior may be very hard to compute for high-dimensional parameter spaces, which is usually the case with real-world applications. I...
متن کاملBayesian analysis of robust Poisson geometric process model using heavy-tailed distributions
We propose a robust Poisson geometric process model with heavy-tailed distributions to cope with the problem of outliers as it may lead to an overestimation of mean and variance resulting in inaccurate interpretations of the situations. Two heavy-tailed distributions namely Student’s t and exponential power distributions with different tailednesses and kurtoses are used and they are represented...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Brazilian Journal of Probability and Statistics
سال: 2020
ISSN: 0103-0752
DOI: 10.1214/18-bjps417