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A direct derivation of the REML likelihood function

Statistical Papers, 2007
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Lynn LaMotte
exaly   +4 more sources

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Reml estimation for repeated measures analysis

Journal of Statistical Computation and Simulation, 1991
Models for repeated measures or growth curves consist of a mean response plus error and the errors are usually correlated. Both maximum likelihood and residual maximum likelihood (REML) estimators of a regression model with dependent errors are derived for cases in which the variance matrix of the error model admits a convenient Cholesky factorisation.
C A Mcgilchrist
exaly   +3 more sources

Regularized REML for Estimation in Heteroscedastic Regression Models

Advances in Intelligent and Soft Computing, 2011
In this paper, we propose a regularized restricted maximum likelihood(REML) method for simultaneous variable selection in heteroscedastic regression models. Under certain regularity conditions, we establish the consistency and asymptotic normality of the resulting estimator.
Dengke Xu, Zhongzhan Zhang, Xu Dengke
exaly   +2 more sources

Bayesian and REML analysis of twinning and fertility in Thoroughbred horses

Livestock Science, 2012
Abstract Horses have low fertility, which affects profitability of breeding. Additional economic loss is generated by various complications accompanying twin pregnancies which are particularly prevalent in Thoroughbred horses. Therefore it is important to identify environmental and genetic factors influencing this trait.
S Mucha, A Wolc, T Szwaczkowski
exaly   +2 more sources

Mapping soil salinity in the Yangtze delta: REML and universal kriging (E-BLUP) revisited

Geoderma, 2015
Rice farmers in China need accurate maps of soil salinity to make rational decisions for management. Modern sensors such as the Geonics EM38 conductivity meter, which records the apparent electrical conductivity, ECa, allied to geostatistics to convert ...
Zhou Shi
exaly   +2 more sources