sse.fuzzy: Sum of Squares within treatments (Errors) for Triangular...

In ANOVA.TFNs: One-Way Analysis of Variance Based on Triangular Fuzzy Numbers

Description

This function calculate Sum of Squares Errors (SSE) for Triangular Fuzzy observation on the basis of m=1,2,3,... (Parchami et al., 2017, 2018).

Usage

sse.fuzzy(Data, m = 1)

Arguments

Data	a matrix with dim=c(n, 4) and FANOVA.Data format.
m	a positive integer number which related to the weight of distance between two cuts of fuzzy numbers, and its default is m=1. For more details see (Parchami et al., 2017, 2018).

See Also

FuzzyNumbers

Examples

# Example 1: 
data(Data)

sse.fuzzy( Data )   # For m=1 
sse.fuzzy( Data, m=2)

# Example 2  ( Checking relation  sst = sstr + sse  for different m):
sst.fuzzy(Data) == sstr.fuzzy(Data) + sse.fuzzy(Data)
sst.fuzzy(Data, m=3) == sstr.fuzzy(Data, m=3) + sse.fuzzy(Data, m=3)

for(m in 1:10) 
  print( round(sst.fuzzy(Data, m), 10) == round(sstr.fuzzy(Data, m) + sse.fuzzy(Data, m), 10) )

ANOVA.TFNs documentation built on May 1, 2019, 9:14 p.m.