Reciprocal distribution

In probability and statistics, the reciprocal distribution, also known as the log-uniform distribution, is a continuous probability distribution. It is characterised by its probability density function, within the support of the distribution, being proportional to the reciprocal of the variable. In probability and statistics, the reciprocal distribution, also known as the log-uniform distribution, is a continuous probability distribution. It is characterised by its probability density function, within the support of the distribution, being proportional to the reciprocal of the variable. The reciprocal distribution is an example of an inverse distribution, and the reciprocal (inverse) of a random variable with a reciprocal distribution itself has a reciprocal distribution. The probability density function (pdf) of the reciprocal distribution is Here, a {displaystyle a} and b {displaystyle b} are the parameters of the distribution, which are the lower and upper bounds of the support, and log e {displaystyle log _{e}} is the natural log function (the logarithm to base e). The cumulative distribution function is A positive random variable X is log-uniformally distributed if the logarithm of X is uniform distributed, This relationship is true regardless of the base of the logarithmic or exponential function. If log a ⁡ ( Y ) {displaystyle log _{a}(Y)} is uniform distributed, then so is log b ⁡ ( Y ) {displaystyle log _{b}(Y)} , for any two positive numbers a , b ≠ 1 {displaystyle a,b eq 1} . Likewise, if e X {displaystyle e^{X}} is log-uniform distributed, then so is a X {displaystyle a^{X}} , where 0 < a ≠ 1 {displaystyle 0<a eq 1} . The reciprocal distribution is of considerable importance in numerical analysis as a computer’s arithmetic operations transform mantissas with initial arbitrary distributions to the reciprocal distribution as a limiting distribution.