Extract regression coefficients, variances, etc. from
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coef(object, ...) confint(object, ...) Sigma(object, ...) vcoef(object, ...) vcoef0(object, ...) ## S4 method for signature 'dlMod' Sigma(object, scaled = TRUE, ...) ## S4 method for signature 'dlMod' vcoef0(object, scaled = TRUE, ...) ## S4 method for signature 'dlMod' vcoef(object, scaled = TRUE, ...) ## S3 method for class 'dlMod' coef(object, scaled = TRUE, ...) ## S3 method for class 'dlMod' confint(object, parm, level = 0.95, scaled = TRUE, coef = TRUE, ...)
an integer or character index to subset parameters
the desired confidence level
Other typical methods like
sigma, etc. are handled via inheritance
from lme4 classes.
If the argument
scaled = TRUE, parameter estimates are scaled
by the areas between radii and summed so that they can be interpreted
as the estimate up to a given radius (e.g. see the dlmBE
follows the format of
lme4::coef.merMod to return the sums of fixed
and random effects for each level and grouping factor
returns confidence intervals for regression
returns the regression coefficient covariance matrix.
Row and column indices are in the same order as
vcoef (see below)
returns vectorized coefficients from the fitted
model. Fixed effects come before distributed lag coefficients, which
come before other random effects coefficients. For example, if
β is a vector of fixed effects; θ_1 and
θ_2 are vectors of (separately penalized) DL coefficients;
and b_1, b_2, ... are additional random
effects vectors for groups 1, 2, ..., then
vcoef will return the (named) vector
(β', θ_1', θ_2', b_1', b_2', ...)'.
vcoef0 returns the same coefficient vector
but without names (and is slightly faster).
All of these functions return
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