Bibliography

(eng): The problem of non-parametric statistical modeling of 2-dimensional surfaces from observed data is studied. In general, the model is constructed from a set of basal functions, which means to estimate a number of parameters. We present two approaches allowing reduction of needed parameters, a well known method of projection pursuit and the less known method of Gordon surface. Further, we analyze consequences of sparse data to precision of model and uncertainty of prediction.