· 2017· Book chapter
Local Regression Models
- 497citations
- 2017year
Short summary
Loess, a local regression fitting method, allows users to specify error properties (Gaussian, symmetric), variance (constant, weighted), predictor behavior (locally linear, quadratic), and neighborhood size for data analysis.
AI-generated from the title and abstract; the full text is not read.
Key points
- Loess is a local regression fitting method for data analysis.
- Key specifications include error properties, variance, predictor behavior, and neighborhood size.
- Diagnostic checking is essential for validating loess model fits.
- The chapter demonstrates practical data analysis using S functions for loess.
AI-generated from the title and abstract; the full text is not read.
Abstract
Local regression models provide methods for fitting regression functions, or regression surfaces, to data. The chapter describes the specifications of a particular model determine the details of the method used to fit the model; the fitting method, which is called loess. It discusses the S functions and objects for local regression models by working through a number of examples. Our goal is to show how the data are analyzed in practice using S. This means we must discuss diagnostic methods. Thus, diagnostic checking is an essential part of the practice of fitting local regression models, and, as with all model building, omitting it results in demonstrated validity being replaced simply by hope. Thus, the fitting of local regression models involves making the following choices about the specification of properties of the errors and the regression surface. Properties are Gaussian or symmetric distribution; constant variance or a priori weights; locally linear or locally quadratic in numeric predictors; and neighborhood size.
The authors' abstract, as published at the source., 2017 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Analytical Chemistry
Analytical ChemistryChemistry