Useful in modeling copy errors and waiting times
This distribution's moment-generating function is e raised to the product of m and quantity e to the x minus one, where m is its mean. One application of this distribution is to a construct requiring both independent increment and stationary increment assumptions. A related function based on the difference of variables following this distribution is named for Skellam and is useful in describing differences in the photon noise of two images. Fluctuation in one of its parameters is called shot noise, and its parameter denoted lambda describes both its mean and variance. Useful in modeling copy errors and waiting times, for 10 points, identify this distribution named after the Frenchman who introduced it.
This distribution's moment-generating function is e raised to the product of m and quantity e to the x minus one, where m is its mean.
{Poisson} distribution [or {Poissonian}; or {von Bortkiewicz} distribution early]