run.tests: Run several tests of independence on a benchmark of different...

In knnIndep: Independence tests and benchmarks

Description

This function runs a set of independence tests on a benchmark consisting of different functional dependence types (see generate.benchmark.data)

Usage

run.tests(fun, args, types, noises, size = 320, nsim = 500, ...)

Arguments

fun	function or character naming a function. A function should have two vectors of coordinates as first two arguments
args	list of additional arguments to the functions fun. If a function does not need any arguments use an empty list.
types	numeric, which type of dependence to benchmark (see generate.benchmark.data)
noises	matrix of noise to add to each dependence. It should have types number of columns
size	numeric, size of the data sets to generate (default 320 points)
nsim	numeric, how many replicate simulations to run under the null model and H1, default 500
...	additional arguments to pass on to function generate.benchmark.data

Details

This function makes use of mclapply so MC_CORES should be set to a number greater than 1 for parallelization

Value

This function returns a list data structure that can be further processed with the functions of this package, calculate.power,generate.roc

Author(s)

Sebastian Dümcke [e-mail]

See Also

calculate.power,generate.roc, generate.benchmark.data

Examples

noises = cbind(lin=c(.1,.5,.8),circ=c(.2,.4,.6))
mycor = function(...) cor(...)^2
results.cor=run.tests(mycor,args=list(),types=c(1,7),noises=noises,nsim=50,size=100)
results = run.tests("novelTest.extreme",args=list(maxi=10),types=c(1,7),noises=noises,nsim=25,
	size=100)
## Not run: 
x11()
par(mfrow=c(1,ncol(noises)))
roc.plot(generate.roc(results,pval=FALSE),legend=noises)

## End(Not run)
power = t(drop(calculate.power(results,.95,`>`)))
power.cor = t(drop(calculate.power(results.cor,.95,`>`)))
#cor is excellent at linear relationships, not so much for circular relationships:
#(increasing power is an artifact of low number of simulation, increase nsim in run.tests)
power.plot(list(cor=power.cor, novelTest=power),noises,show.legend="topright",mains=c("Linear", 
	"Circle")) 

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