Robust Designs in Generalized Linear Models: A Quantile Dispersion Graphs Approach |
| |
Authors: | I Das M Aggarwal |
| |
Institution: | 1. Department of Statistics, Kumaun University, SSJ Campus Almora, Almora, India;2. Department of Mathematical Sciences, University of Memphis, Memphis, Tennessee, USA |
| |
Abstract: | This article studies design selection for generalized linear models (GLMs) using the quantile dispersion graphs (QDGs) approach in the presence of misspecification in the link and/or linear predictor. The uncertainty in the linear predictor is represented by a unknown function and estimated using kriging. For addressing misspecified link functions, a generalized family of link functions is used. Numerical examples are shown to illustrate the proposed methodology. |
| |
Keywords: | Family of link functions Kriging Logistic link Parameter orthogonality Standardization |
|
|