Titlebook: Linear Models for Multivariate, Time Series, and Spatial Data; Ronald Christensen Textbook 19911st edition Springer-Verlag New York 1991 C

拱形面包

Linear Models for Spatial Data: Kriging,high-quality copper are more likely to occur near other high-quality deposits. The levels of lead contamination in the soil around a smelter are likely to be correlated. The prevalence of AIDS viewed geographically is correlated. There are innumerable situations in which data are collected at variou

B-cell

Springer-Verlag New York 1991

OTTER

Cholagogue

脫毛

Metastasis

羅盤

Time Domain Analysis,. , .., ..,... In the traditional approach, the variance components in the spectral approximation will be nonzero, thus there is little chance of developing a parsimonious model. (The model with measurement error is more promising in this regard.)

LAP

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Multivariate Linear Models,987, Section XIII.1) and multivariate one-way analysis of variance. Principal components are user-constructed variables which are best linear predictors (cf. Christensen, 1987, Section VI.3) of the original data. Factor analysis has ties to both multivariate linear models and principal components.

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