binhf (version 1.0-3)

qqstuff: Quantile-quantile information about Haar-NN and Anscombe samples

Description

A function to generate Q-Q plots (from simulations) for the Anscombe and (binomial) Haar-Fisz transforms.

Usage

qqstuff(intensity, binsize = 4, paths = 100, respaths = 1000, plot.q = FALSE, 
plot.sq = FALSE)

Arguments

intensity

an Bernoulli intensity vector, e.g. pintens.

binsize

a binomial size to generate a binomial mean vector.

paths

the number of paths sampled from the mean vector to use in Q-Q calculations.

respaths

the number of residual paths to use in squared residual calculations.

plot.q

A boolean variable, indicating whether simulation Q-Q plots should be outputted or not.

plot.sq

A boolean variable, indicating whether simulation squared residual plots should be outputted or not.

Value

qqinfo. A 8 component list of quantile and residual plot information.

vmat

A matrix of dimensions respathsxlength(intensity), each row being a path from the intensity vector.

Av

A matrix of dimensions respathsxlength(intensity), each row an Anscombe-transformed path.

bfv

A matrix of dimensions respathsxlength(intensity), each row a binomial Haar-Fisz-transformed path.

vminusl

A matrix of the difference between the paths and the mean intensity.

vminusl

A matrix of the difference between the Anscombe-transformed paths and the mean intensity.

vminusl

A matrix of the difference between the binomial Haar-Fisz-transformed paths and the mean intensity.

Asqres

vector of squared residuals of Anscombe-transformed paths.

bfsqres

vector of squared residuals of binomial Haar-Fisz-transformed paths.

Details

respaths paths are sampled from the mean intensity vector. From these, the first paths are used to generate Q-Q data, which are then averaged for the Q-Q plots. The original paths are used to calculate a squared residual vector corresponding to the mean intensity vector.

See Also

qqnormy

Examples

# NOT RUN {
data(pintens)

a<-qqstuff(intensity=pintens,binsize=4,paths=100,respaths=100,plot.q=TRUE,plot.sq=TRUE)

#plots some interesting graphs.
# }

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