power.plot: Plot power of benchmarked tests of independence

In knnIndep: Independence tests and benchmarks

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

Author(s)

Sebastian Dümcke [e-mail]

See Also

calculate.power, run.tests

Examples

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))

Example output

knnIndep documentation built on May 2, 2019, 3:23 a.m.