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knnIndep (version 2.0)

power.plot: Plot power of benchmarked tests of independence

Description

This functions plots the results of the benchmark. Input are the estimated powers at a certin significance level from calculate.power.

Usage

power.plot(powers, num.noise = seq(from = 0.1, to = 3, by = 0.1), mains = c("Linear", 
	"Quadratic", "Cubic", expression("Sine: period 4" * pi), 
	expression("Sine: period 16" * pi), "X^(1/4)", "Circle", "Step function",
	 "Torus"), col = c("black", "red", "blue", "green", "cyan", "brown", "pink"), 
	 labels = TRUE,	which = 1:nrow(powers[[1]]), show.legend = "bottomright")

Arguments

powers
named list of matrices one for each method with dimension, with one row for each type of dependence and a column for each noise level
num.noise
matrix, noise levels at which the test were run (see run.tests)
mains
character vector, title of each dependence type
col
character vector, specify the colours, one for each test
labels
labels to plot at the x axis, or TRUE (default) for standard label plotting (see axis)
which
numeric vector, which type of dependence to plot
show.legend
character, either ("bottomright", "topleft", "topright", or "bottomleft") indicates where to place the legend (see legend). NULL (default) to disable plotting a legend

Value

Does not return a value, used for the side-effect of plotting

See Also

calculate.power, run.tests

Examples

Run this code
mycor = function(...) cor(...)^2
noises = cbind(c(.3,.4,6),c(.3,.5,4))
colnames(noises) = c("1",".2") #mutual information of the noise levels
vals = run.tests(mycor,list(),1:2,noises,100)
power.cor = drop(calculate.power(vals))
power.plot(list(cor=power.cor),t(noises))

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