random variable

Simulation of statistical mean and variance of normally distributed data $N_X(m_X,\sigma_X)$ transformed by nonlinear functions $g(X)=\cos X$, $e^X$ and their inverse functions $g^{-1}(X)=\arccos X$, $\ln X$

This paper presents analytical relationships for calculating statistical mean and variances of functions g(X)=cosX, eX, g1(X)=arccosX, lnX of transformation of a normally NX(mX,σX) distributed random variable.

Simulation of statistical mean and variance of normally distributed random values, transformed by nonlinear functions $\sqrt{|X|}$ and $\sqrt{X}$

This paper presents theoretical studies of formation regularities for the statistical mean and variance of normally distributed random values with the unlimited argument values subjected to nonlinear transformations of functions |X| and  X.  It is shown that for nonlinear square root transformation of a normally distributed random variable, the integrals of higher order mean n>1 satisfy the inequality ¯(y¯Y)n0.  On the basis of the theoretical research, the correct boundaries m,σ of error transfer for