Evaluation of vectorization/parallelization techniques: application to nonparametric curve estimation

The simulation of statistical models in a computer is a fundamental aspect of research in the field of nonparametric curve estimation. Methods such as the FFT (Fast Fourier Transform) or WARP (Weighted Average of Rounded Points) have been developed and analysed for computer implementation of the different techniques in this realm, with the aim of reducing the computation time as much as possible. In this work we analyse two techniques with this objective. These are the vectorization of the source code in which the different algorithms are implemented, and their distributed execution. It can be observed that the vectorization of the programs can improve the results obtained with techniques such as the FFT or WARP, or, in some cases, can prevent the use of these.