Numerical estimation of basic arithmetical operations on bounded random variables

Abstract The objective of the study is estimating probability density functions of arithmetic operations on random variables. There are many methods that use specific parametrical and non-parametrical models in order to obtain accurate results. However, there are not many studies on speed of convergence and computation complexity of these methods.

This paper introduces a new method of estimation used to obtain results on bounded random variables. The method is based on a new publication provided by Jaroszewicz and Korzen (2012). The algorithm uses numerical analysis techniques such as numerical integration and curve interpolation. Author’s method is compared to the well-known Monte Carlo method.

Keywords Random Variables, Arithmetical operations, Numerical integration, Curve Interpolation, Monte Carlo Method, Convergence.

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