WaveletGARCHFore: Forecasting by Wavelet-GARCH model

In WaveletGARCH: Fit the Wavelet-GARCH Model to Volatile Time Series Data

Description

Forecasting of Wavelet-GARCH model based on ARCH LM test.

Usage

WaveletGARCHFore(series,filtern,level,nofore)
## S3 method for class 'WaveletGARCHFore'
print(x,...)

Arguments

series	univariate time series
filtern	The name of wavelet filter
level	The level of wavelet decomposition
nofore	The lead period of forecast
x	An object of WaveletGARCHFore
...	Additional arguments if any

Value

forecastobject

The forecasted values of the series by Waveetl-GARCH model

References

Percival D. B. and Walden A. T. 2000. Wavelet Methods for Time-Series Analysis. Cambridge Univ. Press, U.K.

Paul R. K., Prajneshu and Ghosh H. 2013. Wavelet Frequency Domain Approach for Modelling and Forecasting of Indian Monsoon Rainfall Time-Series Data. Journal of the Indian society of agricultural statistics, 67, 319 to 327.

Paul, R.K. and Birthal, P.S. 2015. Investigating rainfall trend over India using wavelet technique. Journal of Water and Climate Change, 7, 365 to 378.

Paul, R. K. 2015. ARIMAX-GARCH-WAVELET Model for forecasting volatile data. Model Assisted Statistics and Application, 10, 243 to252.

Examples

data(mtcars)
ab<-mtcars$qsec

objfore<-WaveletGARCHFore(ab,"d4",4,10)

WaveletGARCH documentation built on Feb. 29, 2020, 5:08 p.m.