A Selective Overview and Comparison of Robust Mixture Regression Estimators

Yu, Chun; Yao, Weixin; Yang, Guangren

doi:10.1111/insr.12349

Title: A Selective Overview and Comparison of Robust Mixture Regression Estimators

Authors:

Yu, Chun ^[1]; Yao, Weixin ^[2];

^[3]

School of Statistics Jiangxi University of Finance and Economics Nanchang 330013 China
Department of Statistics University of California Riverside 92521 CA USA
Department of Statistics, School of Economics Jinan University Guangzhou 510632 China

Publication Date:: 2019-11-29

Sponsoring Org.:: USDOE

OSTI Identifier:: 1576654

Grant/Contract Number:: 10006272

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: International Statistical Review

Additional Journal Information:: Journal Name: International Statistical Review Journal Volume: 88 Journal Issue: 1; Journal ID: ISSN 0306-7734

Publisher:: Wiley-Blackwell

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Yu, Chun, Yao, Weixin, and Yang, Guangren. A Selective Overview and Comparison of Robust Mixture Regression Estimators.  United Kingdom: N. p., 2019. 
Web.  doi:10.1111/insr.12349.

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                    Yu, Chun, Yao, Weixin, & Yang, Guangren. A Selective Overview and Comparison of Robust Mixture Regression Estimators.  United Kingdom.  https://doi.org/10.1111/insr.12349

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                    Yu, Chun, Yao, Weixin, and Yang, Guangren. Fri .  
"A Selective Overview and Comparison of Robust Mixture Regression Estimators".  United Kingdom.  https://doi.org/10.1111/insr.12349.

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@article{osti_1576654,

  title        = {A Selective Overview and Comparison of Robust Mixture Regression Estimators},

  author       = {Yu, Chun and Yao, Weixin and Yang, Guangren},

  abstractNote = {},

  doi          = {10.1111/insr.12349},

  journal      = {International Statistical Review},

  number       = 1,

  volume       = 88,

  place        = {United Kingdom},

  year         = {2019},

  month        = {11}

}

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Works referenced in this record:

Mixture Models, Robustness, and the Weighted Likelihood Methodology
journal, June 2000

Markatou, Marianthi
Biometrics, Vol. 56, Issue 2
DOI: 10.1111/j.0006-341X.2000.00483.x

A profile likelihood method for normal mixture with unequal variance
journal, July 2010

Yao, Weixin
Journal of Statistical Planning and Inference, Vol. 140, Issue 7
DOI: 10.1016/j.jspi.2010.02.004

Consistent Estimation of a Mixing Distribution
journal, September 1992

Leroux, Brian G.
The Annals of Statistics, Vol. 20, Issue 3
DOI: 10.1214/aos/1176348772

Dealing with label switching in mixture models
journal, November 2000

Stephens, Matthew
Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 62, Issue 4
DOI: 10.1111/1467-9868.00265

Bayesian Mixture Labeling by Highest Posterior Density
journal, June 2009

Yao, Weixin; Lindsay, Bruce G.
Journal of the American Statistical Association, Vol. 104, Issue 486
DOI: 10.1198/jasa.2009.0237

The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
journal, January 1994

Liu, Chuanhai; Rubin, Donald B.
Biometrika, Vol. 81, Issue 4
DOI: 10.1093/biomet/81.4.633

Robust Estimation of Mixture Complexity
journal, December 2006

Woo, Mi-Ja; Sriram, T. N.
Journal of the American Statistical Association, Vol. 101, Issue 476
DOI: 10.1198/016214506000000555

Computational and Inferential Difficulties with Mixture Posterior Distributions
journal, September 2000

Celeux, Gilles; Hurn, Merrilee; Robert, Christian P.
Journal of the American Statistical Association, Vol. 95, Issue 451
DOI: 10.1080/01621459.2000.10474285

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
journal, December 2001

Fan, Jianqing; Li, Runze
Journal of the American Statistical Association, Vol. 96, Issue 456
DOI: 10.1198/016214501753382273

