Model the sampling process

This module function is used to specify the components of the sampling module in EpiSewer.

Each component can be specified using one or several helper functions (see available options below). See the documentation of the individual helper functions to adjust model priors and further settings.

Usage

model_sampling(
  outliers = outliers_none(),
  sample_effects = sample_effects_none()
)

Arguments

outliers

Outliers in concentrations. EpiSewer can automatically identify independent spikes in the concentration time series and model them as outliers to reduce the impact on transmission dynamic estimates. Modeling options:

• outliers_none()

• outliers_estimate()

sample_effects

Sample (batch) effects. The pathogen concentration in a sample may be influenced by sampling-related external factors, for example the time between sampling and shipping to the lab (age-of-sample effect), or different sampling or storage methods. EpiSewer allows to estimate such effects using covariates that describe differences between the samples. Modeling options:

• sample_effects_none()

• sample_effects_estimate_weekday()

• sample_effects_estimate_matrix()

Value

A modeldata object containing the data and specifications of the sampling module.

See also

Other module functions: model_forecast(), model_infections(), model_measurements(), model_sewage(), model_shedding()