| bibtype |
J -
Journal Article
|
| ARLID |
0410589 |
| utime |
20240903170614.1 |
| mtime |
20060210235959.9 |
| title
(primary) (eng) |
Combining forecasts using the least trimmed squares |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0297163 |
| ISSN |
0023-5954 |
| title
|
Kybernetika |
| volume_id |
37 |
| volume |
2 (2001) |
| page_num |
183-204 |
| publisher |
| name |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
|
| keyword |
robust regression |
| keyword |
forecast improvement |
| keyword |
high breakdown point |
| author
(primary) |
| ARLID |
cav_un_auth*0101225 |
| name1 |
Víšek |
| name2 |
Jan Ámos |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| COSATI |
12B |
| cas_special |
| project |
| project_id |
255/2000/A EK/FSV |
| agency |
GA UK |
| country |
CZ |
|
| research |
AV0Z1075907 |
| abstract
(eng) |
Employing recently derived asymptotic representation of the least trimmed squares estimator, the combination of the forecasts with constraints are studied. Under the assumption of unbiasedness of individual forecasts it is shown that the combination without intercept and with constraint imposed on the estimate of the regression coefficients that they sum to one, is better than others. A numerical example is included to support theoretical conclusions. |
| RIV |
BB |
| department |
SI |
| permalink |
http://hdl.handle.net/11104/0130678 |
| ID_orig |
UTIA-B 20010058 |
| arlyear |
2001 |
| mrcbU63 |
cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 37 č. 2 2001 183 204 Ústav teorie informace a automatizace AV ČR, v. v. i. |
|