extract.LL.unmarked

an object of 'unmarkedFit' class resulting from the fit of 'occu',
  'occuRN', 'colext', 'pcount', or 'pcountOpen'.

This function extracts the log-likelihood from an object of various
'unmarkedFit' classes.

models

This package includes functions to create model selection
        tables based on Akaike's information criterion (AIC) and the
        second-order AIC (AICc), as well as their quasi-likelihood
        counterparts (QAIC, QAICc).  Tables are printed with delta AIC
        and Akaike weights.  The package also features functions to
        conduct classic model averaging (multimodel inference) for a
        given parameter of interest or predicted values, as well as a
        shrinkage version of model averaging parameter estimates.
        Other handy functions enable the computation of relative
        variable importance, evidence ratios, and confidence sets for
        the best model.  The present version works with linear models
        ('lm' class), generalized linear models ('glm' class), linear
        models fit by generalized least squares ('gls' class), linear
        mixed models ('lme' class), generalized linear mixed models
        ('mer' class), multinomial and ordinal logistic regressions
        ('multinom' and 'polr' classes), and nonlinear models ('nls'
        class).  The package also supports various models incorporating
        detection probabilities such as single-season occupancy models
        ('unmarkedFitOccu' class), multiple-season occupancy models
        ('unmarkedFitColExt' class), single-season heterogeneity models
        ('unmarkedFitOccuRN' class), and single-season and
        multiple-season N-mixture models for repeated counts
        ('unmarkedFitPCount' and 'unmarkedFitPCO' classes,
        respectively).

extract.LL.unmarked: Extract Log-Likelihood of Model

Description

Usage

Arguments

Value

Details

See Also

Examples