Outlier detection and robust mixture modeling using nonconvex penalized likelihood
journal, September 2015

Yu, Chun; Chen, Kun; Yao, Weixin
Journal of Statistical Planning and Inference, Vol. 164
DOI: 10.1016/j.jspi.2015.03.003

Robust linear clustering
journal, January 2009

García-Escudero, L. A.; Gordaliza, A.; San Martín, R.
Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 71, Issue 1
DOI: 10.1111/j.1467-9868.2008.00682.x

The robust EM-type algorithms for log-concave mixtures of regression models
journal, July 2017

Hu, Hao; Yao, Weixin; Wu, Yichao
Computational Statistics & Data Analysis, Vol. 111
DOI: 10.1016/j.csda.2017.01.004

Ideal spatial adaptation by wavelet shrinkage
journal, September 1994

Donoho, David L.; Johnstone, Iain M.
Biometrika, Vol. 81, Issue 3
DOI: 10.1093/biomet/81.3.425

Model based labeling for mixture models
journal, January 2011

Yao, Weixin
Statistics and Computing, Vol. 22, Issue 2
DOI: 10.1007/s11222-010-9226-8

Robust Mixture of Linear Regression Models
journal, September 2012

Bashir, Shaheena; Carter, E. M.
Communications in Statistics - Theory and Methods, Vol. 41, Issue 18
DOI: 10.1080/03610926.2011.558655

Robust mixture regression model fitting by Laplace distribution
journal, March 2014

Song, Weixing; Yao, Weixin; Xing, Yanru
Computational Statistics & Data Analysis, Vol. 71
DOI: 10.1016/j.csda.2013.06.022

Robust mixture modeling based on scale mixtures of skew-normal distributions
journal, December 2010

Basso, Rodrigo M.; Lachos, Víctor H.; Cabral, Celso Rômulo Barbosa
Computational Statistics & Data Analysis, Vol. 54, Issue 12
DOI: 10.1016/j.csda.2009.09.031

A Markov model for switching regressions
journal, March 1973

Goldfeld, Stephen M.; Quandt, Richard E.
Journal of Econometrics, Vol. 1, Issue 1
DOI: 10.1016/0304-4076(73)90002-X

Testing the Order of a Finite Mixture
journal, September 2010

Li, Pengfei; Chen, Jiahua
Journal of the American Statistical Association, Vol. 105, Issue 491
DOI: 10.1198/jasa.2010.tm09032

Robust clusterwise linear regression through trimming
journal, December 2010

García-Escudero, L. A.; Gordaliza, A.; Mayo-Iscar, A.
Computational Statistics & Data Analysis, Vol. 54, Issue 12
DOI: 10.1016/j.csda.2009.07.002

Consistent estimation of mixture complexity
journal, October 2001

Marchette, David J.; Priebe, Carey E.; James, Lancelot F.
The Annals of Statistics, Vol. 29, Issue 5
DOI: 10.1214/aos/1013203454

Robust mixture regression modeling using the least trimmed squares (LTS)-estimation method
journal, July 2017

Doğru, Fatma Zehra; Arslan, Olcay
Communications in Statistics - Simulation and Computation, Vol. 47, Issue 7
DOI: 10.1080/03610918.2017.1341528

Robust fitting of mixtures using the trimmed likelihood estimator
journal, September 2007

Neykov, N.; Filzmoser, P.; Dimova, R.
Computational Statistics & Data Analysis, Vol. 52, Issue 1
DOI: 10.1016/j.csda.2006.12.024

Determining the number of components in mixtures of linear models
journal, November 2001

Hawkins, Dollena S.; Allen, David M.; Stromberg, Arnold J.
Computational Statistics & Data Analysis, Vol. 38, Issue 1
DOI: 10.1016/S0167-9473(01)00017-2

Robust mixture regression using the <mml:math altimg="si171.gif" display="inline" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd" xmlns:sa="http://www.elsevier.com/xml/common/struct-aff/dtd"><mml:mi>t</mml:mi></mml:math>-distribution
journal, March 2014

