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A Note on Variances in the Components of Variance Model
The American Statistician, 1971In a components of variance model the variance of individual observations and of various averages of observations are shown to be dependent upon the design-that is, upon the sampling scheme. For example, using the usual notation, for the nested random model yij = iA+ ri + eJ(i), i = 1, 2, . . . I, and j = 1 2, ... J, Var(ysi) = [(I 1)J/(IJ 1)]a2 + a2e.
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Extraction of Components with Structured Variance
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006We present a method for exploratory data analysis of large spatiotemporal data sets such as global longtime climate measurements, extending our previous work on semiblind source separation of climate data. The method seeks fast changing components whose variances exhibit slow behavior with specific temporal structure.
Alexander Ilin, Harri Valpola, Erkki Oja
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Variance components of gingival thickness
Journal of Periodontal Research, 2005Objectives: Distinct periodontal phenotypes have been identified by cluster analysis, which is an explorative method with very low external validity. The aim of the present study was to investigate variance components of facial gingival thickness in young adults with mild gingivitis.Material and methods: Thirty‐three non‐smoking females, 18–23 years ...
H P, Müller, E, Könönen
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1981
So far, the examples of analysis-of-variance problems that we have considered all fall within the scope of what we call the ‘fixed effects’ analysis, or the ‘model I’ situation. In these problems the questions being asked are questions about contrasts of sets of means.
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So far, the examples of analysis-of-variance problems that we have considered all fall within the scope of what we call the ‘fixed effects’ analysis, or the ‘model I’ situation. In these problems the questions being asked are questions about contrasts of sets of means.
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Nonlinear Regression With Variance Components
Journal of the American Statistical Association, 1992Abstract The nonlinear model with variance components, which combines a nonlinear model for the mean with additive random effects, is applicable to split-plot and nested experiments. We propose two methods of estimation for the parameters of the nonlinear model for the mean: (1) estimated generalized least squares (EGLS), and (2) maximum likelihood ...
Marcia L. Gumpertz, Sastry G. Pantula
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Exact Tests for Variance Components
Biometrics, 1996Summary: \textit{J. Öfversten} [ibid. 49, No. 1, 45-57 (1993; Zbl 0771.62053)] presented two kinds of exact \(F\)-tests for variance components in unbalanced mixed linear models. Specifically, methods were developed for models with one random factor, nested classifications, and models with interaction between random factors.
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Statistical Analysis of Negative Variance Components in the Estimation of Variance Components
2008This paper analyzes the problem of negative variance components in the estimation of variance components from the statistical point of view, based on two kinds of estimators of variance components. Our analysis shows that too low relative accuracy and too large errors of the estimated variance components in comparison with the variance component itself
B. Gao, S. Li, W. Li, S. Li, X. Wang
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Variance Components and Disconnected Data
Biometrics, 1978Summary It has been suggested that disconnected data pose problems in variance component estimation and that the dlscarding of certain sections of a data set is a possible solution. In contrast, it is shown in this paper that estimators of variance components can be derived from disconnected data by applying Henderson's Method III without modification.
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