Discrete Wavelet Transform in Improving Estimation Accuracy

  • S. Al Wadi


It is well known that the simplest way of estimation of statistical parameters is the method of least squares using linear functions. However, the problem with this method is in how to find out a linear observations. estimation accuracy is very important concept in many field such that, medicine, humanities, engineering, industry, economics and others since an unbiased vision is crucial in order to support the industry for decision making, also suitable data to obtain is, how estimates are completed, what factors encourage the choice of estimation methods and the current level of estimation accuracy. Therefore, this articlepurposesa novel technique in field of improving inferences about population characteristic estimation, mathematical models were implemented in content of stock market data are collected from Amman stock exchange (ASE). Estimation accuracy directly will be implemented and Daubechies Wavelet transform (DWT) combined with interval estimation accuracy will be calculated also. Themethodology aims to compare the accuracy level between the interval estimation accuracy directly and the accuracy that calculated using DWT combined with interval estimation. The results show that DWT improves the estimation accuracy in content of stock market data. Therefore, the DWT combines with traditional estimation accuracy is better than traditional estimation accuracy directly. The results are implemented using (SPSS) and MATLAB.

How to Cite
AL WADI, S.. Discrete Wavelet Transform in Improving Estimation Accuracy. Current Science, [S.l.], v. 114, n. Issue 7, dec. 2017. ISSN 0011-3891. Available at: <http://currentscience.org/index.php/CS/article/view/177>. Date accessed: 24 jan. 2018.