Yao, Weixin; Wei, Yan; Yu, Chun
Computational Statistics & Data Analysis, Vol. 71
DOI: 10.1016/j.csda.2013.07.019

FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters
journal, January 2008

Grün, Bettina; Leisch, Friedrich
Journal of Statistical Software, Vol. 28, Issue 4
DOI: 10.18637/jss.v028.i04

Nearly unbiased variable selection under minimax concave penalty
journal, April 2010

Zhang, Cun-Hui
The Annals of Statistics, Vol. 38, Issue 2
DOI: 10.1214/09-AOS729

A new method for robust mixture regression
journal, December 2016

Yu, Chun; Yao, Weixin; Chen, Kun
Canadian Journal of Statistics, Vol. 45, Issue 1
DOI: 10.1002/cjs.11310

LogConcDEAD : An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density
journal, January 2009

Cule, Madeleine; Gramacy, Robert; Samworth, Richard
Journal of Statistical Software, Vol. 29, Issue 2
DOI: 10.18637/jss.v029.i02

Least Median of Squares Regression
journal, December 1984

Rousseeuw, Peter J.
Journal of the American Statistical Association, Vol. 79, Issue 388
DOI: 10.1080/01621459.1984.10477105

Identifiablity of Models for Clusterwise Linear Regression
journal, July 2000

Hennig, C.
Journal of Classification, Vol. 17, Issue 2
DOI: 10.1007/s003570000022

Choosing initial values for the EM algorithm for finite mixtures
journal, January 2003

Karlis, Dimitris; Xekalaki, Evdokia
Computational Statistics & Data Analysis, Vol. 41, Issue 3-4
DOI: 10.1016/S0167-9473(02)00177-9

Wavelets in statistics: A review
journal, August 1997

Antoniadis, A.
Journal of the Italian Statistical Society, Vol. 6, Issue 2
DOI: 10.1007/BF03178905

Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model
journal, June 2017

Punzo, Antonio; McNicholas, Paul. D.
Journal of Classification, Vol. 34, Issue 2
DOI: 10.1007/s00357-017-9234-x

Maximum likelihood estimation via the ECM algorithm: A general framework
journal, January 1993

Meng, Xiao-Li; Rubin, Donald B.
Biometrika, Vol. 80, Issue 2
DOI: 10.1093/biomet/80.2.267

A constrained em algorithm for univariate normal mixtures
journal, January 1986

Hathaway, Richard J.
Journal of Statistical Computation and Simulation, Vol. 23, Issue 3
DOI: 10.1080/00949658608810872

A Constrained Formulation of Maximum-Likelihood Estimation for Normal Mixture Distributions
journal, June 1985

Hathaway, Richard J.
The Annals of Statistics, Vol. 13, Issue 2
DOI: 10.1214/aos/1176349557

Penalized minimum-distance estimates in finite mixture models
journal, June 1996

Chen, Jiahua; Kalbfleisch, J. D.
Canadian Journal of Statistics, Vol. 24, Issue 2
DOI: 10.2307/3315623

Robust estimation of mixtures of regressions with random covariates, via trimming and constraints
journal, February 2016

García-Escudero, L. A.; Gordaliza, A.; Greselin, F.
Statistics and Computing, Vol. 27, Issue 2
DOI: 10.1007/s11222-016-9628-3

regression models: approximation and maximum likelihood estimation
journal, June 1999

Tanner, Martin A.; Jiang, Wenxin
The Annals of Statistics, Vol. 27, Issue 3
DOI: 10.1214/aos/1018031265

Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
journal, January 2003

Biernacki, Christophe; Celeux, Gilles; Govaert, Gérard
Computational Statistics & Data Analysis, Vol. 41, Issue 3-4
DOI: 10.1016/S0167-9473(02)00163-9

