Estimations of AR(p) Model using Wave Shrink

In this research, A proposed method was used to shrink the wavelet, in order to deals with the problem of noise (or contamination) that may encounter the time series data, and trying to find the best estimation for the parameters of the autoregressive model of order (p) by getting the least possible value (best value) of the estimated statistical criteria's values for the proposed models (of less contamination) as the final prediction error, loss function and The Mean Absolute Prediction Error, and comparing them with the estimated statistical criteria's for the autoregressive model from order (p) that estimated by the classical method.In the application side of the research, the analysis of the time series observations of the quantity of the annual rainfall in Erbil city for the period (1992-2007) was discussed depending on the use of MATLAB software, in addition to write code using MATLAB language.