Smoothing cubic normalized B splines are used in synthesizing a suboptimal algorithm for estimation on Bayes criteria, maximum likelihood, and a posteriori density without constraint on the gaussian behavior of the corresponding distribution densities. The potential accuracy of the algorithm is evaluated in accordance with the Cramer-Rao inequality.