What are the advantages of using t distribution components in Bayesian non-parametrics?

Oct 12, 2023 ... We address the problem of computing a consistency factor for the MCD estimator in a heavy-tail scenario, when uncontaminated data come from a multivariate ... Mar 26, 2025 ... Student's t-test, in statistics, a method of testing hypotheses about the mean of a small sample drawn from a normally distributed population The Student-t Distribution ... Density, distribution function, quantile function and random generation for the Student-t distribution with location mu , scale ... Statistics in Python: Student's t-Distributions ... Student's t-Distributions are a generalisation of the standard normal distribution. Their exact shapes depend ... The decoder infers the posterior distribution of observation given a latent variable. The encoder and de- coder neural networks are optimized by minimizing the ... a continuous probability distribution that generalizes the standard normal distribution. Like the latter, it is symmetric around zero and bell-shaped. (2) Student's t-distribution is less peaked than a normal distribution, at the same time, t-distribution has “fatter tails”. In this way, it seems like that ... Feb 2, 2019 ... The normal distribution is a special case of Student's t t t-distribution with the ν \nu ν parameter (i.e., the degree of freedom) set to ... Sep 3, 2018 ... The skew normal family is great for modeling skewed gaussian data, and the student t distribution is great for outliers. Student's T distribution. Describes a normal variable whose precision is gamma distributed. If only nu parameter is passed, this specifies a standard (central) ...