Negative binomial process count and mixture modeling
The seemingly disjoint problems of count and mixture modeling are united under the
negative binomial (NB) process. A gamma process is employed to model the rate measure …
negative binomial (NB) process. A gamma process is employed to model the rate measure …
A semiparametric negative binomial generalized linear model for modeling over-dispersed count data with a heavy tail: Characteristics and applications to crash data
Crash data can often be characterized by over-dispersion, heavy (long) tail and many
observations with the value zero. Over the last few years, a small number of researchers …
observations with the value zero. Over the last few years, a small number of researchers …
The discrete infinite logistic normal distribution for mixed-membership modeling
We present the discrete infinite logistic normal distribution (DILN,“Dylan”), a Bayesian
nonparametric prior for mixed membership models. DILN is a generalization of the …
nonparametric prior for mixed membership models. DILN is a generalization of the …
Compound random measures and their use in Bayesian non-parametrics
JE Griffin, F Leisen - Journal of the Royal Statistical Society …, 2017 - academic.oup.com
A new class of dependent random measures which we call compound random measures is
proposed and the use of normalized versions of these random measures as priors in …
proposed and the use of normalized versions of these random measures as priors in …
Bayesian nonparametric Plackett–Luce models for the analysis of preferences for college degree programmes
In this paper we propose a Bayesian nonparametric model for clustering partial ranking
data. We start by developing a Bayesian nonparametric extension of the popular Plackett …
data. We start by developing a Bayesian nonparametric extension of the popular Plackett …
Nonparametric Bayesian negative binomial factor analysis
M Zhou - 2018 - projecteuclid.org
Nonparametric Bayesian Negative Binomial Factor Analysis Page 1 Bayesian Analysis (2018)
13, Number 4, pp. 1065–1093 Nonparametric Bayesian Negative Binomial Factor Analysis …
13, Number 4, pp. 1065–1093 Nonparametric Bayesian Negative Binomial Factor Analysis …
Comparing distributions by using dependent normalized random-measure mixtures
A methodology for the simultaneous Bayesian non-parametric modelling of several
distributions is developed. Our approach uses normalized random measures with …
distributions is developed. Our approach uses normalized random measures with …
Streaming variational inference for Bayesian nonparametric mixture models
A Tank, N Foti, E Fox - Artificial Intelligence and Statistics, 2015 - proceedings.mlr.press
In theory, Bayesian nonparametric (BNP) models are well suited to streaming data scenarios
due to their ability to adapt model complexity based on the amount of data observed …
due to their ability to adapt model complexity based on the amount of data observed …
On a rapid simulation of the Dirichlet process
M Zarepour, L Al Labadi - Statistics & Probability Letters, 2012 - Elsevier
We describe a simple, yet efficient, procedure for approximating the Lévy measure of a
Gamma (α, 1) random variable. We use this approximation to derive a finite sum …
Gamma (α, 1) random variable. We use this approximation to derive a finite sum …