hmltm.px: Calculates perp dist detection probability p(x).

In david-borchers/hmltm: Line transect estimation with hidden Markov availability models

Calculates perp dist detection probability p(x).

Description

Calculates perp dist detection probability p(x).

Usage

hmltm.px(
  x,
  pars,
  hfun,
  models = list(y = NULL, x = NULL),
  cov = NULL,
  survey.pars,
  hmm.pars,
  type = "response",
  ally = TRUE
)

Arguments

x	perpendicular distances at which to evaluate function.
pars	starting parameter values, as for est.hmltm.
hfun	detection hazard function name; same as argument FUN of est.hmltm.
models	detection hazard covariate models, as for est.hmltm.
cov	covariate matrix with each row corresponding to an observation. Must contain columns with variables appearing in models, and named accordingly, as well as column of perpendicular distance, named "x". (Perpendicular distances only used if to.x is TRUE.)
survey.pars	survey parameters, as for est.hmltm.
hmm.pars	availability hmm parameters, as for est.hmltm. Must have elements $Et and $Sigma.Et
type	if "link", parameter vector pars is assumed to be on the link scale, else on the natural scale
ally	If TRUE calculates detection probability at all forward distances, else at zero.

david-borchers/hmltm documentation built on Oct. 29, 2023, 9:07 p.m.