w2n: Scaling function: working to natural parameters

In moveHMM: Animal Movement Modelling using Hidden Markov Models

Scaling function: working to natural parameters

Description

Scales each parameter from the set of real numbers, back to its natural interval. Used during the optimization of the log-likelihood.

Usage

w2n(wpar, bounds, parSize, nbStates, nbCovs, estAngleMean, stationary)

Arguments

wpar	Vector of state-dependent distributions unconstrained parameters.
bounds	Matrix with 2 columns and as many rows as there are elements in wpar. Each row contains the lower and upper bound for the correponding parameter.
parSize	Vector of two values: number of parameters of the step length distribution, number of parameters of the turning angle distribution.
nbStates	The number of states of the HMM.
nbCovs	The number of covariates.
estAngleMean	TRUE if the angle mean is estimated, FALSE otherwise.
stationary	FALSE if there are covariates. If TRUE, the initial distribution is considered equal to the stationary distribution. Default: FALSE.

Value

A list of:

stepPar	Matrix of natural parameters of the step length distribution
anglePar	Matrix of natural parameters of the turning angle distribution
beta	Matrix of regression coefficients of the transition probabilities
delta	Initial distribution

Examples

## Not run: 
nbStates <- 3
nbCovs <- 2
par <- c(0.001,0.999,0.5,0.001,1500.3,7.1)
parSize <- c(1,1)
bounds <- matrix(c(0,1,0,1,0,1,
                   0,Inf,0,Inf,0,Inf),
                 byrow=TRUE,ncol=2)
beta <- matrix(rnorm(18),ncol=6,nrow=3)
delta <- c(0.6,0.3,0.1)
wpar <- n2w(par,bounds,beta,delta,nbStates,FALSE)
print(w2n(wpar,bounds,parSize,nbStates,nbCovs,estAngleMean=FALSE,stationary=FALSE))

## End(Not run)

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