AnalyzeTS (version 2.2)

fuzzy.ts2: Abbasov Mamedova model and FVD model

Description

Calculating fuzziness and forecast time series by fuzziness method according to Abbasov - Manedova (2010) and NFTS models.

Usage

fuzzy.ts2(ts, n = 7, w = 7, D1 = 0, D2 = 0, C = NULL, forecast = 5, 
r = 12, trace = FALSE, plot = FALSE, grid = FALSE, type = "Abbasov-Mamedova")

Arguments

ts

Univariate time series.

n

Number of fuzzy set.

w

The w parameter.

D1, D2

Two proper positive numbers.

C

A optional constant.

forecast

Number of points to forecast in future.

r

Display results returned to the specified number of decimal places (default 12). (See round2str for details of r paramicter.)

trace

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

type

Model is choosed to predicts time series by fuzziness, type = "Abbasov-Manedova" or type = "NFTS".

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 are returned as a list containing two components. When trace = FALSE, results are returned as a list containing two components.

References

Abbasov, A.M. and Mamedova, M.H., 2003. Application of fuzzy time series to population forecasting, Proceedings of 8th Symposion on Information Technology in Urban and Spatial Planning, Vienna University of Technology, February 25-March1, 545-552.

See Also

Gfuzzy.ts2

Examples

#data(enrollment)
#layout(1:2)
#NF.mod<-fuzzy.ts2(enrollment,n=7,w=7,C=0.0001,forecast=11,trace=TRUE,plot=TRUE,type="NFTS")
#AM.mod<-fuzzy.ts2(enrollment,n=5,w=5,C=0.01,forecast=5,plot=TRUE,type="Abbasov-Mamedova")
#NF.mod
#AM.mod

#Finding the best C value by DOC function
#Abbasov-Mamedova model
#str.C1<-DOC(enrollment,n=7,w=7,D1=0,D2=0,CEF="MAPE",type="Abbasov-Mamedova")
#C1<-as.numeric(str.C1[1])
#fuzzy.ts2(enrollment,n=7,w=7,D1=0,D2=0,C=C1,forecast=5,type="Abbasov-Mamedova")

#NFTS model
#str.C2<-DOC(enrollment,n=7,w=7,D1=0,D2=0,CEF="MAPE",type="NFTS")
#C2<-as.numeric(str.C2[1])
#fuzzy.ts2(enrollment,n=7,w=7,D1=0,D2=0,C=C1,forecast=5,type="NFTS")