Get a data frame of data and model fit diagnostics

Usage

get_diagnostics(
  stan_fit_object,
  train_data,
  location,
  model_type,
  forecast_date,
  ebmfi_tolerance = 0.2,
  divergences_tolerance = 0.01,
  p_high_rhat_tolerance = 0.05,
  max_tree_depth_tol = 0.01,
  ...
)

Arguments

stan_fit_object: The cmdstan object
train_data: The dataframe containing hospital admissions and wastewater data for callibration of the model
location: The location the model is being run on
model_type: The type of model
forecast_date: The date of the forecast
ebmfi_tolerance: tolerance for mean EBMFI, default of 0.2
divergences_tolerance: tolerance for percent of iterations that are divergent from an individual chain
p_high_rhat_tolerance: tolerance for probability of high p_hat, default 0.05
max_tree_depth_tol: tolerance for number of draws that hit the maximum tree depth, default to 0.01
...

Value

Returns a dataframe containing diagnostic summaries