predictStationary: Predict stationary state probabilities

In moveHMM: Animal Movement Modelling using Hidden Markov Models

Predict stationary state probabilities

Description

Predict stationary state probabilities

Usage

predictStationary(
  m,
  newData,
  beta = m$mle$beta,
  returnCI = FALSE,
  alpha = 0.95
)

Arguments

m	Fitted moveHMM object, as returned by fitHMM
newData	Data frame with columns for the covariates
beta	Optional matrix of regression coefficients for the transition probability model. By default, uses estimates in m.
returnCI	Logical indicating whether confidence intervals should be returned. Default: FALSE.
alpha	Confidence level if returnCI = TRUE. Default: 0.95, i.e., 95% confidence intervals.

Value

List with elements 'mle', 'lci', and 'uci' (the last two only if returnCI = TRUE). Each element is a matrix of stationary state probabilities with one row for each row of newData and one column for each state.

moveHMM documentation built on May 31, 2023, 6:13 p.m.