Multiobjective model selection for non-linear regression techniques

2010 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2010.5649190 ◽

2010 ◽

Author(s):

Luca Pasolli ◽

Claudia Notarnicola ◽

Lorenzo Bruzzone

Keyword(s):

Model Selection ◽

Linear Regression ◽

Regression Techniques ◽

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Consistency of a class of information criteria for model selection in non-linear regression

Communication in Statistics- Theory and Methods ◽

10.1080/03610929108830587 ◽

1991 ◽

Vol 20 (5-6) ◽

pp. 1619-1629 ◽

Author(s):

Dominique Haughton

Keyword(s):

Model Selection ◽

Linear Regression ◽

Information Criteria ◽

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Model selection for high-dimensional linear regression with dependent observations

The Annals of Statistics ◽

10.1214/19-aos1872 ◽

2020 ◽

Vol 48 (4) ◽

pp. 1959-1980

Author(s):

Ching-Kang Ing

Keyword(s):

Model Selection ◽

Linear Regression ◽

High Dimensional ◽

Dependent Observations ◽

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Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures

Brazilian Journal of Probability and Statistics ◽

10.1214/18-bjps417 ◽

2020 ◽

Vol 34 (1) ◽

pp. 51-70 ◽

Author(s):

Flávio B. Gonçalves ◽

Marcos O. Prates ◽

Victor Hugo Lachos

Keyword(s):

Model Selection ◽

Linear Regression ◽

Bayesian Model ◽

Bayesian Model Selection ◽

Finite Mixtures ◽

Selection For ◽

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Budget constrained model selection for multiple linear regression

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2021.1991956 ◽

2021 ◽

pp. 1-13

Author(s):

Jingying Zhang ◽

Ronald L. Rardin ◽

Justin R. Chimka

Keyword(s):

Model Selection ◽

Linear Regression ◽

Multiple Linear Regression ◽

Constrained Model ◽

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Model Selection in Harmonic Non-Linear Regression

Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach ◽

10.1007/978-94-011-0866-9_12 ◽

1994 ◽

pp. 187-207

Author(s):

Dominique Haughton ◽

Jonathan Haughton ◽

Alan Izenman

Keyword(s):

Model Selection ◽

Linear Regression ◽

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Model Selection for Non-Linear Dynamic Models

SSRN Electronic Journal ◽

10.2139/ssrn.201749 ◽

2000 ◽

Author(s):

Massimiliano Giuseppe Marcellino

Keyword(s):

Model Selection ◽

Dynamic Models ◽

Linear Dynamic ◽

Selection For ◽

Linear Dynamic Models

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An Approach to Identify New Insecticides AgainstMyzus Persicae. In silicoStudy Based on Linear and Non‐linear Regression Techniques

Molecular Informatics ◽

10.1002/minf.201800119 ◽

2019 ◽

Vol 38 (8-9) ◽

pp. 1800119 ◽

Author(s):

Luminita Crisan ◽

Ana Borota ◽

Takahiro Suzuki ◽

Simona Funar‐Timofei

Keyword(s):

Linear Regression ◽

Regression Techniques

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Non-linear signal evaluation with linear regression techniques for redundant signals

Sensors and Actuators B Chemical ◽

10.1016/0925-4005(95)85179-8 ◽

1995 ◽

Vol 25 (1-3) ◽

pp. 805-807 ◽

Author(s):

Gerhard Niebling ◽

Rudolf Mu¨ller

Keyword(s):

Linear Regression ◽

Signal Evaluation ◽

Regression Techniques ◽

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Non-linear regression techniques in data analysis

Medical Informatics ◽

10.3109/14639238509010848 ◽

1985 ◽

Vol 10 (2) ◽

pp. 137-142 ◽

Author(s):

Vincent J. Cunningham

Keyword(s):

Data Analysis ◽

Linear Regression ◽

Regression Techniques

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Relative Cost Based Model Selection for Sparse High-Dimensional Linear Regression Models

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp40776.2020.9054045 ◽

2020 ◽

Author(s):

Prakash B. Gohain ◽

Magnus Jansson

Keyword(s):

Model Selection ◽

Linear Regression ◽

Regression Models ◽

High Dimensional ◽

Relative Cost ◽

Linear Regression Models ◽

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