| Title: | Forecasting of univariate time series using the Pattern Sequence-based Forecasting (PSF) algorithm |
|---|---|
| Description: | Pattern Sequence Based Forecasting (PSF) takes univariate time series data as input and assist to forecast its future values. This algorithm forecasts the behavior of time series based on similarity of pattern sequences. Initially, clustering is done with the labeling of samples from database. The labels associated with samples are then used for forecasting the future behaviour of time series data. The further technical details and references regarding PSF are discussed in Vignette. |
| Authors: | Neeraj Bokde, Gualberto Asencio-Cortes and Francisco Martinez-Alvarez |
| Maintainer: | Neeraj Bokde <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.3 |
| Built: | 2024-11-13 02:58:01 UTC |
| Source: | https://github.com/neerajdhanraj/psf |
Takes an univariate time series and the prediction horizon as inputs.
psf(data, n.ahead, k = seq(2, 10), w = seq(1, 10), cycle = 24)psf(data, n.ahead, k = seq(2, 10), w = seq(1, 10), cycle = 24)
data |
Input univariate time series, in any format (time series (ts), vector, matrix, list, data frame). |
n.ahead |
The number of predicted values to be obtained. |
k |
The number of clusters, or a vector of candidate values to search for the optimum automatically. |
w |
The window size, or a vector of candidate values to search for the optimum automatically. |
cycle |
The number of values that conform a cycle in the time series (e.g. 24 hours per day). Only used when input data is not in time series format. |
A list with 3 elements:
predictions |
Vector with the resulting predictions |
k |
Number of clusters used |
w |
Window size used |
## Forecast the next 12 values of the univariate time series: nottem (package:datasets). psf(nottem, 12) ## Forecast the next 48 values of the univariate time series: sunspots (package:datasets). psf(sunspots, 48)## Forecast the next 12 values of the univariate time series: nottem (package:datasets). psf(nottem, 12) ## Forecast the next 48 values of the univariate time series: sunspots (package:datasets). psf(sunspots, 48)
Takes an univariate time series and a vector with forecasted values.
psf_plot(data, predictions, cycle = 24, ...)psf_plot(data, predictions, cycle = 24, ...)
data |
Input univariate time series (in either time series (ts) or vector format). All values should be numeric. |
predictions |
A vector with already forecasted values. |
cycle |
The number of values that conform a cycle in the time series (e.g. 24 hours per day, 12 month per year, and so on). Only used when input data is not in time series (ts) format. |
... |
Additional graphical parameters given to plot function. |
## Forecast the next 12 values of the univariate time series: nottem (package:datasets). res <- psf(nottem, 12) ## Plot forecasted values from PSF. psf_plot(nottem, res$predictions)## Forecast the next 12 values of the univariate time series: nottem (package:datasets). res <- psf(nottem, 12) ## Plot forecasted values from PSF. psf_plot(nottem, res$predictions)