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Extraction of Components with Structured Variance [PDF]
The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006 We 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.
Erkki Oja, Harri Valpola, Alexander Ilin
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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 ...
Hans-Peter Müller, Eija Könönen
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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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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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A User's Guide to Principal Components.
, 1991Preface.Introduction.1. Getting Started.2. PCA with More Than Two Variables.3. Scaling of Data.4. Inferential Procedures.5. Putting It All Together-Hearing Loss I.6. Operations with Group Data.7.
J. Lastovicka, J. E. Jackson
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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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Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
, 1977Recent developments promise to increase greatly the popularity of maximum likelihood (ml) as a technique for estimating variance components. Patterson and Thompson (1971) proposed a restricted maximum likelihood (reml) approach which takes into account ...
D. Harville
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Reliable computing in estimation of variance components.
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2008The purpose of this study is to present guidelines in selection of statistical and computing algorithms for variance components estimation when computing involves software packages.
I. Misztal
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Mixed Models and Variance Components
1987Traditionally, linear models have been divided into three categories: fixed effects models, random effects models, and mixed models. The categorization depends on whether the β vector in Y = Xβ + e is fixed, random, or has both fixed and random elements.
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On identifiability of (co)variance components in animal models with competition effects.
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, 2008There is an increased interest in estimating the (co)variance components of additive animal models with direct and competition effects (AMC). However, some attempts to estimate the dispersion parameters in different animal species faced problems of ...
R. Cantet, E. P. Cappa
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