WaveletETS {WaveletETS} | R Documentation |
Wavelet Based Error Trend Seasonality Model
Description
Wavelet Based Error Trend Seasonality Model
Usage
WaveletETS(ts, split_ratio = 0.8, wlevels = 3)
Arguments
ts |
Time Series Data |
split_ratio |
Training and Testing Split |
wlevels |
Number of Wavelet Levels |
Value
Train_actual: Actual train series
Test_actual: Actual test series
Train_fitted: Fitted train series
Test_predicted: Predicted test series
Accuracy: RMSE and MAPE of the model
References
Aminghafari, M. and Poggi, J.M. 2012. Nonstationary time series forecasting using wavelets and kernel smoothing. Communications in Statistics-Theory and Methods, 41(3),485-499.
Paul, R.K. A and Anjoy, P. 2018. Modeling fractionally integrated maximum temperature series in India in presence of structural break. Theory and Applied Climatology 134, 241–249.
Examples
library("WaveletETS")
data<- rnorm(100,100, 10)
WG<-WaveletETS(ts=data)
[Package WaveletETS version 0.1.0 Index]