Proposing a Test for 2-D White Noise

Pseudo-random number are different from the true random numbers. Testing on whether pseudo-random number generator (PRNG) is accurate is necessary because of the increasing need in the advantages of PRNG than the true ones. In this thesis, we use a new way that converts the one dimensional numbers in to two dimensional lattice, and testing whether the different lattices we generate follows the white noise or not. The method we used is called the maximum pseudo-likelihood estimator (MPLE), which is from Ising model. Finally we look at the results to see where the boundaries of our method lies.