With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

No credit card required

Chapter 7

Regression II

7.1 Introduction

In Chapter 4 we introduced rank-based fitting of linear models using Rfit. In this chapter, we discuss further topics for rank-based regression. These include high breakdown fits, diagnostic procedures, weighted regression, nonlinear models, and autoregressive time series models. We also discuss optimal scores for a family of skew normal distributions and present an adaptive procedure for regression estimation based on a family of Winsorized Wilcoxon scores.

Let $\mathbit{Y}={\left[{y}_{1},...{y}_{n}\right]}^{T}$ denote an n × 1 vector of responses. Then the matrix version of the linear model, (4.2), is

where $X={\left[{x}_{1},...,{x}_{n}\right]}^{T}$ is an n × p design matrix, and $\mathbit{e}={\left[{e}_{1},...,{e}_{n}\right]}^{T}$ is an n × 1 vector of error terms. Assume for ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

No credit card required