Extract variance and correlation components
VarCorr(x, sigma = 1, ...) ## S3 method for class 'lme' VarCorr(x, sigma = x$sigma, rdig = 3, ...) ## S3 method for class 'pdMat' VarCorr(x, sigma = 1, rdig = 3, ...) ## S3 method for class 'pdBlocked' VarCorr(x, sigma = 1, rdig = 3, ...)
x |
a fitted model object, usually an object inheriting from
class |
sigma |
an optional numeric value used as a multiplier for the
standard deviations. The default is |
rdig |
an optional integer value specifying the number of digits
used to represent correlation estimates. Default is |
... |
further optional arguments passed to other methods (none for the methods documented here). |
a matrix with the estimated variances, standard deviations, and
correlations for the random effects. The first two columns, named
Variance
and StdDev
, give, respectively, the variance
and the standard deviations. If there are correlation components in
the random effects model, the third column, named Corr
,
and the remaining unnamed columns give the estimated correlations
among random effects within the same level of grouping. The
within-group error variance and standard deviation are included as
the last row in the matrix.
José Pinheiro and Douglas Bates bates@stat.wisc.edu
Pinheiro, J.C., and Bates, D.M. (2000) Mixed-Effects Models in S and S-PLUS, Springer, esp. pp. 100, 461.
fm1 <- lme(distance ~ age, data = Orthodont, random = ~age) VarCorr(fm1)
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