Wavelet-Generalized Least Squares: A New BLU Estimator of Linear Regression Models with 1/f Errors

10.1006/nimg.2001.0955 ◽

2002 ◽

Vol 15 (1) ◽

pp. 217-232 ◽

Author(s):

M.J. Fadili ◽

E.T. Bullmore

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Generalized Least Squares ◽

Linear Regression Models

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Asymptotic normality of the time‐domain generalized least squares estimator for linear regression models

Stat ◽

10.1002/sta4.248 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Hien D. Nguyen

Keyword(s):

Linear Regression ◽

Asymptotic Normality ◽

Least Squares ◽

Time Domain ◽

Regression Models ◽

Generalized Least Squares ◽

Least Squares Estimator ◽

Linear Regression Models ◽

Generalized Least Squares Estimator ◽

The Time Domain

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An asymptotic theory for semiparametric generalized least squares estimation in partially linear regression models

Statistical Papers ◽

10.1007/bf02762967 ◽

2005 ◽

Vol 46 (2) ◽

pp. 173-193 ◽

Author(s):

Gemai Chen ◽

Jinhong You

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Asymptotic Theory ◽

Generalized Least Squares ◽

Least Squares Estimation ◽

Linear Regression Models ◽

Partially Linear ◽

Generalized Least Squares Estimation

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Semiparametric generalized least squares estimation in partially linear regression models with correlated errors

Journal of Statistical Planning and Inference ◽

10.1016/j.jspi.2005.10.001 ◽

2007 ◽

Vol 137 (1) ◽

pp. 117-132 ◽

Author(s):

Jinhong You ◽

Gemai Chen

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Generalized Least Squares ◽

Least Squares Estimation ◽

Correlated Errors ◽

Linear Regression Models ◽

Partially Linear ◽

Generalized Least Squares Estimation

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Strong consistency of least-squares estimation in linear regression models with vague concepts

Journal of Multivariate Analysis ◽

10.1016/j.jmva.2005.04.009 ◽

2006 ◽

Vol 97 (3) ◽

pp. 633-654 ◽

Author(s):

Volker Krätschmer

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Strong Consistency ◽

Least Squares Estimation ◽

Linear Regression Models

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Jackknifing type weighted least squares estimators in partially linear regression models

Statistics & Probability Letters ◽

10.1016/s0167-7152(02)00242-0 ◽

2002 ◽

Vol 60 (1) ◽

pp. 17-31

Author(s):

Jinhong You ◽

Xiaoqian Sun ◽

Wan-kai Pang ◽

Ping-kei Leung

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Weighted Least Squares ◽

Linear Regression Models ◽

Partially Linear ◽

Least Squares Estimators

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The construction of fuzzy least squares estimators in fuzzy linear regression models

Expert Systems with Applications ◽

10.1016/j.eswa.2011.04.131 ◽

2011 ◽

Author(s):

Hsien-Chung Wu

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Linear Regression Models ◽

Fuzzy Linear Regression ◽

Least Squares Estimators

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Pitman Closeness Comparison of Least Squares and Stein-Rule Estimators in Linear Regression Models with Non-Normal Disturbances

American Journal of Mathematical and Management Sciences ◽

10.1080/01966324.2001.10737539 ◽

2001 ◽

Vol 21 (1-2) ◽

pp. 89-100 ◽

Author(s):

Shalabh

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Linear Regression Models ◽

Pitman Closeness

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Instrumental Variables Two-Stage Least Squares (2SLS) vs. Maximum Likelihood Structural Equation Modeling of Causal Effects in Linear Regression Models

Structural Equation Modeling A Multidisciplinary Journal ◽

10.1080/10705511.2019.1607740 ◽

2019 ◽

Vol 26 (6) ◽

pp. 876-892 ◽

Author(s):

Alberto Maydeu-Olivares ◽

Dexin Shi ◽

Yves Rosseel

Keyword(s):

Structural Equation Modeling ◽

Maximum Likelihood ◽

Linear Regression ◽

Least Squares ◽

Instrumental Variables ◽

Regression Models ◽

Structural Equation ◽

Causal Effects ◽

Equation Modeling ◽

Linear Regression Models

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On Consistency of Estimators in Simple Linear Regression Models

Calcutta Statistical Association Bulletin ◽

10.1177/0008068320020310 ◽

2002 ◽

Vol 53 (3-4) ◽

pp. 261-264 ◽

Author(s):

Anindya Roy ◽

Thomas I. Seidman

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Sufficient Condition ◽

Simple Linear Regression ◽

Linear Regression Models ◽

Least Squares Estimators

We derive a property of real sequences which can be used to provide a natural sufficient condition for the consistency of the least squares estimators of slope and intercept for a simple linear regression models.

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An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

Journal of Geodesy ◽

10.1007/s00190-017-1062-6 ◽

2017 ◽

Vol 92 (3) ◽

pp. 271-297 ◽

Author(s):

Boris Kargoll ◽

Mohammad Omidalizarandi ◽

Ina Loth ◽

Jens-André Paffenholz ◽

Hamza Alkhatib

Keyword(s):

Linear Regression ◽

Least Squares ◽

Regression Models ◽

Iteratively Reweighted Least Squares ◽

Linear Regression Models ◽

Adjustment Of Parameters ◽

Least Squares Approach

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