validation_targets <- list(
# validate both prior and posterior
tar_target(
validate_likelihood,
c(TRUE, FALSE)
),
# load data for validation data source
tar_target(
validation_obs,
filter_obs(observations, validation_source)
),
# extract the most up to date version of the validation data
tar_target(
current_validation_obs,
latest_obs(validation_obs)
),
# split data into that available in each forecast week
tar_target(
retro_validation_obs,
filter_by_availability(validation_obs, date = validation_dates),
map(validation_dates),
iteration = "list"
),
# plot prior predictive check
# plot posterior predictive check
# Targets producing forecasts for each week of observed data
# prior and predictive checks for validation data on the single strain model
tar_target(
single_predictive_checks,
do.call(
forecast,
c(
forecast_args,
retro_args,
list(
obs = retro_validation_obs,
strains = 1,
model = single_model,
likelihood = validate_likelihood,
overdispersion = overdispersion_scenarios
)
)
)[, likelihood := validate_likelihood],
cross(retro_validation_obs, validate_likelihood, overdispersion_scenarios)
),
# prior and predictive checks for validation data on the two strain model
# stratified by modelled relationship between variants
tar_target(
two_predictive_checks,
do.call(
forecast,
c(
forecast_args,
retro_args,
list(
obs = retro_validation_obs,
strains = 2,
variant_relationship = variant_relationship_scenarios,
model = two_model,
likelihood = validate_likelihood,
overdispersion = overdispersion_scenarios
)
)
)[, likelihood := validate_likelihood],
cross(retro_validation_obs, variant_relationship_scenarios,
overdispersion_scenarios, validate_likelihood)
),
## plot prior predictions for single model
tar_target(
plot_single_strain_prior,
plot_single_strain_predictions(single_predictive_checks,
current_validation_obs,
likelihood = FALSE),
format = "file"
),
## plot posterior predictions for single model
tar_target(
plot_single_strain_posterior,
plot_single_strain_predictions(single_predictive_checks,
current_validation_obs,
likelihood = TRUE),
format = "file"
),
## plot prior predictions for two strain model
tar_target(
plot_two_strain_prior_overdisp,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = FALSE, overdispersion = TRUE),
format = "file"
),
tar_target(
plot_two_strain_prior,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = FALSE, overdispersion = FALSE),
format = "file"
),
tar_target(
plot_two_strain_prior_overdisp_voc,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = FALSE, overdispersion = TRUE,
type = "voc"),
format = "file"
),
tar_target(
plot_two_strain_prior_voc,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = FALSE, overdispersion = FALSE,
type = "voc"),
format = "file"
),
## plot posterior predictions for two strain models
tar_target(
plot_two_strain_posterior_overdisp,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = TRUE, overdispersion = TRUE),
format = "file"
),
tar_target(
plot_two_strain_posterior,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = TRUE, overdispersion = FALSE),
format = "file"
),
tar_target(
plot_two_strain_posterior_overdisp_voc,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = TRUE, overdispersion = TRUE,
type = "voc"),
format = "file"
),
tar_target(
plot_two_strain_posterior_voc,
plot_two_strain_predictions(two_predictive_checks, current_validation_obs,
likelihood = TRUE, overdispersion = FALSE,
type = "voc"),
format = "file"
)
)
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