hmltm.stat: Calculates various statistics from model.

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

Calculates various statistics from model.

Description

Calculates various statistics from model.

Usage

hmltm.stat(
  stat,
  b,
  hfun,
  models = list(y = NULL, x = NULL),
  cov = NULL,
  survey.pars,
  hmm.pars,
  nx = 100,
  type = "link"
)

Arguments

stat	name of statistic to calculate. Valid statistics are "p0" for estimated probability at perpendicular distance zero, "p" for mean estimated detection probability over all perpendicular distances, "invp" for the inverse of mean estimated detection probability over all perpendicular distances, "esw" for estimated effective strip width, and "invesw" for estimated inverse of effective strip width.
b	detection hazard parameter vector.
hfun	detection hazard name (character).
models	covariate models (see est.hmltm for details).
cov	covariate values.
survey.pars	survey parameter specification (see est.hmltm for details).
hmm.pars	hidden Markov model parameter specification (see est.hmltm for details).
nx	number of points at which to evaluate detection function in perpendicular distance dimension.
type	if "link", assumes that parameter vector b is on link scale, else assumes it is on natural scale.

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