TSSVM (version 0.1.0)

ARSVM: Auto-Regressive Support Vector Machine

Description

The ARSVM function fit Auto-Regressive Support Vector Machine for univariate time series data.

Usage

ARSVM(data,h)

Value

Optimum lag

Optimum lag of the considered data

Model Summary

Summary of the fitted SVM

Weights

weights of the fitted SVM

Constant

Constant of the fitted SVM

MAPE

Mean Absolute Percentage Error (MAPE) of the SVM

RMSE

Root Mean Square Error (RMSE) of fitted SVM

fitted

Fitted values of SVM

forecasted.values

h step ahead forecasted values employing SVM

Arguments

data

Input univariate time series (ts) data.

h

The forecast horizon.

Author

Mrinmoy Ray,Samir Barman, Kanchan Sinha, K. N. Singh

Details

This package allows you to fit the Auto-Regressive Support Vector Machine for univariate time series.

References

Kim, K.(2003). Financial time series forecasting using support vector machines, 55(1-2), 307-319.

See Also

SVM

Examples

data=lynx
ARSVM(data,5)