using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors

The wavelet shrink estimator is an attractive technique when estimating the nonparametric regressionfunctions, but it is very sensitive in the case of a correlation in errors. in this research, a polynomialmodel of low degree was used for the purpose of addressing the boundary problem in the waveletreduction in addition to using flexible threshold values in the case of correlation in errors as itdeals with those transactions at each level separately, unlike the comprehensive threshold valuesthat deal with all levels simultaneously, as (visushrink) methods, (false discovery rate) method,(improvement thresholding) and (sureshrink method), as the study was conducted on real monthlydata represented in the rates of theft crimes for juveniles in iraq, specifically the baghdad governorate,and the risk ratios about those crimes for the years 2008-2018, with a sample size of (128) (sureshrink)the study also showed an increase in the rate of theft crimes for juveniles in recent years.