mutoss (version 0.1-3)

gatherStatistics: Gathering statistics from MutossSim objects

Description

This function facilitates gathering statistics from a list of MutossSim objects.

Usage

gatherStatistics(listOfObjects, listOfStatisticFunctions,
    listOfAvgFunctions)

Arguments

listOfObjects

List of MutossSim objects

listOfStatisticFunctions

List of statistics that shall be calculated for every MutossSim object

listOfAvgFunctions

List of functions that will be used to summarize the calculated statistics of all MutossSim objects with the same parameter slot. If this is argument is missing no averaging will be done. Instead the resulting data.frame will keep one row for every Mutoss

Value

• statisticDF
  A data.frame that can be of two different kinds.

  If listOfAvgFunctions is provided, then the resulting data.frame will have a row for every parameter constellation that occurs in the MutossSim objects. There will be columns for every parameter used. Also length(listOfAvgFunctions) * length(listOfStatisticFunctions) additional columns will be created. Every statistic is calculated for every MutossSim object and then all values that belong to a specific parameter constellation are "averaged" by applying all function from listOfAvgFunctions. For example suppose FDP is a function from listOfStatisticFunctions that calculates the realized false discovery proportion, that is number of true hypotheses that were rejected divided by the number of all rejected hypotheses. Also suppose mean and sd are functions in listOfAvgFunctions, then the mean and the standard deviation of the statistic FDP are calculated.

  If listOfAvgFunctions is not provided, then the resulting data.frame will have a row for every MutossSim object. Every parameter will have its own column. Additional columns for every function in listOfStatisticFunction will be created additionally.

Details

For every MutossSim object in listOfObjects all statistics in listOfStatisticFunctions are calculated. If in addition listOfAvgFunctions is provided then the statistics of the objects that have the same parameter slot are passed to this functions. The resulting data.frame will then keep only one row for every parameter constellation.

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)))

# need some MutossSim objects I can work with 
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)))

# Make my own statistic function
NumberOfType1Error <- function(MutossSimObject) sum(slot(MutossSimObject, "rejected") * slot(MutossSimObject, "groundTruth"))

# Get now for every MutossSim object in sim one row in with the statistic
result.all <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error))

# Average over all MutossSim objects with common parameters 
result1 <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error), list(MEAN = mean))
print(result1)  
result2 <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error), list(q05 = function(x) quantile(x, probs=0.05), MEAN = mean, q95 = function(x) quantile(x, probs=0.95)))
print(result2)

# do some plots
require(lattice)
histogram(~NumOfType1Err | method*alpha, data = result.all$statisticDF)
barchart(NumOfType1Err.MEAN ~ method | alpha, data = result2$statisticDF)