A weighted least-squares approach to clusterwise regression
type: Item
instance of: scholarly article
title: A weighted least-squares approach to clusterwise regression
zbMATH Open document ID: 1477.62163
published in: AStA. Advances in Statistical Analysis
publication date: 2020-10-12T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62J05
zbMATH DE Number: 7259159
zbMATH Keywords: clustering
zbMATH Keywords: clusterwise regression
zbMATH Keywords: finite mixture model
zbMATH Keywords: linear regression
zbMATH Keywords: robust regression
zbMATH Keywords: weighted regression
zbMATH Keywords: bootstrap test
author: Rainer Schlittgen
cites work: bootlib
cites work: Q5600597
cites work: Q5340435
cites work: Q4370586
cites work: A maximum likelihood methodology for clusterwise linear regression
cites work: Finite mixture and Markov switching models.
cites work: Fitting finite mixtures of generalized linear regressions in \textsf{R}
cites work: Fixed point clusters for linear regression: Computation and comparison
cites work: Clusters, outliers, and regression: Fixed point clusters
cites work: A mathematical programming approach to clusterwise regression model and its extensions
cites work: Clusterwise linear regression
cites work: A fast algorithm for clusterwise linear regression
cites work: Algorithm: Clusterwise linear least absolute deviations regression
cites work: Estimating the Propagation Rate of a Viral Infection of Potato Plants via Mixtures of Regressions
describes a project that uses: bootlib
describes a project that uses: fpc
describes a project that uses: fields
describes a project that uses: R
describes a project that uses: flexmix
describes a project that uses: Algorithm 39
MaRDI profile type: Publication
full work available at URL: s10182-011-0155-4
OpenAlex ID: W2079879667
DOI: 10.1007/S10182-011-0155-4
description: scientific article; zbMATH DE number 7259159