Negative Binomial Observation Error Model — NegativeBinomialError • EpiAwareR

Links latent infections to observed case counts using a negative binomial distribution. The cluster_factor parameterizes the overdispersion as the coefficient of variation (sqrt(1/phi)), which is more intuitive for setting priors than the dispersion parameter phi directly.

NegativeBinomialError(cluster_factor_prior)

Arguments

cluster_factor_prior: Distribution specification for the cluster factor (sqrt(1/phi)), which represents the coefficient of variation of observation noise.

Value

An S3 object of class c("epiaware_negbin", "epiaware_observation", "epiaware_model") containing:

julia_ref: Reference to the Julia NegativeBinomialError object
spec: List of model specifications

Examples

if (FALSE) { # \dontrun{
# Negative binomial observation model
negbin <- NegativeBinomialError(
  cluster_factor_prior = halfnorm(0.1)
)
print(negbin)
} # }