fHMM_model: Constructor of a model object

Description

This function constructs an object of class fHMM_model, which contains details about the fitted (hierarchical) Hidden Markov model.

Usage

fHMM_model(
  data,
  estimate,
  nlm_output,
  estimation_time,
  ll,
  lls,
  gradient,
  inverse_fisher,
  decoding
)
# S3 method for fHMM_model
print(x, ...)
# S3 method for fHMM_model
residuals(object, ...)
# S3 method for fHMM_model
summary(object, alpha = 0.05, ...)
# S3 method for fHMM_model
coef(object, alpha = 0.05, digits = 2, ...)
# S3 method for fHMM_model
AIC(object, ..., k = 2)
# S3 method for fHMM_model
BIC(object, ...)
# S3 method for fHMM_model
nobs(object, ...)
# S3 method for fHMM_model
logLik(object, ...)
npar(object, ...)
# S3 method for fHMM_model
npar(object, ...)
# S3 method for fHMM_model
predict(object, ahead = 5, alpha = 0.05, ...)

Value

An object of class fHMM_model.

Arguments

data: An object of class fHMM_data.
estimate: A numeric vector of unconstrained model estimates.
nlm_output: The output of nlm for the selected optimization run.
estimation_time: A diff.time object, the total estimation time.
ll: A numeric, the model log-likelihood.
lls: A numeric vector, the model log-likelihoods in all optimization runs.
gradient: A numeric vector, the gradient at the optimum.
inverse_fisher: A numeric vector, the inverse Fisher information for each parameter.
decoding: A numeric vector, the decoded time series.
x, object: An object of class fHMM_model.
...: Currently not used.
alpha: A numeric between 0 and 1, the confidence level.
digits: The number of decimal places.
k: Passed on to AIC.
ahead: The number of time points to predict ahead.