| bibtype |
M -
Monography Chapter
|
| ARLID |
0506939 |
| utime |
20240103222329.3 |
| mtime |
20190726235959.9 |
| DOI |
10.3390/e20120966 |
| title
(primary) (eng) |
Likelihood Ratio Testing under Measurement Errors |
| specification |
| page_count |
9 s. |
| book_pages |
344 |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0506938 |
| ISBN |
978-3-03897-936-4 |
| title
|
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
| page_num |
117-125 |
| publisher |
| place |
Basel |
| name |
MDPI |
| year |
2019 |
|
| editor |
|
|
| keyword |
measurement errors |
| keyword |
robust testing |
| keyword |
information theory |
| keyword |
robust optimization |
| keyword |
two-sample test |
| author
(primary) |
| ARLID |
cav_un_auth*0370844 |
| name1 |
Broniatowski |
| name2 |
M. |
| country |
FR |
|
| author
|
| ARLID |
cav_un_auth*0368969 |
| name1 |
Jurečková |
| name2 |
Jana |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| full_dept |
Department of Stochastic Informatics |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0263018 |
| name1 |
Kalina |
| name2 |
Jan |
| institution |
UIVT-O |
| full_dept (cz) |
Oddělení strojového učení |
| full_dept |
Department of Machine Learning |
| full_dept |
Department of Machine Learning |
| fullinstit |
Ústav informatiky AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA18-01137S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0370462 |
|
| abstract
(eng) |
We consider the likelihood ratio test of a simple null hypothesis (with density f0) against a simple alternative hypothesis (with density g0) in the situation that observations Xi are mismeasured due to the presence of measurement errors. Thus instead of Xi for i = 1, . . . , n, we observe Zi = Xi + √δVi with unobservable parameter δ and unobservable random variable Vi. When we ignore the presence of measurement errors and perform the original test, the probability of type I error becomes different from the nominal value, but the test is still the most powerful among all tests on the modified level. Further, we derive the minimax test of some families of misspecified hypotheses and alternatives. The test exploits the concept of pseudo-capacities elaborated by Huber and Strassen (1973) and Buja (1986). A numerical experiment illustrates the principles and performance of the novel test. |
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20206 |
| reportyear |
2020 |
| num_of_auth |
3 |
| mrcbC47 |
UIVT-O 10000 10100 10101 |
| mrcbC52 |
4 A 4a 20231122144140.3 |
| mrcbC55 |
UIVT-O BA |
| inst_support |
RVO:67985807 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0298067 |
| confidential |
S |
| arlyear |
2019 |
| mrcbTft |
\nSoubory v repozitáři: 506939-a.pdf |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0506938 New Developments in Statistical Information Theory Based on Entropy and Divergence Measures MDPI 2019 Basel 117 125 978-3-03897-936-4 |
| mrcbU67 |
Pardo L. 340 |
|