smsld_tmb: Fitting function for Multistate CJS live-dead models with TMB

Description

A function for computing MLEs for a Multi-state Cormack-Jolly-Seber open population capture-recapture 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.

Usage

smsld_tmb(
  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,
  re = FALSE,
  compile = FALSE,
  extra.args = "",
  clean = FALSE,
  getreals = FALSE,
  useHess = FALSE,
  savef = FALSE,
  ...
)

Value

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 optim; if 0 optim thinks it converged
count: optim results of number of function evaluations
reals: dataframe of data and real S and p estimates for each animal-occasion excluding those that occurred before release
vcv: var-cov matrix of betas if hessian=TRUE was set

Arguments

x: processed dataframe created by process.data
ddl: list of simplified dataframes for design data; created by call to make.design.data
dml: list of design matrices created by create.dm from formula and design data
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 re-rerun with an additional call to cjs when using autoscale or re-starting with initial values. It is stored with returned model object.
parameters: equivalent to model.parameters in crm
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 optim
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: non-zero 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 re-compilation 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
savef: if TRUE, save optimization function in model for reporting
...: not currently used

Author

Jeff Laak

Details

It is easiest to call msld_tmb through the function crm. Details are explained there.