A new method was developed to better understand how nonparametric estimators work for analyzing time series data. Instead of the usual way of looking at the data, this new approach considers the truncation lag as a fixed proportion of the sample size. The results show that the accuracy of estimating the spectral density of the data depends on how the mean is calculated and removed. The findings suggest that this new method gives a more accurate approximation compared to the traditional approach.