TpAUCboot: tpAUCboot

In juanpegarcia/ROCpAI: Receiver Operating Characteristic Partial Area Indexes for evaluating classifiers

Description

Calculates the confidence interval using a boot analysis

Usage

tpAUCboot(
  dataset,
  low.value = NULL,
  up.value = NULL,
  r = 50,
  level = 0.95,
  type.interval = "perc",
  selection = NULL,
  variable = NULL
)

Arguments

dataset	dataframe or RangedSummarizedExperiment objetc
low.value	lower false positive rate value that the function will use to calculate the pAUC
up.value	upper false positive rate value that the function will use to calculate the pAUC
r	number of iterations.
level	confidence level
type.interval	String that represent the type of intervals required. The value should be any subset of the values c("norm","basic", "stud", "perc", "bca") or simply "all" which will compute all five types of intervals.
selection	vector that will only be used if the parameter "dataset" is a RangedSummarizedExperiment object. This parameter is used to select the variables that will be analysed
variable	in case that dataset is a SummarizedExperiment, indicate the Gold Standard

Value

SummarizedExperiment object with the Tp_AUC, the standard desviation, and the lower and upper limits of the confidence interval

Examples

library(fission)
data("fission")
resultstboot<- tpAUCboot(fission,low.value = 0, up.value = 0.25,
selection = c("SPNCRNA.1080","SPAC186.08c"), variable="strain")

juanpegarcia/ROCpAI documentation built on June 3, 2021, 5:42 a.m.