excodeModel Class — excodeModel-class • excode

The `excodeModel` class is a generic container for the model used for outbreak detection based on a hidden Markov model framework.

Slots

nStates: Number of states in the hidden Markov model.
emission: Emission component of the hidden Markov model, including an `excodeFamily` and an `excodeFormula` object.
transitions: Transition probabilities of the hidden Markov model.
transitions_prior: Logical indicating whether a prior for transition probabilities should be used.
prior_weights: Dirichlet prior weights for transition probabilities; cannot be changed by the user.
loglik_transitions: Prior log-likelihood of transition probabilities; only relevant for model fitting.
initial_prob: Initial state probabilities of the hidden Markov model.
setBckgState: Logical indicating whether a background state should be computed for model fitting; background states are set to 0 for time points where the Anscombe residuals of the initial model are < 1.
converged: Logical indicating whether the EM algorithm converged.
niter: Number of iterations used for model fitting.
LogLik: Log-likelihood of the fitted model.
AIC: Akaike information criterion of the fitted model.
BIC: Bayesian information criterion of the fitted model.
posterior: Matrix of posterior probabilities for each time point (rows) and state (columns).
pval: P-values for testing whether each time point is in a normal or excess state.
zscore: Standardized Anscombe residuals (z-scores) for each time point.
timepoint_fit: Numeric time point in the time series used for fitting.
timepoint: Numeric time point in the time series.
date: Date corresponding to each time point.
observed: Vector of observed counts or case numbers.
population: Population size; default is 1.
error: Character string containing an error message, if an error occurred during model fitting.