fuzzy.ts1: Chen, Sing, Heuristic and Chen-Hsu models

Description

Calculating fuzziness of time series with Chen (1996), Singh (2008), Heuristic (Huarng 2001) and Chen-Hsu (2004) models.

Usage

fuzzy.ts1(ts, n = 5, D1 = 0, D2 = 0, type = c("Chen", "Singh",
"Heuristic", "Chen-Hsu"), bin = NULL, trace = FALSE, plot = FALSE, grid = FALSE)

Arguments

Univariate time series.

Number of fuzzy set.

D1,D2

Two proper positive numbers.

type

Type of model.

bin

Point-bin values use to divide fuzzy stes for Chen-Hsu model. If bin=NULL (default) then function just inform information about fuzzy sets.

trace

Let trace=TRUE to print all of calculation results out to creen. Let trace=FALSE (default) to only print fuzzy series out to creen.

plot

Let plot=TRUE to paint graph of obsevation series and fuzzy series. Let plot=FLASE (default) to do not paint graph.

grid

If TRUE, a gray background grid is put on the graph.

Value

When trace = TRUE, results are returned as a list containing the following components. When trace = TRUE, results are returned as a list containing the following components.When trace = FALSE, results is a time series fitted by fuzzy time series model.

References

Chen, S.M., 1996. Forecasting enrollments based on fuzzy time series. Fuzzy Sets and Systems. 81: 311-319.

Chen, S.M. and Hsu, C.C., 2004. A New method to forecast enrollments using fuzzy time series. International Journal of Applied Science and Engineering, 12: 234-244.

Huarng, H., 2001. Huarng models of fuzzy time series for forecasting. Fuzzy Sets and Systems. 123: 369-386.

Singh, S.R., 2008. A computational method of forecasting based on fuzzy time series. Mathematics and Computers in Simulation. 79: 539-554

Examples

Run this code

#Print all of calculation results out to creen.
#par(mfrow=c(2,2))
#data(enrollment)
#fuzzy.ts1(enrollment,n=7,type="Chen",plot=TRUE,grid=TRUE)
#fuzzy.ts1(enrollment,n=7,type="Singh",plot=TRUE)
#fuzzy.ts1(enrollment,n=7,type="Heuristic",plot=TRUE,grid=TRUE)

#Only print fuzzy series out to creen.
#chen10<-fuzzy.ts1(lh,n=10,type="Chen")
#singh10<-fuzzy.ts1(lh,n=10,type="Singh")
#heuristic10<-fuzzy.ts1(lh,n=10,type="Heuristic")

#Useing ChenHsu.bin function to find divide point fuzzy set values.
#a<-fuzzy.ts1(lh,n=5,type="Chen-Hsu",plot=1)
#b<-ChenHsu.bin(a$table1,n.subset=c(1,2,1,1,1))
#chenhsu6<-fuzzy.ts1(lh,type="Chen-Hsu",bin=b,plot=1,trace=1)