durrantsmethod {GammaTest}R Documentation

Durrant's Feature Selection Method

Description

Durrant's Gamma test based feature selection method can be used to identify the relevent inputs to a smooth model based on the results of a full embedding search.

Usage

durrantsmethod(mask.array, percentage=10)

Arguments

mask.array The returned mask array from an embedding search.
percentage The proportion of masks from the high and low Gamma regions required to conduct a frequency analysis on the input inclusion/exclusion. The default is 12.5 percent.

Details

Consult Durrant's thesis from the web link below for more details.

Value

results The normalised frequency counts.

Author(s)

Samuel E. Kemp. To report any bugs or suggestions please email: sekemp@glam.ac.uk

References

Durrant P. J (2002), winGamma: a non-linear data analysis and modelling tool with applications to flood prediction, PhD Thesis, Department of Computer Science, Cardiff University, Wales, UK.

For papers, theses and other Gamma test related material please visit http://users.cs.cf.ac.uk:81/Antonia.J.Jones/GammaArchive/IndexPage.htm

See Also

gammatest fesearch dvec

Examples

# Example on an AR(1) process
ts.sim  <- arima.sim(500, model=list(ar=0.9), sd=sqrt(1))
gfts.sim <- dvec(ts.sim, 8)
my.fe   <- fesearch(gfts.sim)
durrantsmethod(my.fe$mask.array)        

[Package GammaTest version 2.1 Index]