NNsetting: Setting Up The Predictor Matrix in A Neural Network for Time...

In NTS: Nonlinear Time Series Analysis

Setting Up The Predictor Matrix in A Neural Network for Time Series Data

Description

The function sets up the predictor matrix in a neural network for time series data.

Usage

NNsetting(zt, locY = 1, nfore = 0, lags = c(1:5), include.lagY = TRUE)

Arguments

zt	data matrix, including the dependent variable Y(t).
locY	location of the dependent variable (column number).
nfore	number of out-of-sample prediction (1-step ahead).
lags	a vector containing the lagged variables used to form the x-matrix.
include.lagY	indicator for including lagged Y(t) in the predictor matrix.

Value

The function returns a list with following components.

X	x-matrix for training a neural network.
y	y-output for training a neural network.
predX	x-matrix for the prediction subsample.
predY	y-output for the prediction subsample.

References

Tsay, R. and Chen, R. (2018). Nonlinear Time Series Analysis. John Wiley & Sons, New Jersey.

NTS documentation built on Sept. 25, 2023, 1:08 a.m.