data_impute: Impute missing values

In tylerJPike/OOS: Out-of-Sample Time Series Forecasting

Description

A function to impute missing values. Is used as a data preparation helper function and is called internally by forecast_univariate, forecast_multivariate, and forecast_combine.

Usage

data_impute(Data, method = "kalman", variables = NULL, verbose = FALSE)

Arguments

Data	data.frame: data frame of target variable, exogenous variables, and observed date (named 'date')
method	string: select which method to use from the imputeTS package; 'interpolation', 'kalman', 'locf', 'ma', 'mean', 'random', 'remove','replace', 'seadec', 'seasplit'
variables	string: vector of variables to standardize, default is all but 'date' column
verbose	boolean: show start-up status of impute.missing.routine

Value

data.frame with missing data imputed

tylerJPike/OOS documentation built on March 20, 2021, 3:20 a.m.