fipp: Induced Priors in Bayesian Mixture Models

Jan Greve; Bettina Grün; Gertraud Malsiner-Walli; Sylvia Frühwirth-Schnatter

fipp: Induced Priors in Bayesian Mixture Models

Jan Greve^* (Developer), Bettina Grün (Developer), Gertraud Malsiner-Walli (Developer), Sylvia Frühwirth-Schnatter (Developer)

^*Corresponding author for this work

Institute for Statistics and Mathematics

Publication: Non-textual form › Software

Abstract

Computes implicitly induced quantities from prior/hyperparameter specifications of three Mixtures of Finite Mixtures models: Dirichlet Process Mixtures (DPMs; Escobar and West (1995) ), Static Mixtures of Finite Mixtures (Static MFMs; Miller and Harrison (2018) ), and Dynamic Mixtures of Finite Mixtures (Dynamic MFMs; Frühwirth-Schnatter, Malsiner-Walli and Grün (2020) ). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) ) as well as the package vignette.

Original language	English
Publisher	R Foundation for Statistical Computing
Publication status	Published - 11 Feb 2021

Austrian Classification of Fields of Science and Technology (ÖFOS)

101018 Statistics

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title = "fipp: Induced Priors in Bayesian Mixture Models",

abstract = "Computes implicitly induced quantities from prior/hyperparameter specifications of three Mixtures of Finite Mixtures models: Dirichlet Process Mixtures (DPMs; Escobar and West (1995) ), Static Mixtures of Finite Mixtures (Static MFMs; Miller and Harrison (2018) ), and Dynamic Mixtures of Finite Mixtures (Dynamic MFMs; Fr{\"u}hwirth-Schnatter, Malsiner-Walli and Gr{\"u}n (2020) ). For methodological details, please refer to Greve, Gr{\"u}n, Malsiner-Walli and Fr{\"u}hwirth-Schnatter (2020) ) as well as the package vignette.",

author = "Jan Greve and Bettina Gr{\"u}n and Gertraud Malsiner-Walli and Sylvia Fr{\"u}hwirth-Schnatter",

year = "2021",

month = feb,

day = "11",

language = "English",

publisher = "R Foundation for Statistical Computing",

address = "United States",

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A2 - Greve, Jan

A2 - Grün, Bettina

A2 - Malsiner-Walli, Gertraud

A2 - Frühwirth-Schnatter, Sylvia

PY - 2021/2/11

Y1 - 2021/2/11

N2 - Computes implicitly induced quantities from prior/hyperparameter specifications of three Mixtures of Finite Mixtures models: Dirichlet Process Mixtures (DPMs; Escobar and West (1995) ), Static Mixtures of Finite Mixtures (Static MFMs; Miller and Harrison (2018) ), and Dynamic Mixtures of Finite Mixtures (Dynamic MFMs; Frühwirth-Schnatter, Malsiner-Walli and Grün (2020) ). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) ) as well as the package vignette.

AB - Computes implicitly induced quantities from prior/hyperparameter specifications of three Mixtures of Finite Mixtures models: Dirichlet Process Mixtures (DPMs; Escobar and West (1995) ), Static Mixtures of Finite Mixtures (Static MFMs; Miller and Harrison (2018) ), and Dynamic Mixtures of Finite Mixtures (Dynamic MFMs; Frühwirth-Schnatter, Malsiner-Walli and Grün (2020) ). For methodological details, please refer to Greve, Grün, Malsiner-Walli and Frühwirth-Schnatter (2020) ) as well as the package vignette.

UR - https://CRAN.R-project.org/package=fipp

M3 - Software

PB - R Foundation for Statistical Computing

ER -

fipp: Induced Priors in Bayesian Mixture Models

Abstract

Austrian Classification of Fields of Science and Technology (ÖFOS)

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