Density Estimation using Entropy Maximization for Semi-continuous Data
| dc.contributor.author | Popuri, Sai K. | |
| dc.contributor.author | Neerchal, Nagaraj K. | |
| dc.contributor.author | Mehta, Amita | |
| dc.contributor.author | Mousavi, Ahmad | |
| dc.date.accessioned | 2020-12-15T17:00:16Z | |
| dc.date.available | 2020-12-15T17:00:16Z | |
| dc.date.issued | 2020-11-17 | |
| dc.description.abstract | Semi-continuous data comes from a distribution that is a mixture of the point mass at zero and a continuous distribution with support on the positive real line. A clear example is the daily rainfall data. In this paper, we present a novel algorithm to estimate the density function for semi-continuous data using the principle of maximum entropy. Unlike existing methods in the literature, our algorithm needs only the sample values of the constraint functions in the entropy maximization problem and does not need the entire sample. Using simulations, we show that the estimate of the entropy produced by our algorithm has significantly less bias compared to existing methods. An application to the daily rainfall data is provided. | 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. CNS-0821258, CNS-1228778, and OAC-1726023) and the SCREMS program (grant no. DMS-0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). See hpcf.umbc.edu for more information on HPCF and the projects using its resources. | en_US |
| dc.description.uri | https://arxiv.org/abs/2011.08475 | en_US |
| dc.format.extent | 19 pages | en_US |
| dc.genre | journal articles preprints | en_US |
| dc.identifier | doi:10.13016/m2raar-vrek | |
| dc.identifier.citation | Sai K. Popuri, Nagaraj K. Neerchal, Amita Mehta and Ahmad Mousavi, Density Estimation using Entropy Maximization for Semi-continuous Data, https://arxiv.org/abs/2011.08475 | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/20262 | |
| 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.relation.ispartof | UMBC Joint Center for Earth Systems Technology (JCET) | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | |
| dc.title | Density Estimation using Entropy Maximization for Semi-continuous Data | en_US |
| dc.type | Text | en_US |