Hypothesis test for normal mixture models: The EM approach
journal, October 2009

Chen, Jiahua; Li, Pengfei
The Annals of Statistics, Vol. 37, Issue 5A
DOI: 10.1214/08-AOS651

Robust estimation of the number of components for mixtures of linear regression models
journal, August 2015

Li, Meng; Xiang, Sijia; Yao, Weixin
Computational Statistics, Vol. 31, Issue 4
DOI: 10.1007/s00180-015-0610-x

Robust fitting of mixture regression models
journal, July 2012

Bai, Xiuqin; Yao, Weixin; Boyer, John E.
Computational Statistics & Data Analysis, Vol. 56, Issue 7
DOI: 10.1016/j.csda.2012.01.016

Maximum likelihood estimation of the mixture of log-concave densities
journal, September 2016

Hu, Hao; Wu, Yichao; Yao, Weixin
Computational Statistics & Data Analysis, Vol. 101
DOI: 10.1016/j.csda.2016.03.002

Order Selection in Finite Mixture Models With a Nonsmooth Penalty
journal, March 2009

Chen, Jiahua; Khalili, Abbas
Journal of the American Statistical Association, Vol. 104, Issue 485
DOI: 10.1198/jasa.2009.0103

Robust mixture regression modeling based on scale mixtures of skew-normal distributions
journal, July 2015

Zeller, Camila B.; Cabral, Celso R. B.; Lachos, Víctor H.
TEST, Vol. 25, Issue 2
DOI: 10.1007/s11749-015-0460-4

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Title: A Selective Overview and Comparison of Robust Mixture Regression Estimators

Citation Formats

Mixture Models, Robustness, and the Weighted Likelihood Methodology journal, June 2000

A profile likelihood method for normal mixture with unequal variance journal, July 2010

Consistent Estimation of a Mixing Distribution journal, September 1992

Dealing with label switching in mixture models journal, November 2000

Bayesian Mixture Labeling by Highest Posterior Density journal, June 2009

The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence journal, January 1994

Robust Estimation of Mixture Complexity journal, December 2006

Computational and Inferential Difficulties with Mixture Posterior Distributions journal, September 2000

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties journal, December 2001

Outlier detection and robust mixture modeling using nonconvex penalized likelihood journal, September 2015

Robust linear clustering journal, January 2009

The robust EM-type algorithms for log-concave mixtures of regression models journal, July 2017

Ideal spatial adaptation by wavelet shrinkage journal, September 1994

Model based labeling for mixture models journal, January 2011

Robust Mixture of Linear Regression Models journal, September 2012

Robust mixture regression model fitting by Laplace distribution journal, March 2014

Robust mixture modeling based on scale mixtures of skew-normal distributions journal, December 2010

A Markov model for switching regressions journal, March 1973

Testing the Order of a Finite Mixture journal, September 2010

Robust clusterwise linear regression through trimming journal, December 2010

Consistent estimation of mixture complexity journal, October 2001

Robust mixture regression modeling using the least trimmed squares (LTS)-estimation method journal, July 2017

Robust fitting of mixtures using the trimmed likelihood estimator journal, September 2007

Determining the number of components in mixtures of linear models journal, November 2001

FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters journal, January 2008

Nearly unbiased variable selection under minimax concave penalty journal, April 2010

A new method for robust mixture regression journal, December 2016

LogConcDEAD : An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density journal, January 2009

Least Median of Squares Regression journal, December 1984

Identifiablity of Models for Clusterwise Linear Regression journal, July 2000

Choosing initial values for the EM algorithm for finite mixtures journal, January 2003

Wavelets in statistics: A review journal, August 1997

Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model journal, June 2017

Maximum likelihood estimation via the ECM algorithm: A general framework journal, January 1993

A constrained em algorithm for univariate normal mixtures journal, January 1986

A Constrained Formulation of Maximum-Likelihood Estimation for Normal Mixture Distributions journal, June 1985

