Weighted.fuzzy.mean {FuzzySTs}

Calculates the weighted fuzzy sample mean

Description

Calculates the weighted fuzzy sample mean

Usage

Weighted.fuzzy.mean(
  data.fuzzified,
  weight,
  breakpoints = 100,
  alphacuts = FALSE
)

Arguments

data.fuzzified

a fuzzification matrix constructed by a call to the function FUZZ or the function GFUZZ, or a similar matrix. No NA are allowed.

weight

a weighting vector of the same length of the fuzzification matrix. No NA allowed.

breakpoints

a positive arbitrary integer representing the number of breaks chosen to build the numerical alpha-cuts. It is fixed to 100 by default.

alphacuts

fixed by default to "FALSE". No alpha-cuts are printed in this case.

Value

If the parameter alphacuts="TRUE", the function returns a matrix composed by 2 vectors representing the numerical left and right alpha-cuts. For this output, is.alphacuts = TRUE. If the parameter alphacuts="FALSE", the function returns a trapezoidal fuzzy number given by the quadruple (p,q,r,s).

Examples

mat <- matrix(c(1,2,2,3,3,4,4,5), ncol =4)
w <- c(1,3)
Weighted.fuzzy.mean(mat, w)