nielsaka/modelconf: Estimation of Model Confidence Sets

This package offers an implementation of the algorithms developed by Hansen, Lunde and Nason (2011). The authors introduce the notion of a model confidence set (MCS) to account for the degree of uncertainty surrounding model selection. In analogy to confidence intervals for population parameters, the MCS methodology estimates a set of models that is expected to contain the best model(s) with a given probability.

Getting started

Package details

LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
nielsaka/modelconf documentation built on May 9, 2019, 7:35 p.m.