In this chapter, based on the criteria of BIAS (bias) and RMSE (root mean squared error), we examine the nonlinear filters introduced and developed in the previous chapters. Monte-Carlo experiments are performed in Section 5.2. There, each nonlinear filter is compared using various types of nonlinear functions. One set of data yt and αt for t=l,...,T is artificially simulated and, given yt, each filtering estimate of αt is compared with the artificially simulated αt. This procedure is performed 1000 times (i.e., 1000 sets of data are generated) and BIAS and RMSE between the estimated αt and the simulated one are computed for each time t.