ARX forecaster argument constructor — arx_args

Constructs a list of arguments for arx_forecaster().

Usage

arx_args_list(
  lags = c(0L, 7L, 14L),
  ahead = 7L,
  n_training = Inf,
  forecast_date = NULL,
  target_date = NULL,
  quantile_levels = c(0.05, 0.95),
  symmetrize = TRUE,
  nonneg = TRUE,
  quantile_by_key = character(0L),
  nafill_buffer = Inf,
  check_enough_data_n = NULL,
  check_enough_data_epi_keys = NULL,
  ...
)

Arguments

lags: Vector or List. Positive integers enumerating lags to use in autoregressive-type models (in days). By default, an unnamed list of lags will be set to correspond to the order of the predictors.
ahead: Integer. Number of time steps ahead (in days) of the forecast date for which forecasts should be produced.
n_training: Integer. An upper limit for the number of rows per key that are used for training (in the time unit of the epi_df).
forecast_date: Date. The date on which the forecast is created. The default NULL will attempt to determine this automatically.
target_date: Date. The date for which the forecast is intended. The default NULL will attempt to determine this automatically.
quantile_levels: Vector or NULL. A vector of probabilities to produce prediction intervals. These are created by computing the quantiles of training residuals. A NULL value will result in point forecasts only.
symmetrize: Logical. The default TRUE calculates symmetric prediction intervals. This argument only applies when residual quantiles are used. It is not applicable with trainer = quantile_reg(), for example.
nonneg: Logical. The default TRUE enforces nonnegative predictions by hard-thresholding at 0.
quantile_by_key: Character vector. Groups residuals by listed keys before calculating residual quantiles. See the by_key argument to layer_residual_quantiles() for more information. The default, character(0) performs no grouping. This argument only applies when residual quantiles are used. It is not applicable with trainer = quantile_reg(), for example.
nafill_buffer: At predict time, recent values of the training data are used to create a forecast. However, these can be NA due to, e.g., data latency issues. By default, any missing values will get filled with less recent data. Setting this value to NULL will result in 1 extra recent row (beyond those required for lag creation) to be used. Note that we require at least min(lags) rows of recent data per geo_value to create a prediction. For this reason, setting nafill_buffer < min(lags) will be treated as additional allowed recent data rather than the total amount of recent data to examine.
check_enough_data_n: Integer. A lower limit for the number of rows per epi_key that are required for training. If NULL, this check is ignored.
check_enough_data_epi_keys: Character vector. A character vector of column names on which to group the data and check threshold within each group. Useful if training per group (for example, per geo_value).
...: Space to handle future expansions (unused).

Value

A list containing updated parameter choices with class arx_flist.

Examples

arx_args_list()
#> • lags : 0, 7, and 14
#> • ahead : 7
#> • n_training : Inf
#> • quantile_levels : 0.05 and 0.95
#> • forecast_date : "NULL"
#> • target_date : "NULL"
#> • symmetrize : TRUE
#> • nonneg : TRUE
#> • max_lags : 14
#> • quantile_by_key : "_empty_"
#> • nafill_buffer : Inf
#> • check_enough_data_n : "NULL"
#> • check_enough_data_epi_keys : "NULL"
arx_args_list(symmetrize = FALSE)
#> • lags : 0, 7, and 14
#> • ahead : 7
#> • n_training : Inf
#> • quantile_levels : 0.05 and 0.95
#> • forecast_date : "NULL"
#> • target_date : "NULL"
#> • symmetrize : FALSE
#> • nonneg : TRUE
#> • max_lags : 14
#> • quantile_by_key : "_empty_"
#> • nafill_buffer : Inf
#> • check_enough_data_n : "NULL"
#> • check_enough_data_epi_keys : "NULL"
arx_args_list(quantile_levels = c(.1, .3, .7, .9), n_training = 120)
#> • lags : 0, 7, and 14
#> • ahead : 7
#> • n_training : 120
#> • quantile_levels : 0.1, 0.3, 0.7, and 0.9
#> • forecast_date : "NULL"
#> • target_date : "NULL"
#> • symmetrize : TRUE
#> • nonneg : TRUE
#> • max_lags : 14
#> • quantile_by_key : "_empty_"
#> • nafill_buffer : Inf
#> • check_enough_data_n : "NULL"
#> • check_enough_data_epi_keys : "NULL"