GDOC: Finding the best C values
In AnalyzeTS: Analyze Fuzzy Time Series

Description Usage Arguments Details Value Author(s) See Also Examples

Finding the best C values for more Abbasov Mamedova and NFTS models according to DOC algorithm at the same time.

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

`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.
`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`	A character vector where each element is choosing model to predicts time series by fuzziness, type = "Abbasov-Manedova" (default) or type = "NFTS" or both.
`show.complete`	If TRUE, a graph will appear showing the percentage completed.

GDOC function consider length(n)*length(w)*length(type) models combining from three parameter n, w and type, and then using DOC function finding the best C values forone by models.

A list contain two components where the first component is the best C values of Abbasov-Mamedova models and the second component is the best C values of NFTS models.

Hong Viet Minh <hongvietminh@gmail.com>

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

Using DOC function in case only a Abbasov-Mamedova or NFTS model.