F.cr.model.matrix(capture, survival, nan, ns)
ivar
and tvar
functions to work. Normally, nan
=
number of rows in capture history matrix. No default value. ns
= number of
columns in the capture history matrix. nrow(x)
where x
is a 2-D matrix in the model (i.e.,
number of animals). NS = ncol(x)
(i.e., number of capture occasions).
NX = number of matrices specified in the model. IX = 1 if an intercept is included,
0 otherwise. The j-th covariate matrix specified in the model can be accessed directly with
capX[, IX+1+(NS*(j-1)):(NS*j) ]
. nrow(x)
where y
is a 2-D matrix in the model (i.e.,
number of animals). NS = ncol(y)
(i.e., number of capture occasions).
NY = number of matrices specified in the model. IY = 1 if an intercept is included,
0 otherwise. The j-th covariate matrix specified in the model can be accessed directly with
capY[, IY+1+(NS*(j-1)):(NS*j) ]
. This routine uses a call to eval
with a model frame, and calls the
R internal model.matrix
to
resolve the matrices in the formula. All matrices specified in the models
should be in the current scope and accessible to both eval
and model.matrix
.
This routine calls F.3d.model.matrix
twice. F.3d.model.matrix
does all the work.
F.cjs.estim
, model.matrix
, eval
# Synthetic example with 10 animals and 5 occasions
nan <- 10
ns <- 5
sex <- matrix( as.numeric(runif( nan ) > 0.5), nrow=nan, ncol=ns )
x <- matrix( runif( nan*ns ) , nrow=nan, ncol=ns )
F.cr.model.matrix( capture= ~ sex + x, survival= ~ -1 + x, nan, ns )
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