This study proposes the model for interpolating time series to use them  to forecast effectively for future. This model is established based on the improved fuzzy clustering analysis problem, which is implemented by the Matlab procedure. The proposed model is illustrated by a data set and tested for many other datasets, especially for 3003 series in  M3-Competition data. Comparing  to the exist...

Count time series are widely encountered in practice. As with continuous valued data, many count have seasonal properties. This paper uses a recent advance stationary to develop general modeling paradigm. The model constructed here permits any marginal distribution for the and most flexible autocorrelations possible, including those negative dependence. Likelihood methods of inference explored....