ABSTRACT
This chapter introduces the probability plot, a tool often used to evaluate how well a cumulative distribution model matches observed data. It considers that a statistical model of the electromagnetic fields inside an overmoded enclosure, which drives the cable currents in a realistic way, must not only obey the same probability density function (pdf) as the measured fields; it must also obey the same local autocorrelation with respect to small spatial translation or frequency shift. The chapter then describes how the pdf of simulated cable-driving power-flux distribution densities may be matched to an arbitrarily selected pdf through filtering random numbers. Price el al. have published a thorough derivation of the physics and statistics leading to the anticipation of a chi square attribute in the squared fields or power fluxes. However, there is a simple approach that relies somewhat on intuition for reaching the same conclusion.
