Time Series Forecasting Using GRNN
A general regression neural network (GRNN) is a variant of a
Radial Basis Function Network characterized by a fast single-pass learning.
'tsfgrnn' allows you to forecast time series using a GRNN model Francisco
Martinez et al. (2019) <10.1007> and Weizhong Yan
(2012) <10.1109>. When the forecasting horizon
is higher than 1, two multi-step ahead forecasting strategies can be used.
The model built is autoregressive, that is, it is only based on the
observations of the time series. You can consult and plot how the
prediction was done. It is also possible to assess the forecasting accuracy
of the model using rolling origin evaluation.10.1109>10.1007>