EpistemicCorrectedVariance.md
In FuzzySimRes: Simulation and Resampling Methods for Epistemic Fuzzy Data

Function returns correct values

Code
  set.seed(123456)
  testSample1 <- SimulateSample(n = 10, originalPD = "rnorm", parOriginalPD = list(
    mean = 0, sd = 1), incrCorePD = "rexp", parIncrCorePD = list(rate = 2),
  suppLeftPD = "runif", parSuppLeftPD = list(min = 0, max = 0.6), suppRightPD = "runif",
  parSuppRightPD = list(min = 0, max = 0.6), type = "trapezoidal")
  EpistemicCorrectedVariance(testSample1$value)
Output
  [1] 1.17446

Code
  set.seed(123456)
  testSample1 <- SimulateSample(n = 10, originalPD = "rnorm", parOriginalPD = list(
    mean = 0, sd = 1), incrCorePD = "rexp", parIncrCorePD = list(rate = 2),
  suppLeftPD = "runif", parSuppLeftPD = list(min = 0, max = 0.6), suppRightPD = "runif",
  parSuppRightPD = list(min = 0, max = 0.6), type = "trapezoidal")
  EpistemicCorrectedVariance(testSample1$value, cutsNumber = 10)
Output
  [1] 1.807633

Code
  set.seed(123456)
  testSample1 <- SimulateSample(n = 1, originalPD = "rnorm", parOriginalPD = list(
    mean = 0, sd = 1), suppLeftPD = "runif", parSuppLeftPD = list(min = 0, max = 0.6),
  suppRightPD = "runif", parSuppRightPD = list(min = 0, max = 0.6), type = "triangular")
  EpistemicCorrectedVariance(testSample1$value[[1]], cutsNumber = 12)
Output
  [1] 0

Code
  set.seed(123456)
  testSample1 <- SimulateSample(n = 5, originalPD = "rnorm", parOriginalPD = list(
    mean = 0, sd = 1), incrCorePD = "rexp", parIncrCorePD = list(rate = 2),
  suppLeftPD = "runif", parSuppLeftPD = list(min = 0, max = 0.6), suppRightPD = "runif",
  parSuppRightPD = list(min = 0, max = 0.6), knotNumbers = 0, type = "PLFN")
  EpistemicCorrectedVariance(testSample1$value, cutsNumber = 10)
Output
  [1] 2.017854

Code
  set.seed(123456)
  testSample1 <- SimulateSample(n = 5, originalPD = "rnorm", parOriginalPD = list(
    mean = 0, sd = 1), incrCorePD = "rexp", parIncrCorePD = list(rate = 2),
  suppLeftPD = "runif", parSuppLeftPD = list(min = 0, max = 0.6), suppRightPD = "runif",
  parSuppRightPD = list(min = 0, max = 0.6), knotNumbers = 0, type = "PLFN")
  testSample1Epistemic <- EpistemicBootstrap(testSample1$value, cutsNumber = 8)
  EpistemicCorrectedVariance(testSample1Epistemic)
Output
  [1] 11.16113