GeneratorFuzzyNumbers {FuzzyResampling}

Generate initial sample using various random distributions.

Description

GeneratorFuzzyNumbers generates the random sample of trapezoidal fuzzy numbers using the various random distributions, using the functions from the stats package.

Usage

GeneratorFuzzyNumbers(
  n,
  originalRandomDist,
  parametersOriginalRD,
  increasesRandomDist,
  parametersIncreasesRD,
  supportLeftRandomDist,
  parametersSupportLeftRD,
  supportRightRandomDist,
  parametersSupportRightRD,
  increases = FALSE,
  ...
)

Arguments

n

Number of fuzzy trapezoidal numbers in the created sample.

originalRandomDist

Name of the random generator used to create the "true origin" of fuzzy trapezoidal number (as defined in stats package).

parametersOriginalRD

List of parameters required by the random generator used to create the "true origin" of fuzzy trapezoidal number.

increasesRandomDist

Name of the random generator used to create the increases of the core of fuzzy trapezoidal number (as defined in stats package).

parametersIncreasesRD

List of parameters required by the random generator used to create the increases of the core of fuzzy trapezoidal number.

supportLeftRandomDist

Name of the random generator used to create the increases of the left support of fuzzy trapezoidal number (as defined in stats package).

parametersSupportLeftRD

List of parameters required by the random generator used to create the increases of the left support of fuzzy trapezoidal number.

supportRightRandomDist

Name of the random generator used to create the increases of the right support of fuzzy trapezoidal number (as defined in stats package).

parametersSupportRightRD

List of parameters required by the random generator used to create the increases of the right support of fuzzy trapezoidal number.

increases

If TRUE is used, then the output fuzzy numbers are given in the form: left increment of the support, left end of the core, right end of the core, right increment of the support. Otherwise, the default value FALSE is used and the fuzzy numbers are given in the form: left end of the support, left end of the core, right end of the core, right end of the support.

...

Some additional parameters to pass to other functions.

Details

The procedure simulates the initial sample which consists of n trapezoidal fuzzy numbers. The "true origin" of each fuzzy number is independently drawn from the random distribution using originalRandomDist function from the stats package with the parameters defined by parametersOriginalRD. The same applies to the increases of the core (the function increasesRandomDist with the parameters parametersIncreasesRD is then used), the left increase of the support (the function supportLeftRandomDist with the parameters parametersSupportLeftRD, respectively), and the right increase of the support (the function supportRightRandomDist with the parameters parametersSupportRightRD, respectively).

Names of these generators for random probabilities and their respective parameters should be in the form required by stats package.

The output is given as a matrix. In each row, there is a single fuzzy number in one of the forms:

1. left end of the support, left end of the core, right end of the core, right end of the support, or

2. left increment of the support, left end of the core, right end of the core, right increment of the support.

To obtain this second form, the parameter increases=TRUE has to be used.

Value

This function returns matrix which consists of n trapezoidal fuzzy numbers. Each fuzzy number (four values) ia given as one row in this matrix.

References

Grzegorzewski, P., Hryniewicz, O., Romaniuk, M. (2020) Flexible resampling for fuzzy data based on the canonical representation International Journal of Computational Intelligence Systems, 13 (1), pp. 1650-1662

Grzegorzewski, P., Romaniuk, M. (2022) Bootstrapped Kolmogorov-Smirnov Test for Epistemic Fuzzy Data Information Processing and Management of Uncertainty in Knowledge-Based Systems Springer

See Also

GeneratorNExpUU

Other sampling functions: GeneratorNExpUU(), GeneratorNU()

Examples

# seed PRNG

set.seed(1234)

# generate 10 trapezoidal fuzzy numbers (the normal distribution for the "true origin",
# the exponential distribution for the increases of the core, and two different uniform
# distribution for the increases of the support)

GeneratorFuzzyNumbers(10,"rnorm",list(mean=0,sd=1),"rexp",list(rate=2),"runif",
                     list(min=0,max=0.6),"runif",list(min=0,max=1))