n2w: Scaling function: natural to working parameters.

In moveHMM: Animal Movement Modelling using Hidden Markov Models

Scaling function: natural to working parameters.

Description

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

Usage

n2w(par, bounds, beta, delta = NULL, nbStates, estAngleMean)

Arguments

par	Vector of state-dependent distributions parameters.
bounds	Matrix with 2 columns and as many rows as there are elements in par. Each row contains the lower and upper bound for the correponding parameter.
beta	Matrix of regression coefficients for the transition probabilities.
delta	Initial distribution. Default: NULL ; if the initial distribution is not estimated.
nbStates	The number of states of the HMM.
estAngleMean	TRUE if the angle mean is estimated, FALSE otherwise.

Value

A vector of unconstrained parameters.

Examples

## Not run: 
nbStates <- 3
par <- c(0.001,0.999,0.5,0.001,1500.3,7.1)
bounds <- matrix(c(0,1, # bounds for first parameter
                   0,1, # bounds for second parameter
                   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)

# vector of working parameters
wpar <- n2w(par=par,bounds=bounds,beta=beta,delta=delta,nbStates=nbStates,
           estAngleMean=FALSE)

## End(Not run)

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