Robust finite mixture regression for heterogeneous targets
Sign Up to like & getrecommendations! Published in 2018 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-018-0564-z
Abstract: Finite Mixture Regression (FMR) refers to the mixture modeling scheme which learns multiple regression models from the training data set. Each of them is in charge of a subset. FMR is an effective scheme for… read more here.
Keywords: regression; mixture regression; regression heterogeneous; finite mixture ... See more keywords
Semiparametric Mixture of Regression Models Under Unimodal Error Distribution
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DOI: 10.1007/s42519-020-00113-8
Abstract: A semiparametric model has the advantage of being more robust than a parametric model and more efficient than a nonparametric model. In this paper, a semiparametric regression mixture model, in which the regression coefficients are… read more here.
Keywords: regression; semiparametric mixture; model; mixture regression ... See more keywords
Adaptive design of experiments based on Gaussian mixture regression
Sign Up to like & getrecommendations! Published in 2021 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.104226
Abstract: Abstract In the design of molecules, materials, and processes, adaptive design of experiments (ADoE) is conducted to minimize the number of experiments. Although Bayesian optimization (BO) is an effective tool, BO merely selects a candidate… read more here.
Keywords: number; mixture regression; gaussian mixture; design experiments ... See more keywords
Mixture regression for longitudinal data based on joint mean-covariance model
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Multivariate Analysis"
DOI: 10.1016/j.jmva.2022.104956
Abstract: In the process of modeling longitudinal data, we focus on the case that the studied population is comprised of different groups of individuals and individuals within the same group share the similar kind of mean… read more here.
Keywords: mixture regression; mixture; covariance; model ... See more keywords
Parameter estimation for mixtures of skew Laplace normal distributions and application in mixture regression modeling
Sign Up to like & getrecommendations! Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2016.1252400
Abstract: ABSTRACT In this article, we propose mixtures of skew Laplace normal (SLN) distributions to model both skewness and heavy-tailedness in the neous data set as an alternative to mixtures of skew Student-t-normal (STN) distributions. We… read more here.
Keywords: skew laplace; laplace normal; mixture regression; mixtures skew ... See more keywords
Bayesian finite mixture of regression analysis for cancer based on histopathological imaging-environment interactions.
Sign Up to like & getrecommendations! Published in 2023 at "Biostatistics"
DOI: 10.1093/biostatistics/kxab038
Abstract: Cancer is a heterogeneous disease. Finite mixture of regression (FMR)-as an important heterogeneity analysis technique when an outcome variable is present-has been extensively employed in cancer research, revealing important differences in the associations between a… read more here.
Keywords: finite mixture; mixture regression; histopathological imaging; analysis ... See more keywords
Variational Bayesian Gaussian Mixture Regression for Soft Sensing Key Variables in Non-Gaussian Industrial Processes
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Control Systems Technology"
DOI: 10.1109/tcst.2016.2576999
Abstract: In this brief, a variational Bayesian Gaussian mixture regression (VBGMR) method is developed for soft sensing key quality-related variables in a non-Gaussian industrial process. Traditional Gaussian mixture regression (GMR) is based on Gaussian mixture model… read more here.
Keywords: variational bayesian; mixture regression; gaussian mixture; mixture ... See more keywords