Prediction with a flexible finite mixture-of-regressions

DOI10.1016/j.csda.2018.01.012OpenAlexW2793872545WikidataQ57583386 ScholiaQ57583386MaRDI QIDQ1727867

Ilmari Ahonen, Denis Larocque, Jaakko Nevalainen

Publication date: 21 February 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://trepo.tuni.fi/handle/10024/105214

zbMATH Keywords

bootstrappenalizationprediction intervalsrandom forestfinite mixture regression

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Generalized linear models (logistic models) (62J12) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Clusterwise elastic-net regression based on a combined information criterion, Editorial for the 4th special issue on advances in mixture models, Prediction of the Nash through penalized mixture of logistic regression models

Uses Software

• R
• flexmix
• snowfall
• glmnet
• randomForest
• BayesDA
• ISLR
• nor1mix
• SPMoE
• fmrlasso

Cites Work

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• Variable Selection in Finite Mixture of Regression Models
• An Introduction to Statistical Learning
• A New Approach to Estimating Switching Regressions
• Random forests