WaveletETS

ETS stands for Error, Trend, and Seasonality, and it is a popular time series forecasting method. Wavelet decomposition can be used for denoising, compression, and feature extraction of signals. By removing the high-frequency components, wavelet decomposition can remove noise from the data while preserving important features. A hybrid Wavelet ETS (Error Trend-Seasonality) model has been developed for time series forecasting using algorithm of Anjoy and Paul (2017) doi:10.1007/s00521-017-3289-9.

Last 30 days

This package has been downloaded 125 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 1,815 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 23 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.