0387176 20240103201940.420130207235959.9 11 s. cav_un_epca*03856941803-9782184 (2012)154-164MDPI regression analysis Gordon surface prediction error projection pursuit cav_un_auth*0101227 Volf Petr Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Department of Stochastic Informatics Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/SI/volf-on two flexible methods of 2-dimensional regression analysis.pdf GAP209/10/2045 GA ČR CZ cav_un_auth*0263360 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. 2013 BB 1 RVO:67985556 http://hdl.handle.net/11104/0217949 2012 cav_un_epca*0385694 ACC JOURNAL 1803-9782 Roč. 18 č. 4 2012 154 164 MDPI