| deprecated {statmod} | R Documentation |
These functions are provided for compatibility with older versions of R only, and may be defunct as soon as the next release.
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)
The arguments formula, weights, data, subset and contrasts have the same meaning as in lm.
The arguments y, X and w have the same meaning as in lm.wfit.
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. |
y |
numeric response vector |
X |
numeric design matrix for fixed model |
Z |
numeric design matrix for random effects |
w |
optional vector of prior weights |
randomizedBlock and randomizedBlockFit have been renamed to mixedModel2 and mixedModel2Fit respectively.