Usage
randomizedBlock(formula, random, weights=NULL, only.varcomp=FALSE, data=list(), subset=NULL, contrasts=NULL, tol=1e-6, maxit=50, trace=FALSE)
randomizedBlockFit(y, X, Z, w=NULL, only.varcomp=FALSE, tol=1e-6, maxit=50, trace=FALSE)
Arguments
formula
formula specifying the fixed model.
random
vector or factor specifying the blocks corresponding to random effects.
weights
optional vector of prior weights.
only.varcomp
logical value, if TRUE
computation of standard errors and fixed effect coefficients will be skipped
data
an optional data frame containing the variables in the model.
subset
an optional vector specifying a subset of observations to be used in the fitting process.
contrasts
an optional list. See the contrasts.arg
argument of model.matrix.default
.
tol
small positive numeric tolerance, passed to glmgam.fit
maxit
maximum number of iterations permitted, passed to glmgam.fit
trace
logical value, passed to glmgam.fit
. If TRUE
then working estimates will be printed at each iteration.
X
numeric design matrix for fixed model
Z
numeric design matrix for random effects
w
optional vector of prior weights