mutoss (version 0.1-3)

simulation: Simulation studies

Description

This function generates data according to a specified function and parameters and then applies specified procedures to the generated data. The input and output is gathered in a MutossSim object. Also the slot "index" of any created MutossSim is set to a specific number, so that any two MutossSim objects that are based upon the same input have the same number in the index slot.

Usage

simulation(replications, DataGen, listOfProcedures)

Arguments

replications

The number of replications. This means how many simulation runs will be performed.

DataGen

A list that contains the function and parameters for generating data which will be analyzed be the procedures in listOfProcedures.

listOfProcedures

A list of lists which contains the procedures and parameters to use for the simulation.

Value

• A list of MutossSim ojects. The list can be directly plugged into the function gatherStatistics.

Examples

# this function generates pValues 
myGen <- function(n, n0) list(pValues = c(runif(n-n0, 0, 0.01), runif(n0)), groundTruth = c(rep(FALSE, times=n-n0), rep(TRUE, times=n0)))

# Calling 10 times myGen(200, 50)
# Apply then 
# 1. bonferroni with alpha=0.25 to the 1000 lists from myGen
# 2. bonferroni with alpha=0.5 to the 1000 lists from myGen
# 3. holm with alpha=0.25 to the 1000 lists from myGen
# 4. holm with alpha=0.5 to the 1000 lists from myGen
# This yields 40 MutossSim objects
# THEN
# Calling 10 times myGen(200, 100)
# Apply then 
# 1. bonferroni with alpha=0.25 to the 1000 lists from myGen
# 2. bonferroni with alpha=0.5 to the 1000 lists from myGen
# 3. holm with alpha=0.25 to the 1000 lists from myGen
# 4. holm with alpha=0.5 to the 1000 lists from myGen
# This yields 40 MutossSim objects
# Altogether the function simulation returns 80 MutossSim objects.
sim <- simulation(replications = 10, list(funName="myGen", fun=myGen, n=200, n0=c(50,100)), 
list(list(funName="BH", fun=function(pValues, alpha) BH(pValues, alpha, silent=TRUE), alpha=c(0.25, 0.5)),
list(funName="holm", fun=holm, alpha=c(0.25, 0.5),silent=TRUE)))
#
# Just calculating some statistics and making some plots
NumberOfType1Error <- function(MutossSimObject) sum(slot(MutossSimObject, "rejected") * slot(MutossSimObject, "groundTruth"))
result.all <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error))
result <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error), list(median=median, mean=mean, sd=sd))
print(result)
require(lattice)
histogram(~NumOfType1Err | method*alpha, data = result.all$statisticDF)
barchart(NumOfType1Err.median + NumOfType1Err.mean ~ method | alpha, data = result$statisticDF)