Results 261 to 270 of about 12,789,297 (308)
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Biometrika, 1969
This paper gives a self-contained analysis of a mixed model for regressions. The model differs from the ordinary covariance model as well as from the error components regression model considered by Mundlak (1963), Wallace & Hussain (1969) and some other writers.
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This paper gives a self-contained analysis of a mixed model for regressions. The model differs from the ordinary covariance model as well as from the error components regression model considered by Mundlak (1963), Wallace & Hussain (1969) and some other writers.
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Computational Statistics, 2003
The author gives a brief overview of general design mixed models (MM) with emphasis on the use of the mixed model framework to fit and make inference for a wide variety of semiparametric regression models. It is demonstrated that the MM approach to smoothing has several advantages.
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The author gives a brief overview of general design mixed models (MM) with emphasis on the use of the mixed model framework to fit and make inference for a wide variety of semiparametric regression models. It is demonstrated that the MM approach to smoothing has several advantages.
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A Mixed Model of Optimal Saving
2016This paper proposes a mixed model to study a consumer’s optimal saving in the presence of two types of risk: income risk and background risk. In this model the income risk is represented by a fuzzy number and the background risk by a random variable.
Irina Georgescu +2 more
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Functional Mixed Effects Models
Biometrics, 2002Summary.In this article, a new class of functional models in which smoothing splines are used to model fixed effects as well as random effects is introduced. The linear mixed effects models are extended to non‐parametric mixed effects models by introducing functional random effects, which are modeled as realizations of zero‐mean stochastic processes ...
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2010
The Context-Tree-Weighting algorithm is an example of an computationally efficient way to compute a Bayesian mixture of context-tree models. In this talk I will present several classes of models for which efficient mixing procedures exist. After briefly touching the binary CTW method I will discuss an efficient way to determine the MAP context tree ...
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The Context-Tree-Weighting algorithm is an example of an computationally efficient way to compute a Bayesian mixture of context-tree models. In this talk I will present several classes of models for which efficient mixing procedures exist. After briefly touching the binary CTW method I will discuss an efficient way to determine the MAP context tree ...
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Unproven Methods of Cancer Treatment: Coley's Mixed Toxins
Ca-A Cancer Journal for Clinicians, 1965Harry Grabstald
exaly
Computing Maximum Likelihood Estimates for the Mixed A.O.V. Model Using the W Transformation
Technometrics, 1973H O Hartley
exaly