𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Locally Adaptive Function Estimation for Binary Regression Models

✍ Scribed by Alexander Jerak; Stefan Lang

Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
358 KB
Volume
47
Category
Article
ISSN
0323-3847

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Variance Estimation for High-Dimensional
Variance Estimation for High-Dimensional Regression Models
✍ Vladimir Spokoiny πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 190 KB

The paper is concerned with the problem of variance estimation for a highdimensional regression model. The results show that the accuracy n -1/2 of variance estimation can be achieved only under some restrictions on smoothness properties of the regression function and on the dimensionality of the mo

Linear Least Squares Estimation of Regre
Linear Least Squares Estimation of Regression Models for Two-Dimensional Random Fields
✍ Guy Cohen; Joseph M. Francos πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 122 KB

We consider the problem of estimating regression models of two-dimensional random fields. Asymptotic properties of the least squares estimator of the linear regression coefficients are studied for the case where the disturbance is a homogeneous random field with an absolutely continuous spectral dis

Robust estimation for the Cox regression
Robust estimation for the Cox regression model based on trimming
✍ Alessio Farcomeni; Sara Viviani πŸ“‚ Article πŸ“… 2011 πŸ› John Wiley and Sons 🌐 English βš– 231 KB πŸ‘ 2 views

## Abstract We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis‐type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties