Model Confidence Set procedure

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Description

Perform the Model Confidence Set procedure of Hansen et.al (2011) for a given set of loss series belonging to several different models that should be compared

Details

Package: MCS
Type: Package
Version: 0.1.0
Date: 2014-07-27
License: GPL-2

The R package MCS aims to implement the Model Confidence Set (MCS) procedure recently developed by Hansen et al. (2011). The Hansen's procedure consists on a sequence of tests which permits to construct a set of 'superior' models, where the null hypothesis of Equal Predictive Ability (EPA) is not rejected at a certain confidence level. The EPA statistic tests is calculated for an arbitrary loss function, meaning that we could test models on various aspects, for example punctual forecasts.

Author(s)

Leopoldo Catania & Mauro Bernardi

Maintainer: Leopoldo Catania <leopoldo.catania@gmail.com>

References

Hansen PR, Lunde A, Nason JM (2011). The model confidence set. Econometrica, 79(2), 453-497. Bernardi M. and Catania L. (2014) The Model Confidence Set package for R. URL http://arxiv.org/abs/1410.8504

Examples

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## Not run: 
library(MCS)
data(Loss)
MCS <- MCSprocedure(Loss=Loss[,1:5],alpha=0.2,B=5000,statistic='Tmax',cl=NULL)

## End(Not run)