apply_transformation: #' apply_transformation

In linea: Linear Regression Interface

#' apply_transformation

Description

Transform data based on model table

Usage

apply_transformation(
  raw_data = NULL,
  model_table = NULL,
  trans_df = NULL,
  pool_var = NULL,
  verbose = FALSE
)

Arguments

raw_data	data.frame containing data for analysis
model_table	data.frame as created in the build_model_table function
trans_df	data.frame defining the non-linear transformations to apply
pool_var	string specifying the pool variable name (e.g. 'country')
verbose	A boolean to specify whether to print warnings

Details

Transform data based on the model table by applying the transformation functions (e.g. decay, diminish, lag, and ma) with the specified parameters to the respective variable

Value

data.frame of raw_data with added transformed variables

Examples

pooled_data = read_xcsv(
 verbose = FALSE,
 file = "https://raw.githubusercontent.com/paladinic/data/main/pooled%20data.csv")


model_table = build_model_table('christmas')
model_table['decay'] = '0.5'

trans_data = apply_transformation(
 raw_data = pooled_data,
 model_table = model_table,
 pool_var = 'country')

linea documentation built on Sept. 15, 2022, 9:06 a.m.