In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

In this paper we develop a general framework of Bayesian influence analysis for assessing various perturbation schemes to the data, the prior and the sampling distribution for a class of statistical ...

It turns out that the old adage about statistics and damned lies wasn’t a joke. Sticks and stones may be bonebreakers, and words inflict no (physical) pain, but numbers can kill. In 2004, for instance ...

Naive Bayes classification is a machine learning technique that can be used to predict the class of an item based on two or more categorical predictor variables. For example, you might want to predict ...

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...

CATALOG DESCRIPTION: Fundamental and advanced topics in statistical pattern recognition including Bayesian decision theory, Maximum-likelihood and Bayesian estimation, Nonparametric density estimation ...