AnalyzeTS (version 2.0)

fuzzy.ts3: Improve Abbasov Mamedova version 1 model

Description

Predicts time series by fuzziness method according to improve Abbasov-Manedova model.

Usage

fuzzy.ts3(ts, n = 7, w = 7, D1 = 0, D2 = 0, C = NULL, forecast = 5, 
fty = c("ts", "f"), trace = FALSE, plot = FALSE)

Arguments

ts

Observation series.

n

Number of fuzzy set.

w

'w' parameter.

D1

A adequate value.

D2

A adequate value.

C

A optional constant.

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.

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.

fty

fty="f", N(length(ts)) = N(length(ts)-1) + V(length(ts)+1).

fty="ts", N(length(ts)) = ts(length(ts)) + V(length(ts)+1).

Value

type

Name of fuzzy model.

table1

Information about changing fuzzy sets.

table2

Observation series and changing series.

table3

The change fuzzy of observation series.

table4

Interpolate values.

table5

Forecasting values.

table6

The change fuzzy of forecasting series.

timeseries

Forecasting timeseries.

accuracy

Information about 6 accuracy of forecasting model.

References

Vo Van Tai, Duong Ton Dam, Pham Minh Truc, Dang Kien Cuong, 2016. Forecasting crest of sanility at three main stations of Ca Mau province by fuzzy time series model.

See Also

fuzzy.ts2

Examples

data(sanility)
fuzzy.ts3(sanility,n=7,w=4,C=0.01,forecast=5,fty="f",plot=TRUE,trace=1)
fuzzy.ts3(sanility,n=5,w=5,C=0.01,forecast=5,fty="ts")