A function for computing MLEs for a specified Cormack-Jolly-Seber open
population capture-recapture model for processed dataframe x with
user specified formulas in parameters that create list of design
matrices dml. This function can be called directly but is most easily
called from crm that sets up needed arguments.
cjs_admb(
x,
ddl,
dml,
model_data = NULL,
parameters,
accumulate = TRUE,
initial = NULL,
method,
hessian = FALSE,
debug = FALSE,
chunk_size = 1e+07,
refit,
itnmax = NULL,
control = NULL,
scale,
use.admb = FALSE,
crossed = TRUE,
compile = FALSE,
extra.args = NULL,
reml,
clean = TRUE,
...
)The resulting value of the function is a list with the class of
crm,cjs such that the generic functions print and coef can be used.
Elements are 1) beta: named vector of parameter estimatesm 2) lnl: -2*log
likelihood, 3) AIC: lnl + 2* number of parameters, 4) convergence: result from optim; if 0 optim thinks it
converged, 5) count:optim results of number of function
evaluations, 6) reals: dataframe of data and real Phi and p estimates for
each animal-occasion excluding those that occurred before release, 7) vcv:var-cov matrix of betas if hessian=TRUE was set.
processed dataframe created by process.data
list of dataframes for design data; created by call to
make.design.data
list of design matrices created by create.dm from
formula and design data
a list of all the relevant data for fitting the model including imat, Phi.dm,p.dm,Phi.fixed,p.fixed, and time.intervals. It is used to save values and avoid accumulation again if the model was re-rerun with an additional call to cjs when using autoscale or re-starting with initial values. It is stored with returned model object.
equivalent to model.parameters in crm
if TRUE will accumulate capture histories with common value and with a common design matrix for Phi and p to speed up execution
list of initial values for parameters if desired; if each is a named vector from previous run it will match to columns with same name
method to use for optimization; see optim
if TRUE will compute and return the hessian
if TRUE will print out information for each iteration
specifies amount of memory to use in accumulating capture histories; amount used is 8*chunk_size/1e6 MB (default 80MB)
non-zero entry to refit
maximum number of iterations
control string for optimization functions
vector of scale values for parameters
if TRUE creates data file for admbcjs.tpl and runs admb optimizer
if TRUE it uses cjs.tpl or cjs_reml.tpl if reml=FALSE or TRUE respectively; if FALSE, then it uses cjsre which can use Gauss-Hermite integration
if TRUE forces re-compilation of tpl file
optional character string that is passed to admb if use.admb==TRUE
if set to TRUE uses cjs_reml if crossed
if TRUE, deletes the tpl and executable files for amdb if use.admb=T
any remaining arguments are passed to additional parameters
passed to optim or cjs.lnl
Jeff Laake
It is easiest to call cjs through the function crm.
Details are explained there.
Be cautious with this function at present. It does not include many checks
to make sure values like fixed values will remain in the specified range of
the data. Normally this would not be a big problem but because
cjs.lnl calls an external FORTRAN subroutine, if it gets a
subscript out of bounds, it will cause R to terminate. So make sure to save
your workspace frequently if you use this function in its current
implementation.
Pledger, S., K. H. Pollock, et al. (2003). Open capture-recapture models with heterogeneity: I. Cormack-Jolly-Seber model. Biometrics 59(4):786-794.