inspectgammahist {GammaTest}R Documentation

Model Identification: Inspecting The Peaks of a Gamma Histogram

Description

Identifies the relevent inputs to a smooth model based on the analysing the peaks in the Gamma histogram from a full embedding search.

Usage

inspectgammahist(fe.results, gamma.range, ones=TRUE)

Arguments

fe.results The returned results from a full embedding search.
gamma.range The range of the Gamma statistics we wish to inspect.
ones Logical indicating whether to count the occurances of input inclusion/exclusion. TRUE indicates to count input exclusion, FALSE means to count input exclusion.

Details

Counts the number of input inclusions or exclusions within a particular Gamma range. For more information see Durrant (2002).

Value

results The normalised frequency counts.

Author(s)

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

References

Kemp S. E. (2004), Gamma Test Based Data Analysis Applied to Modelling and Forecasting Crime Rates, MPhil to PhD Transfer Report, School of Computing, University of Glamorgan, Wales, UK.

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.

Jones A. J (2003), New tools in non-linear modelling and prediction. Computational Management Science, 1(1):xx.

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)
inspectgammahist(my.fe, gamma.range=c(0,1), ones=TRUE)  

[Package GammaTest version 2.1 Index]