nLogLike_rcpp: Negative log-likelihood

Description

Computation of the negative log-likelihood (forward algorithm - written in C++)

Usage

nLogLike_rcpp(
  nbStates,
  covs,
  data,
  dataNames,
  dist,
  Par,
  aInd,
  zeroInflation,
  oneInflation,
  stationary,
  knownStates,
  betaRef,
  mixtures
)

Value

Negative log-likelihood

Arguments

nbStates: Number of states,
covs: Covariates,
data: A momentuHMMData object of the observations,
dataNames: Character vector containing the names of the data streams,
dist: Named list indicating the probability distributions of the data streams.
Par: Named list containing the state-dependent parameters of the data streams, matrix of regression coefficients for the transition probabilities ('beta'), and initial distribution ('delta').
aInd: Vector of indices of the rows at which the data switches to another animal
zeroInflation: Named list of logicals indicating whether the probability distributions of the data streams are zero-inflated.
oneInflation: Named list of logicals indicating whether the probability distributions of the data streams are one-inflated.
stationary: false if there are time-varying covariates in formula or any covariates in formulaDelta. If true, the initial distribution is considered equal to the stationary distribution. Default: false.
knownStates: Vector of values of the state process which are known prior to fitting the model (if any). Default: NULL (states are not known). This should be a vector with length the number of rows of 'data'; each element should either be an integer (the value of the known states) or NA if the state is not known.
betaRef: Indices of reference elements for t.p.m. multinomial logit link.
mixtures: Number of mixtures for the state transition probabilities