add_ts_object_split: Add a ts_object split to the main_forecasting_table

In ing-bank/tsforecast: Time Series Forecasting Pipeline

Description

add_ts_object_split is a function to split a time series object into training or validation data and add them as a separate column to the main_forecasting_table.

Usage

add_ts_object_split(
  main_forecasting_table,
  type = c("train", "valid"),
  ts_object
)

Arguments

main_forecasting_table	A tibble containing five columns: ts_start, ts_split_date, ts_end, train_length and valid_length. ts_start column stores starting dates of the time series object and ts_end column stores end date. ts_split_date column give the date point where to split the time series object to be training or validation data. train_length and valid_length columns represent number of training data points and validation data points after each splitting. Thus, each row in the main_forecasting_table is one way of splitting the time series object.#'
type	A character string indicates obtaining training data or validation data, which can be either "train" or "valid".
ts_object	A time series object containing the values for the column_of_interest, which has been created using the transform_data_to_ts_object function from tstools.

Value

main_forecasting_table, the same tibble but extended with a new column named either "ts_object_train" or "ts_object_valid" which contains a time series object to be used for training or validation.

Examples

main_forecasting_table <- tibble::tibble(
   ts_start = 199101,
   ts_split_date = 199308,
   ts_end = 200611,
   train_length = 32,
   valid_length = 159
)
ts_object <- tstools::initialize_ts_forecast_data(
      data = dummy_gasprice,
      date_col = "year_month",
      col_of_interest = "gasprice",
      group_cols = c("state", "oil_company"),
      xreg_cols = c("spotprice", "gemprice")
   ) %>%
   dplyr::filter(grouping == "state = New York   &   oil_company = CompanyB") %>%
   dplyr::select(period, col_of_interest, grouping) %>%
   tstools::transform_data_to_ts_object(seasonal_periods = c(12, 3))
main_forecasting_table %>%
   add_ts_object_split(
      type = "train",
      ts_object = ts_object
   ) %>%
   add_ts_object_split(
      type = "valid",
      ts_object = ts_object
   )

ing-bank/tsforecast documentation built on Sept. 18, 2020, 9:40 a.m.