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mrds (version 2.3.0)

flnl: Log-likelihood computation for distance sampling data

Description

For a specific set of parameter values, it computes and returns the negative log-likelihood for the distance sampling likelihood for distances that are unbinned, binned and a mixture of both. The function flnl is the function minimized using optim from within ddf.ds.

Usage

flnl(fpar, ddfobj, misc.options, fitting = "all")

Value

negative log-likelihood value at the parameter values specified in fpar

Arguments

fpar

parameter values for detection function at which negative log-likelihood should be evaluated

ddfobj

distance sampling object

misc.options

a list with the following elements: width transect width; int.range the integration range for observations; showit 0 to 3 controls level debug output; integral.numeric if TRUE integral is computed numerically rather than analytically; point is this a point transect?

fitting

character "key" if only fitting key function parameters, "adjust" if fitting adjustment parameters or "all" to fit both

Author

Jeff Laake, David L Miller

Details

Most of the computation is in flpt.lnl in which the negative log-likelihood is computed for each observation. flnl is a wrapper that optionally outputs intermediate results and sums the individual log-likelihood values.

flnl is the main routine that manipulates the parameters using getpar to handle fitting of key, adjustment or all of the parameters. It then calls flpt.lnl to do the actual computation of the likelihood. The probability density function for point counts is fr and for line transects is fx. fx=g(x)/mu (where g(x) is the detection function); whereas, f(r)=r*g(r)/mu where mu in both cases is the normalizing constant. Both functions are in source code file for link{detfct} and are called from distpdf and the integral calculations are made with integratepdf.

See Also

flt.var, detfct