AnalyzeTS (version 2.0)

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

Description

Calculates fuzziness of time series with Chen, Singh, Heuristic and Chen-Hsu.

Usage

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

Arguments

ts

Observation series.

n

Number of fuzzy set.

D1

A adequate value.

D2

A adequate value.

type

Type of model.

bin

Point 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.

Value

type

Name of fuzzy model.

table1

Information about fuzzy sets.

table2

Information about fuzzy series of Chen, Sing, Heuristic and Chen-Hsu models (in bin!=NUL).

accuracy

Information about 7 accuracy of forecasting 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

par(mfrow=c(2,2))
chen10<-fuzzy.ts1(lh,n=5,type="Chen",plot=TRUE)
singh10<-fuzzy.ts1(lh,n=5,type="Singh",plot=TRUE)
heuristic10<-fuzzy.ts1(lh,n=5,type="Heuristic",plot=TRUE)

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