THE USE OF THE SHRINKAGE WAVELET TRANSFORMS IN ESTIMATING THE INTEREST RATE ON LONG-TERM LOANS USING DIFFERENT THRESHOLD RULES WITH APPLICATION

Abstract

Wavelet transform applications began to enter the field of statistics as a powerful tool in the field of data smoothing. Considering the wavelet method in statistical estimations is one of the very powerful methods that were spread by the Estimators Wavelet Shrinkage (where wavelet shrinkage is a method or method for removing signal distortion (Signal) based on On the idea of performing Thresholding for the wavelet coefficients and resulting by applying the wavelet transformation, Donoho and others suggested estimation methods for the wavelet regression function. On long-term loans, these methods are the soft threshold, Carrot threshold, and the first improved threshold, in addition to taking the value of the Visushrink threshold, where simulation experiments were used using three test functions at a sample size (64) and noise ratios (5), in general, it shows the superiority of the estimation methods using the value of The visu soft threshold is followed by the improved visu garot method using the visu threshold value. Lamy uses a soft threshold rule and it is more explanatory because the data has a non-linear model