DOC: Finding the best C value
In AnalyzeTS: Analyze Fuzzy Time Series

Description Usage Arguments Value Author(s) See Also Examples

Finding the best C value for Abbasov Mamedova and NFTS models according to DOC algorithm.

1 2	DOC(ts, n = 7, w = 7, D1 = 0, D2 = 0, error = 1e-06, k=500,r=13, CEF = "MSE",type="Abbasov-Mamedova", show.complete = TRUE, keyword)

`ts`	Univariate time series.
`n`	Number of fuzzy set.
`w`	The w parameter.
`D1,D2`	Two proper positive numbers.
`error`	Error of C value is finded by DOC algorithm, which compare the best C value really. Default error = 0.000001.
`k`	In each iteration of the algorithm, k+1 (or k or k-1) values of C will be considered. The k must be a integer and greater than 499, default k = 500.
`r`	Display results returned to the specified number of decimal places (default 13). (See `round2str` for details of r paramicter.)
`CEF`	One of the criterion to evaluate forecasting model, must be one of "ME","MAE" , "MPE", "MAPE", "MSE" (default), or "RMSE".
`type`	Model is choosed to predicts time series by fuzziness, type = "Abbasov-Manedova" (default) or type = "NFTS".
`show.complete`	If TRUE, a graph will appear showing the percentage completed.
`keyword`	A keyword help connecting from `GDOC` function to `Compare.Cs` function. User are not allowed to use parameter 'keyword'.

The best C value and CEF corresponding value.

Hong Viet Minh <hongvietminh@gmail.com>

Vo Van Tai <vvtai@ctu.edu.vn>

GDOC

1
2
3

#data(enrollment)
#DOC(enrollment,n=7,w=7,error=0.00001,CEF="MSE",type="Abbasov-Mamedova")
#DOC(enrollment,n=7,w=7,error=0.00001,CEF="MAPE",type="NFTS")

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