Wavelet-based Testing and Locating for Variance Change Points

This is the major subroutine for testing.hov, providing the workhorse algorithm to recursively test and locate multiple variance changes in so-called long memory processes.

mult.loc(dwt.list, modwt.list, wf, level, min.coef, debug)

Arguments

dwt.list	List of wavelet vector coefficients from the `dwt`.
modwt.list	List of wavelet vector coefficients from the `modwt`.
wf	Name of the wavelet filter to use in the decomposition.
level	Specifies the depth of the decomposition.
min.coef	Minimum number of wavelet coefficients for testing purposes.
debug	Boolean variable: if set to `TRUE`, actions taken by the algorithm are printed to the screen.

Value

Matrix.

Details

For details see Section 9.6 of Percival and Walden (2000) or Section 7.3 in Gencay, Selcuk and Whitcher (2001).

References

Gencay, R., F. Selcuk and B. Whitcher (2001) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press.

Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.

Author