Penalized minimum-distance estimates in finite mixture models journal, June 1996

Robust estimation of mixtures of regressions with random covariates, via trimming and constraints journal, February 2016

regression models: approximation and maximum likelihood estimation journal, June 1999

Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models journal, January 2003

Hypothesis test for normal mixture models: The EM approach journal, October 2009

Robust estimation of the number of components for mixtures of linear regression models journal, August 2015

Robust fitting of mixture regression models journal, July 2012

Maximum likelihood estimation of the mixture of log-concave densities journal, September 2016

Order Selection in Finite Mixture Models With a Nonsmooth Penalty journal, March 2009

Robust mixture regression modeling based on scale mixtures of skew-normal distributions journal, July 2015

Mixture Models, Robustness, and the Weighted Likelihood Methodology
journal, June 2000

A profile likelihood method for normal mixture with unequal variance
journal, July 2010

Consistent Estimation of a Mixing Distribution
journal, September 1992

Dealing with label switching in mixture models
journal, November 2000

Bayesian Mixture Labeling by Highest Posterior Density
journal, June 2009

The ECME algorithm: A simple extension of EM and ECM with faster monotone convergence
journal, January 1994

Robust Estimation of Mixture Complexity
journal, December 2006

Computational and Inferential Difficulties with Mixture Posterior Distributions
journal, September 2000

Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
journal, December 2001

Outlier detection and robust mixture modeling using nonconvex penalized likelihood
journal, September 2015

Robust linear clustering
journal, January 2009

The robust EM-type algorithms for log-concave mixtures of regression models
journal, July 2017

Ideal spatial adaptation by wavelet shrinkage
journal, September 1994

Model based labeling for mixture models
journal, January 2011

Robust Mixture of Linear Regression Models
journal, September 2012

Robust mixture regression model fitting by Laplace distribution
journal, March 2014

Robust mixture modeling based on scale mixtures of skew-normal distributions
journal, December 2010

A Markov model for switching regressions
journal, March 1973

Testing the Order of a Finite Mixture
journal, September 2010

Robust clusterwise linear regression through trimming
journal, December 2010

Consistent estimation of mixture complexity
journal, October 2001

Robust mixture regression modeling using the least trimmed squares (LTS)-estimation method
journal, July 2017

Robust fitting of mixtures using the trimmed likelihood estimator
journal, September 2007

Determining the number of components in mixtures of linear models
journal, November 2001

FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters
journal, January 2008

Nearly unbiased variable selection under minimax concave penalty
journal, April 2010

A new method for robust mixture regression
journal, December 2016

LogConcDEAD : An R Package for Maximum Likelihood Estimation of a Multivariate Log-Concave Density
journal, January 2009

Least Median of Squares Regression
journal, December 1984

Identifiablity of Models for Clusterwise Linear Regression
journal, July 2000

Choosing initial values for the EM algorithm for finite mixtures
journal, January 2003

Wavelets in statistics: A review
journal, August 1997

Robust Clustering in Regression Analysis via the Contaminated Gaussian Cluster-Weighted Model
journal, June 2017

Maximum likelihood estimation via the ECM algorithm: A general framework
journal, January 1993

A constrained em algorithm for univariate normal mixtures
journal, January 1986

A Constrained Formulation of Maximum-Likelihood Estimation for Normal Mixture Distributions
journal, June 1985

Penalized minimum-distance estimates in finite mixture models
journal, June 1996

Robust estimation of mixtures of regressions with random covariates, via trimming and constraints
journal, February 2016

regression models: approximation and maximum likelihood estimation
journal, June 1999

Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models
journal, January 2003

Hypothesis test for normal mixture models: The EM approach
journal, October 2009

Robust estimation of the number of components for mixtures of linear regression models
journal, August 2015

Robust fitting of mixture regression models
journal, July 2012

Maximum likelihood estimation of the mixture of log-concave densities
journal, September 2016

Order Selection in Finite Mixture Models With a Nonsmooth Penalty
journal, March 2009

Robust mixture regression modeling based on scale mixtures of skew-normal distributions
journal, July 2015