fv_as_data_list: Format data for use with stan

In epiforecasts/forecast.vocs: Forecast Case and Sequence Notifications using Variant of Concern Strain Dynamics

Format data for use with stan

Description

Format data for use with stan

Usage

fv_as_data_list(
  obs,
  horizon = 4,
  r_init = c(0, 0.25),
  r_step = 1,
  r_forecast = TRUE,
  beta = c(0, 0.5),
  lkj = 0.5,
  voc_scale = c(0, 0.2),
  period = NULL,
  special_periods = c(),
  variant_relationship = "correlated",
  overdispersion = TRUE,
  likelihood = TRUE,
  output_loglik = TRUE,
  debug = FALSE
)

Arguments

obs	A data frame with the following variables: date, cases, seq_voc, and seq_total.
horizon	Integer forecast horizon. Defaults to 4.
r_init	Numeric vector of length 2. Mean and standard deviation for the normal prior on the initial log growth rate.
r_step	Integer, defaults to 1. The number of observations between each change in the growth rate.
r_forecast	Logical, defaults TRUE. Should the growth rate be forecast beyond the data horizon.
beta	Numeric vector, defaults to c(0, 0.5). Represents the mean and standard deviation of the normal prior (truncated at 1 and -1) on the weighting in the differenced AR process of the previous difference. Placing a tight prior around zero effectively reduces the AR process to a random walk on the growth rate.
lkj	Numeric defaults to 0.5. The assumed prior covariance between variants growth rates when using the "correlated" model. This sets the shape parameter for the Lewandowski-Kurowicka-Joe (LKJ) prior distribution. If set to 1 assigns a uniform prior for all correlations, values less than 1 indicate increased belief in strong correlations and values greater than 1 indicate increased belief weaker correlations. Our default setting places increased weight on some correlation between strains.
voc_scale	Numeric vector of length 2. Prior mean and standard deviation for the initial growth rate modifier due to the variant of concern.
period	Logical defaults to NULL. If specified should be a function that accepts a vector of dates. This can be used to assign periodic effects to dates which will then be adjusted for in the case model. An example is adjusting for day of the week effects for which the fv_dow_period() can be used.
special_periods	A vector of dates to pass to the period function argument with the same name to be treated as "special" for example holidays being treated as sundays in fv_dow_period().
variant_relationship	Character string, defaulting to "correlated". Controls the relationship of strains with options being "correlated" (strains growth rates are correlated over time), "scaled" (a fixed scaling between strains), and "independent" (fully independent strains after initial scaling).
overdispersion	Logical, defaults to TRUE. Should the observations used include overdispersion.
likelihood	Logical, defaults to TRUE. Should the likelihood be included in the model
output_loglik	Logical, defaults to FALSE. Should the log-likelihood be output. Disabling this will speed up fitting if evaluating the model fit is not required.
debug	Logical, defaults to FALSE. Should within model debug information be returned.

Value

A list as required by stan.

See Also

Functions used for modelling fv_inits(), fv_model(), fv_sample()

Examples

fv_as_data_list(latest_obs(germany_covid19_delta_obs))

epiforecasts/forecast.vocs documentation built on May 14, 2023, 2 p.m.