Nonparametric Inference for Bioassay
| dc.contributor.advisor | Bhattacharya, Rabi N. | en_US |
| dc.contributor.author | Lin, Lizhen | |
| dc.creator | Lin, Lizhen | en_US |
| dc.date.accessioned | 2012-05-09T21:58:59Z | |
| dc.date.available | 2012-05-09T21:58:59Z | |
| dc.date.issued | 2012 | |
| dc.identifier.uri | http://hdl.handle.net/10150/222849 | |
| dc.description.abstract | This thesis proposes some new model independent or nonparametric methods for estimating the dose-response curve and the effective dosage curve in the context of bioassay. The research problem is also of importance in environmental risk assessment and other areas of health sciences. It is shown in the thesis that our new nonparametric methods while bearing optimal asymptotic properties also exhibit strong finite sample performance. Although our specific emphasis is on bioassay and environmental risk assessment, the methodology developed in this dissertation applies broadly to general order restricted inference. | |
| dc.language.iso | en | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. | en_US |
| dc.subject | Dose-response curve | en_US |
| dc.subject | Effective dosage curve | en_US |
| dc.subject | Mean integrated squared error | en_US |
| dc.subject | Monotone shape constrained curve estimation | en_US |
| dc.subject | Mathematics | en_US |
| dc.subject | Asymptotic optimality | en_US |
| dc.subject | Bioassay | en_US |
| dc.title | Nonparametric Inference for Bioassay | en_US |
| dc.type | text | en_US |
| dc.type | Electronic Dissertation | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | doctoral | en_US |
| dc.contributor.committeemember | Kennedy, Tom G. | en_US |
| dc.contributor.committeemember | Piegorsch, Walter W. | en_US |
| dc.contributor.committeemember | Watkins, Joseph C. | en_US |
| dc.contributor.committeemember | Bhattacharya, Rabi N. | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.discipline | Mathematics | en_US |
| thesis.degree.name | Ph.D. | en_US |
| refterms.dateFOA | 2018-04-26T18:24:00Z | |
| html.description.abstract | This thesis proposes some new model independent or nonparametric methods for estimating the dose-response curve and the effective dosage curve in the context of bioassay. The research problem is also of importance in environmental risk assessment and other areas of health sciences. It is shown in the thesis that our new nonparametric methods while bearing optimal asymptotic properties also exhibit strong finite sample performance. Although our specific emphasis is on bioassay and environmental risk assessment, the methodology developed in this dissertation applies broadly to general order restricted inference. |
