Gfuzzy.ts2: Updating

In AnalyzeTS: Analyze Fuzzy Time Series

Description

Updating

Usage

Gfuzzy.ts2(ts, n = 7, w = 7, D1 = 0, D2 = 0, C = list(C1 = NULL, C2 = NULL), 
forecast = 5, plot = FALSE, grid = FALSE, type = "Abbasov-Mamedova")

Arguments

ts	Univariate time series.
n	A numeric vector where each element is number of fuzzy set.
w	A numeric vector where each element is w parameter.
D1, D2	Two proper positive numbers.
C	A list consiting 2 component C1 and C2 or a rusult object from GDOC function.
forecast	Number of points to forecast in future.
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" or both.

Details

Gfuzzy.ts2 function consider length(n)*length(w)*length(type) models combining from three parameter n, w and type, and then using fuzzy.ts2 function analyze for each submodel.

Value

A list with three component.

information	Explaining for lables in annotation on the graph also as name of columns in interpolate and forecast components.
interpolate, forecast	two data frame where each column is a time series interpolate and forecasted in future by fuzzy time series model corresponding.

Author(s)

Hong Viet Minh <[e-mail]>

Vo Van Tai <[e-mail]>

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

Using Gfuzzy.ts1 function in case only a fuzzy time series model.

Examples

#data(enrollment)
#g.C<-GDOC(enrollment,n=c(5,7,9),w=c(7,9),D1=0,D2=0,
#CEF="MSE",type=c("Abbasov-Mamedova","NFTS"))
#g.fuzzy1<-Gfuzzy.ts2(enrollment,n=c(5,7,9),w=c(7,9),D1=0,D2=0,C=g.C,forecast=5, 
#plot=1,grid=0,type=c("Abbasov-Mamedova","NFTS")) 

Example output

Loading required package: MASS
Loading required package: TSA

Attaching package: 'TSA'

The following objects are masked from 'package:stats':

    acf, arima

The following object is masked from 'package:utils':

    tar

Loading required package: TTR
Loading required package: tseries
Loading required package: urca

Attaching package: 'AnalyzeTS'

The following object is masked from 'package:base':

    pmax

AnalyzeTS documentation built on Dec. 9, 2019, 1:07 a.m.