Residual maximum likelihood estimation (REML) is often preferred to maximum likelihood estimation as a method of estimating covariance parameters in linear models because it takes account of the loss of degrees of freedom in estimating the mean and produces unbiased estimating equations for the variance parameters. In this note it is shown that REML has an exact conditional likelihood interpret...

A unified frequency domain cross-validation (FDCV) method is proposed to obtain a heteroskedasticity and autocorrelation consistent (HAC) standard error. This enables model/tuning parameter selection across both parametric nonparametric spectral estimators simultaneously. The candidate class for this approach consists of restricted maximum likelihood-based (REML) autoregressive lag-weights with...

This paper considers double generalized linear models, which allow the mean and dispersion to be modelled simultaneously in a generalized linear model context. Estimation of the dispersion parameters is based on a χ1 approximation to the unit deviances, and the accuracy of the saddle-point approximation which underlies this is discussed. Approximate REML methods are developed for estimation of ...

Plant breeders traditionally have estimated genotypic and phenotypic correlations between traits using the method of moments on the basis of a multivariate analysis of variance (MANOVA). Drawbacks of using the method of moments to estimate variance and covariance components include the possibility of obtaining estimates outside of parameter bounds, reduced estimation efficiency, and ignorance o...

95 Estimating heritability, the proportion of variation in phenotypic values due to (additive) genetic effects, is an important subject matter to plant and animal breeders alike. In most applications there is not an analytic expression for the restricted maximum likelihood (REML) estimator of heritability since it is obtained via an iterative procedure. The focus of this paper is to find a clos...

Crossed random effects models can simultaneously take into account both fixed and of the subjects stimuli when observations are nested within combinations stimuli. Unfortunately, maximum likelihood estimation (MLE) restricted (REML) often encounter convergence problems, which in turn lead researchers to fit simpler that yield invalid statistical inferences. On other hand, if structure is too si...

IMPORTANCE Narcolepsy, a disorder associated with HLA-DQB1*06:02 and caused by hypocretin (orexin) deficiency, is diagnosed using the Multiple Sleep Latency Test (MSLT) following nocturnal polysomnography (NPSG). In many patients, a short rapid eye movement sleep latency (REML) during the NPSG is also observed but not used diagnostically. OBJECTIVE To determine diagnostic accuracy and clinica...

A set of FORTRAN programs to implement a multiple-trait Gibbs sampling algorithm for (co)variance component inference in animal models (MTGSAM) was developed. The MTGSAM programs are available to the public. The programs support models with correlated genetic effects and arbitrary numbers of covariates, fixed effects, and independent random effects for each trait. Any combination of missing tra...

The performance of Restricted Maximum Likelihood (REML) and Bayesian Markov Chain approaches to study gene expression trends across time were compared. Measurements of performance included the consistent identi cation of cDNAs differentially expressed and not differentially expressed and estimates of changes in cDNA expression across age was investigated. The normalized observations were assume...