add_missing_attributes_to_ts_object: Add missing attributes to time series object

In ing-bank/tsforecast: Time Series Forecasting Pipeline

Description

add_missing_attributes_to_ts_object is a function to add a set of missing attributes to a time series object. This is usually required after transforming a time series object, e.g. by applying the window function, during which manually added attributes are removed.

Usage

add_missing_attributes_to_ts_object(new_ts_object, prev_ts_object)

Arguments

new_ts_object	A time series object, to which the missing attributes need to be added.
prev_ts_object	A time series object, which contains the attributes that are missing.

Value

A time series object with an extended set of attributes.

Examples

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 = CompanyA") %>%
   tstools::transform_data_to_ts_object(seasonal_periods = 3)
new_ts_object <- window(
   x = ts_object, 
   end = c(2001, 1)
)
attributes(new_ts_object)
new_ts_object <- add_missing_attributes_to_ts_object(
   new_ts_object = new_ts_object,
   prev_ts_object = ts_object
)
attributes(new_ts_object)

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