SLBDD (version 0.0.4)

DLdata: Create an input data matrix for a Deep learning program that uses time series data.

Description

R command to setup the training and forecasting data for deep learning.

Usage

DLdata(x, forerate = 0.2, locY = 1, lag = 1)

Arguments

x

T by k data matrix: T data points in rows and k time series in columns.

forerate

Fraction of sample size to form the forecasting (or testing) sample.

locY

Locator for the dependent variable.

lag

Number of lags to be used to form predictors.

Value

A list containing:

• Xtrain - Standardized predictors matrix.

• Ytrain - Dependent variable in training sample.

• Xtest - Predictor in testing sample, standardized according to X_train.

• Ytest - Dependent variable in the testing sample.

• nfore - Number of forecasts.

Examples

# NOT RUN {
x <- matrix(rnorm(7000), nrow=700, ncol=100)
m1 <- DLdata(x, forerate=c(200/nrow(x)), lag=6, locY=6)
# }