Results 271 to 280 of about 178,886 (297)

Estimation of covariance parameters in kriging via restricted maximum likelihood

Mathematical Geology, 1991
In kriging, parametric approaches to covariance (or variogram) estimation require that unknown parameters be inferred from a single realization of the underlying random field. An approach to such an estimation problem is to assume the field to be Gaussian and iteratively minimize a (restricted) negative loglikelihood over the parameter space.
Dietrich, C. R., Osborne, M. R.
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Restricted maximum likelihood estimation under Eisenhart model Ill

Statistica Neerlandica, 1991
For a balanced two‐way mixed model, the maximum likelihood (ML) and restricted ML (REML) estimators of the variance components were obtained and compared under the non‐negativity requirements of the variance components by Lee and Kapadia (1984). In this note, for a mixed (random blocks) incomplete block model, explicit forms for the REML estimators of ...
Lee, K. R., Kapadia, C. H.
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Restricted Maximum Likelihood Estimation for Parameters of the Social Relations Model

Psychometrika, 2016
In many areas of research, the round-robin design is used to study interpersonal judgments and behaviors. The resulting data are analyzed with the social relations model (SRM), whereby almost all previously published studies have used ANOVA-based methods or multilevel-based methods to obtain SRM parameter estimates. In this article, the SRM is embedded
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Maximum likelihood and restricted maximum likelihood estimators as functions of ordinary least squares and analysis of variance estimators

Communications in Statistics - Theory and Methods, 1996
For a class of linear models with normally distributed error structures, necessary and sufficient conditions are given where the maximum likelihood (ML) and restricted maximum likelihood (REML) estimators of the parameters are functions of the ordinary least squares (OLS) and analysis of variance (ANOVA) estimators.
Barry Kurt Moser, Melinda H. McCann
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Restricted maximum likelihood estimation of joint mean‐covariance models

Canadian Journal of Statistics, 2012
AbstractThe class of joint mean‐covariance models uses the modified Cholesky decomposition of the within subject covariance matrix in order to arrive to an unconstrained, statistically meaningful reparameterisation. The new parameterisation of the covariance matrix has two sets of parameters that separately describe the variances and correlations. Thus,
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A RESTRICTED MAXIMUM LIKELIHOOD PROCEDURE FOR ESTIMATING THE VARIANCE FUNCTION OF AN IMMUNOASSAY

Australian & New Zealand Journal of Statistics, 2008
SummaryRestricted maximum likelihood (REML) is a procedure for estimating a variance function in a heteroscedastic linear model. Although REML has been extended to non‐linear models, the case in which the data are dominated by replicated observations with unknown values of the independent variable of interest, such as the concentration of a substance ...
O'Malley, A. James, Smith, Murray H., Sadler, William A.   +2 more
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Asymptotic Optimality of Restricted Maximum Likelihood Estimates for the Mixed Model

Calcutta Statistical Association Bulletin, 1979
In this paper we study the asymptotic optimality of the restricted maximum likelihood estimates of variance components in the mixed model of analysis of variance. Using conceptual design sequences of Miller (1977), under slightly stronger conditions, we show that the restricted maximum likelihood estimates are not only asymptotically normal, but also ...
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Maximum Likelihood Estimation Under Order Restrictions by the Prior Feedback Method

Journal of the American Statistical Association, 1996
Abstract Algorithms for deriving isotonic regression estimators in order-restricted linear models and more generally restricted maximum likelihood estimators are usually quite dependent on the particular problem considered. We propose here an optimization method based on a sequence of formal Bayes estimates whose variances converge to zero. This method,
Christian P. Robert, J. T. Gene Hwang
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An improved approximation to the precision of fixed effects from restricted maximum likelihood

Computational Statistics & Data Analysis, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Michael G. Kenward, James H. Roger
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Restricted maximum likelihood estimation of a common mean and the Mandel–Paule algorithm

Journal of Statistical Planning and Inference, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rukhin, Andrew L., Biggerstaff, Brad J., Vangel, Mark G.   +2 more
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