Research Communication | Open Access
Volume 2019 | Communication ID 275
Volume 2019 | Communication ID 275
| Statistical inverse problem and it's application to health data |
Youssef Hbid, Abdel Douiri, Mohamed Khaladi
Received |
Accepted |
Published |
Feb 07, 2019 |
Feb 26, 2019 |
Mar 01, 2019 |
Abstract: Regression modelling is a powerful statistical tool often used in clinical trials and epidemiological studies. In this presentation, we formulate the estimates of the regression problem as a solution of the statistical inverse problem [1] that measures the discrepancy between the target outcome and the data produced by representation of the modelled predictors. This approach could simultaneously perform variable selection and coefficient estimation. Inspired by Huber’s robust statistics framework, we propose an extension to l1-penalized [2] regression problem. References [1] Douiri A ...