flr: Fuzzy Linear Regression

Description Usage Arguments Author(s) Examples

Description

It gives the estimates of fuzzy regression by using the method of least squares.

Usage

1
flr(Y,X,type)

Arguments

type

is model to be used (1 or 2)

x

is an input fuzzy number

y

is an output fuzzy number

1

"Fuzzy output, Fuzzy input and Fuzzy Parameters"

2

"Fuzzy output, Crisp input and Fuzzy Parameters"

Author(s)

Mohsin Shahzad

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
If given Triangular Fuzzy NUmber

x_left<-c(1.5,3.0,4.5,6.5,8.0,9.5,10.5,12.0)
x_centre<-c(2.0,3.5,5.5,7.0,8.5,10.5,11.0,12.5)
x_right<-c(2.5,4.0,6.5,7.5,9.0,11.5,11.5,13.0)

y_left<-c(3.5,5.0,6.5,6.0,8.0,7.0,10.0,9.0)
y_centre<-c(4.0,5.5,7.5,6.5,8.5,8.0,10.5,9.5)
y_right<-c(4.5,6.0,8.5,7.0,9.0,9.0,11.0,10.0)

X<-cbind(x_left,x_centre,x_right)
Y<-cbind(y_left,y_centre,y_right)

flr(Y,X,type=1)

MohsinFuzzy/FuzzReg documentation built on May 25, 2019, 12:24 p.m.