Joint likelihood estimation and model order selection for outlier censoring
Abstract This study deals with the problem of outlier censoring from the secondary data in a radar scenario, where the number of outliers is unknown. To this end, a procedure consisting of joint likelihood estimation and statistical model order selection (MOS) is proposed. Since the maximum likeliho...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-06-01
|
| Series: | IET Radar, Sonar & Navigation |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/rsn2.12072 |
| _version_ | 1818065527527964672 |
|---|---|
| author | Seyed Mohammad Karbasi |
| author_facet | Seyed Mohammad Karbasi |
| author_sort | Seyed Mohammad Karbasi |
| collection | DOAJ |
| description | Abstract This study deals with the problem of outlier censoring from the secondary data in a radar scenario, where the number of outliers is unknown. To this end, a procedure consisting of joint likelihood estimation and statistical model order selection (MOS) is proposed. Since the maximum likelihood (ML) estimation of the outlier subset requires to solve a combinatorial problem, an approximate ML (AML) method is employed to reduce the complexity. Therefore, to determine the number of outliers, different MOS criteria based on likelihood function are applied. At the analysis stage, the performance of the proposed methods is assessed based on simulated data. The results highlight that the devised algorithms exhibit satisfactory performance with efficient complexity at the same time. |
| first_indexed | 2024-12-10T14:53:19Z |
| format | Article |
| id | doaj.art-317c4f8c101c4601ab860c265b7651c1 |
| institution | Directory Open Access Journal |
| issn | 1751-8784 1751-8792 |
| language | English |
| last_indexed | 2024-12-10T14:53:19Z |
| publishDate | 2021-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Radar, Sonar & Navigation |
| spelling | doaj.art-317c4f8c101c4601ab860c265b7651c12022-12-22T01:44:23ZengWileyIET Radar, Sonar & Navigation1751-87841751-87922021-06-0115656157310.1049/rsn2.12072Joint likelihood estimation and model order selection for outlier censoringSeyed Mohammad Karbasi0Department of Electrical Engineering Sharif University of Technology Tehran IranAbstract This study deals with the problem of outlier censoring from the secondary data in a radar scenario, where the number of outliers is unknown. To this end, a procedure consisting of joint likelihood estimation and statistical model order selection (MOS) is proposed. Since the maximum likelihood (ML) estimation of the outlier subset requires to solve a combinatorial problem, an approximate ML (AML) method is employed to reduce the complexity. Therefore, to determine the number of outliers, different MOS criteria based on likelihood function are applied. At the analysis stage, the performance of the proposed methods is assessed based on simulated data. The results highlight that the devised algorithms exhibit satisfactory performance with efficient complexity at the same time.https://doi.org/10.1049/rsn2.12072maximum likelihood estimationmodelling |
| spellingShingle | Seyed Mohammad Karbasi Joint likelihood estimation and model order selection for outlier censoring IET Radar, Sonar & Navigation maximum likelihood estimation modelling |
| title | Joint likelihood estimation and model order selection for outlier censoring |
| title_full | Joint likelihood estimation and model order selection for outlier censoring |
| title_fullStr | Joint likelihood estimation and model order selection for outlier censoring |
| title_full_unstemmed | Joint likelihood estimation and model order selection for outlier censoring |
| title_short | Joint likelihood estimation and model order selection for outlier censoring |
| title_sort | joint likelihood estimation and model order selection for outlier censoring |
| topic | maximum likelihood estimation modelling |
| url | https://doi.org/10.1049/rsn2.12072 |
| work_keys_str_mv | AT seyedmohammadkarbasi jointlikelihoodestimationandmodelorderselectionforoutliercensoring |