comparison between the methods estimate nonparametric and semiparametric transfer function model in time series the Using simulation
Abstract
The transfer function model the basic concepts in the time series. This model is used in the case of multivariate time series. As for the design of this model, it depends on the available data in the time series and other information in the series so when the representation of the transfer function model depends on the representation of the data In this research, the transfer function has been estimated using the style nonparametric represented in two method local linear regression and cubic smoothing spline method The method of semi-parametric represented use semiparametric single index model, With four proposals, , That the goal of this research is comparing the capabilities of the above mentioned method using simulation at sample sizes (n = 100,150,200) as it found that the estimated proposed( C.S.S-L.S.I) is the best among the studied capabilities.
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