I am looking for regression techniques which are similar to Kriging/Gaussian process regression, in that no explicit model needs to be specified. (Discounting the prior over functions) I have three independent variables and one dependent variable to which I want to apply such a procedure. The independent variables specify coordinates (locations in 3D), while the dependent variable specifies Wi-Fi signal strength at the given coordinates. Since it is hard to appropriately visualize such high dimensional data, techniques without explicit model dependence are of primary interest. The only similar technique I found was the somewhat unsophisticated Nearest-neighbour interpolation.
Are the above-mentioned techniques the only choices for such a problem?