Description Usage Arguments Details Value Author(s) References
A function for computing MLEs for a Multistate CormackJollySeber open
population capturerecapture with dead recoveries 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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25  msld_tmb(
x,
ddl,
fullddl,
dml,
model_data = NULL,
parameters,
accumulate = TRUE,
initial = NULL,
method,
hessian = FALSE,
debug = FALSE,
chunk_size = 1e+07,
refit,
itnmax = NULL,
control = NULL,
scale,
re = FALSE,
compile = FALSE,
extra.args = "",
clean = FALSE,
getreals = FALSE,
useHess = FALSE,
...
)

x 
processed dataframe created by process.data 
ddl 
list of simplified dataframes for design data; created by call to

fullddl 
list of complete dataframes for design data; created by call to

dml 
list of design matrices created by 
model_data 
a list of all the relevant data for fitting the model including imat, S.dm,r.dm,p.dm,Psi.dm,S.fixed,r.fixed,p.fixed,Psi.fixed and time.intervals. It is used to save values and avoid accumulation again if the model was rererun with an additional call to cjs when using autoscale or restarting with initial values. It is stored with returned model object. 
parameters 
equivalent to 
accumulate 
if TRUE will accumulate capture histories with common value and with a common design matrix for all parameters speed up execution 
initial 
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 
method to use for optimization; see 
hessian 
if TRUE will compute and return the hessian 
debug 
if TRUE will print out information for each iteration 
chunk_size 
specifies amount of memory to use in accumulating capture histories; amount used is 8*chunk_size/1e6 MB (default 80MB) 
refit 
nonzero entry to refit 
itnmax 
maximum number of iterations 
control 
control string for optimization functions 
scale 
vector of scale values for parameters 
re 
if TRUE creates random effect model admbcjsre.tpl and runs admb optimizer 
compile 
if TRUE forces recompilation of tpl file 
extra.args 
optional character string that is passed to tmb 
clean 
if TRUE, deletes the dll and recompiles 
getreals 
if TRUE, compute real values and std errors for TMB models; may want to set as FALSE until model selection is complete 
useHess 
if TRUE, the TMB hessian function is used for optimization; using hessian is typically slower with many parameters but can result in a better solution 
... 
not currently used 
It is easiest to call msld_tmb
through the function crm
.
Details are explained there.
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.
beta 
named vector of parameter estimates 
lnl 
2*log likelihood 
AIC 
lnl + 2* number of parameters 
convergence 
result from 
count 

reals 
dataframe of data and real S and p estimates for each animaloccasion excluding those that occurred before release 
vcv 
varcov matrix of betas if hessian=TRUE was set 
Jeff Laak
Ford, J. H., M. V. Bravington, and J. Robbins. 2012. Incorporating individual variability into markrecapture models. Methods in Ecology and Evolution 3:10471054.
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