Fuzzy.CI.test: Computes a fuzzy inference test by the traditional fuzzy...
In FuzzySTs: Fuzzy Statistical Tools

Description Usage Arguments Value Examples

View source: R/Fuzzy_test_CI_25102018.R

Computes a fuzzy inference test by the traditional fuzzy confidence intervals

Fuzzy.CI.test(
  type,
  H0,
  H1,
  t,
  s.d,
  n,
  sig,
  distribution,
  distance.type = "DSGD",
  i = 1,
  j = 1,
  theta = 1/3,
  thetas = 1,
  p = 2,
  q = 0.5,
  breakpoints = 100,
  plot = TRUE
)

`type`	a category betwenn "0", "1" and "2". The category "0" refers to a bilateral test, the category "1" for a lower unilateral one, and "2" for an upper unilateral test.
`H0`	a trapezoidal or a triangular fuzzy number representing the fuzzy null hypothesis.
`H1`	a trapezoidal or a triangular fuzzy number representing the fuzzy alternative hypothesis.
`t`	a given numerical or fuzzy type parameter of the distribution.
`s.d`	a numerical value for the standard deviation of the distribution.
`n`	the total number of observations of the data set.
`sig`	a numerical value representing the significance level of the test.
`distribution`	a distribution chosen between "normal", "poisson", "Student" or "Logistic".
`distance.type`	type of distance chosen from the family of distances. The different choices are given by: "Rho1", "Rho2", "Bertoluzza", "Rhop", "Delta.pq", "Mid/Spr", "wabl", "DSGD", "DSGD.G", "GSGD".
`i`	parameter of the density function of the Beta distribution, fixed by default to i = 1.
`j`	parameter of the density function of the Beta distribution, fixed by default to j = 1.
`theta`	a numerical value between 0 and 1, representing a weighting parameter. By default, theta is fixed to 1/3 referring to the Lebesgue space. This measure is used in the calculations of the following distances: d_Bertoluzza, d_mid/spr and d_phi-wabl/ldev/rdev.
`thetas`	a decimal value between 0 and 1, representing the weight given to the shape of the fuzzy number. By default, thetas is fixed to 1. This parameter is used in the calculations of the d_theta star and the d_GSGD distances.
`p`	a positive integer such that 1 ≤ p < infinity, referring to the parameter of the Rho_p and Delta_pq. By default, p is fixed to 2.
`q`	a decimal value between 0 and 1, referring to the parameter of the metric Delta_pq. By default, p is fixed to 0.5.
`breakpoints`	a positive arbitrary integer representing the number of breaks chosen to build the numerical alpha-cuts. It is fixed to 100 by default.
`plot`	a logical rule "TRUE" or "FALSE" for defining whether to plot the corresponding graphs or not.

Returns a list composed by the arguments, the fuzzy confidence intervals, the fuzzy decisions, the defuzzified values and the decision made.

H0 <- TriangularFuzzyNumber(2.9,3,3.1)
H1 <- TriangularFuzzyNumber(3,3,5)
res <- Fuzzy.CI.test(type = 0, H0, H1, t = TriangularFuzzyNumber(0.8,1.80,2.80), s.d = 0.79, 
n = 10, sig = 0.05, distribution = "normal", distance.type="GSGD")