| Title: | Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD) |
|---|---|
| Description: | Predict future values with hybrid combinations of Pattern Sequence based Forecasting (PSF), Autoregressive Integrated Moving Average (ARIMA), Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) methods based hybrid methods. |
| Authors: | Neeraj Bokde |
| Maintainer: | Neeraj Bokde <[email protected]> |
| License: | GPL |
| Version: | 0.2 |
| Built: | 2024-11-01 03:08:41 UTC |
| Source: | https://github.com/cran/decomposedPSF |
Function to predict with EEMD-ARIMA model
eemdarima(data, n.ahead)eemdarima(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EEMD-ARIMA model
# eemdarima(data = nottem, n.ahead = 6)# eemdarima(data = nottem, n.ahead = 6)
Function to predict with EEMD-PSF model
eemdpsf(data, n.ahead)eemdpsf(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EEMD-PSF model
# eemdpsf(data = nottem, n.ahead = 6)# eemdpsf(data = nottem, n.ahead = 6)
Function to predict with EEMD-PSF,ARIMA model
eemdpsfarima(data, n.ahead)eemdpsfarima(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EEMD-PSF,ARIMA model
# eemdpsfarima(data = nottem, n.ahead = 6)# eemdpsfarima(data = nottem, n.ahead = 6)
Function to predict with EMD-ARIMA model
emdarima(data, n.ahead)emdarima(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EMD-ARIMA model
# emdarima(data = nottem, n.ahead = 6)# emdarima(data = nottem, n.ahead = 6)
Function to predict with EMD-PSF model
emdpsf(data, n.ahead)emdpsf(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EMD-PSF model
# emdpsf(data = nottem, n.ahead = 6)# emdpsf(data = nottem, n.ahead = 6)
Function to predict with EMD-PSF,ARIMA model
emdpsfarima(data, n.ahead)emdpsfarima(data, n.ahead)
data |
as input time series data |
n.ahead |
as horizon of values to be predicted |
predicted values with EMD-PSF,ARIMA model
# emdpsfarima(data = nottem, n.ahead = 6)# emdpsfarima(data = nottem, n.ahead = 6)
Function to restrict the legth of dataset in multiples of 24
lpsf(data, n.ahead)lpsf(data, n.ahead)
data |
as inpute time series |
n.ahead |
as horizon of values to be predicted |
returns the predictied results