Evaluation of Approximation of Fisher Information Matrix in Poisson Mixture Model using High Performance Computing
| dc.contributor.author | Ji, Qing | |
| dc.contributor.author | Gobbert, Matthias K. | |
| dc.contributor.author | Raim, Andrew | |
| dc.contributor.author | Neerchal, Nagaraj K. | |
| dc.contributor.author | Morel, Jorge G. | |
| dc.date.accessioned | 2023-10-12T18:33:15Z | |
| dc.date.available | 2023-10-12T18:33:15Z | |
| dc.description.abstract | • Fisher information matrix(FIM) is an essential part in the computation of maximum likelihood estimation(MLE) as well as in obtaining their standard errors • Computation of FIM is resource intensive in some widely used models such as mixture distributions • Neerchal and Morel(1993), Raim (2014), and Raim et. al.(2014) have provided approximations to the FIM • In this project, we apply this approximation idea to a mixture of two Poisson distributions • A program in C with MPI is designed to test the performance of our approximation under various selections of parameter values | en_US |
| dc.description.sponsorship | The hardware used in the computational studies is part of the UMBC High Performance Computing Facility (HPCF). The facility is supported by the U.S. National Science Foundation through the MRI program (grant nos. CNS0821258 and CNS1228778) and the SCREMS program (grant no. DMS0821311),with additional substantial support from the University of Maryland, Baltimore County (UMBC). See www.umbc.edu/hpcf for more information on HPCF and the projects using its resources. | en_US |
| dc.description.uri | http://hpcf-files.umbc.edu/research/posters/Neerchal_poster_QingJi_hpcf.pdf | en_US |
| dc.format.extent | 1 page | en_US |
| dc.genre | posters | en_US |
| dc.identifier | doi:10.13016/m2qm3x-xcmp | |
| dc.identifier.uri | http://hdl.handle.net/11603/30106 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Mathematics Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. | en_US |
| dc.rights | Public Domain Mark 1.0 | * |
| dc.rights.uri | http://creativecommons.org/publicdomain/mark/1.0/ | * |
| dc.title | Evaluation of Approximation of Fisher Information Matrix in Poisson Mixture Model using High Performance Computing | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0003-1745-2292 | en_US |
| dcterms.creator | https://orcid.org/0000-0002-4440-2330 | en_US |