Robust mixture linear EIV regression models by t-distribution
| dc.contributor.author | Liu, Yantong | |
| dc.date.accessioned | 2012-12-10T14:30:52Z | |
| dc.date.available | 2012-12-10T14:30:52Z | |
| dc.date.graduationmonth | December | |
| dc.date.issued | 2012-12-10 | |
| dc.date.published | 2013 | |
| dc.description.abstract | A robust estimation procedure for mixture errors-in-variables linear regression models is proposed in the report by assuming the error terms follow a t-distribution. The estimation procedure is implemented by an EM algorithm based on the fact that the t-distribution is a scale mixture of normal distribution and a Gamma distribution. Finite sample performance of the proposed algorithm is evaluated by some extensive simulation studies. Comparison is also made with the MLE procedure under normality assumption. | |
| dc.description.advisor | Weixing Song | |
| dc.description.degree | Master of Science | |
| dc.description.department | Department of Statistics | |
| dc.description.level | Masters | |
| dc.identifier.uri | http://hdl.handle.net/2097/15157 | |
| dc.language.iso | en_US | |
| dc.publisher | Kansas State University | |
| dc.rights | © the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.subject | Robust estimation | |
| dc.subject | Linear errors-in-variables model | |
| dc.subject | EM algorithm | |
| dc.subject | Mixture | |
| dc.subject | T-distribution | |
| dc.subject.umi | Statistics (0463) | |
| dc.title | Robust mixture linear EIV regression models by t-distribution | |
| dc.type | Report |
