| bibtype |
J -
Journal Article
|
| ARLID |
0387176 |
| utime |
20240103201940.4 |
| mtime |
20130207235959.9 |
| title
(primary) (eng) |
On two flexible methods of 2-dimensional regression analysis |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0385694 |
| ISSN |
1803-9782 |
| title
|
ACC JOURNAL |
| volume_id |
18 |
| volume |
4 (2012) |
| page_num |
154-164 |
| publisher |
|
|
| keyword |
regression analysis |
| keyword |
Gordon surface |
| keyword |
prediction error |
| keyword |
projection pursuit |
| author
(primary) |
| ARLID |
cav_un_auth*0101227 |
| name1 |
Volf |
| name2 |
Petr |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GAP209/10/2045 |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0263360 |
|
| abstract
(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. |
| reportyear |
2013 |
| RIV |
BB |
| num_of_auth |
1 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0217949 |
| arlyear |
2012 |
| mrcbU63 |
cav_un_epca*0385694 ACC JOURNAL 1803-9782 Roč. 18 č. 4 2012 154 164 MDPI |
|