Extracts the lnl, AICc, npar, beta and real estimates and returns a list of
these results for inclusion in the mark object. The elements
beta and real are dataframes with fields estimate,se,lcl,ucl.
This function was written for internal use and is called by
run.mark.model. It is documented here for more advanced users
that might want to modify the code or adapt for their own use.
extract.mark.output(out, model, adjust, realvcv = FALSE, vcvfile)result: list of extracted output elements
-2xLog-likelihood
Difference between saturated model and lnl
Number of model parameters
Small-sample corrected AIC value using npar and n
Number of model parameters as reported by MARK if npar was adjusted
Small-sample corrected AIC value using npar.unadjusted and n
Effective sample size reported by MARK; used in AICc calculation
Dataframe of beta parameters with fields: estimate, se, lcl, ucl
Dataframe of real parameters with fields: estimate, se, lcl, ucl
variance-covariance matrix for derived parameters if any
dataframe with fields Variable and Value which are the covariate names and value used for real parameter estimates in the MARK output
indices of beta parameters that are non-estimable or at a boundary
variance-covariance matrix for real parameters (simplified) if realvcv=TRUE
output from MARK analysis (model$output)
mark model object
if TRUE, adjusts number of parameters (npar) to number of columns in design matrix, modifies AIC and records both
if TRUE the vcv matrix of the real parameters is extracted and stored in the model results
name of vcv file output
Jeff Laake
run.mark.model