Fuzzy.sample.mean {FuzzySTs} | R Documentation |
Calculates the fuzzy sample mean
Description
Calculates the fuzzy sample mean
Usage
Fuzzy.sample.mean(data.fuzzified, 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. |
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)
Fuzzy.sample.mean(mat)
[Package FuzzySTs version 0.3 Index]