Returns two model matrices for capturerecapture modeling. Both are in the form of (giant) 2D matrices.
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F.cr.model.matrix(capture, survival, nan, ns)

capture 
Formula for the capture model. Must be a formula object with no response, then ~, followed by the names of 2D arrays of covariates to fit in the capture model. For example: capture = ~ age + sex, where age and sex are matrices. 
survival 
Formula for the survival model. Must be a formula object with no response, then ~, followed by the names of 2D arrays of covariates to fit in the survival model. For example: capture = ~ age + sex, where age and sex are matrices. 
nan 
Number of individuals in the model. This is necessary for the

ns 
Number of sampling occasions. Normally, 
This routine is intended to be called internally by model fitting routines of MRA. General users should never have to call this routine.
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.
A list containing the following components:
capX 
A NAN by IX+(NX*NS) matrix containing covariate values for the capture
model. Matrices specified in the model are column appended together.
NAN = 
surX 
A NAN by IY+(NY*NS) matrix containing covariate values for the survival
model. Matrices specified in the model are column appended together.
NAN = 
n.cap.covars 
Number of matrices specified in the capture model (NX above). 
n.sur.covars 
Number of matrices specified in the survival model (NY above). 
cap.intercept 
TRUE or FALSE depending on whether an intercept was included in the capture model 
sur.intercept 
TRUE or FALSE depending on whether an intercept was included in the survival model 
cap.vars 
Vector of names for the NX covariates in the capture model. 
sur.vars 
Vector of names for the NY covariates in the survival model. 
Trent McDonald, WESTINC, tmcdonald@westinc.com
F.cjs.estim
, model.matrix
, eval
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