Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods

Mair, Patrick and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911 and de Leeuw, Jan (2009) Isotone Optimization in R: Pool-Adjacent-Violators Algorithm (PAVA) and Active Set Methods. Journal of Statistical Software, 32 (5). pp. 1-24. ISSN 1548-7660

[img]
Preview
PDF
isotone.pdf
Available under License Creative Commons Attribution 3.0 Austria (CC BY 3.0 AT).

Download (593kB)

Abstract

In this paper we give a general framework for isotone optimization. First we discuss a generalized version of the pool-adjacent-violators algorithm (PAVA) to minimize a separable convex function with simple chain constraints. Besides of general convex functions we extend existing PAVA implementations in terms of observation weights, approaches for tie handling, and responses from repeated measurement designs. Since isotone optimization problems can be formulated as convex programming problems with linear constraints we then develop a primal active set method to solve such problem. This methodology is applied on specific loss functions relevant in statistics. Both approaches are implemented in the R package isotone. (authors' abstract)

Item Type: Article
Keywords: isotone optimization / PAVA / monotone regression / active set / R
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics > Hornik
Version of the Document: Published
Variance from Published Version: None
Depositing User: ePub Administrator
Date Deposited: 16 Oct 2013 12:57
Last Modified: 24 Oct 2019 13:41
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/49144/
URI: https://epub.wu.ac.at/id/eprint/3993

Actions

View Item View Item

Downloads

Downloads per month over past year

View more statistics