Description Details Author(s) References Examples
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
Package: | MCS |
Type: | Package |
Version: | 0.1.3 |
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.
Leopoldo Catania & Mauro Bernardi
Maintainer: Leopoldo Catania <leopoldo.catania@gmail.com>
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
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Superior Set Model created :
Rank_M v_M MCS_M Rank_R v_R MCS_R Loss
sGARCH-norm 4 0.8108405 0.6136 4 1.4124330 0.3696 0.0004042581
sGARCH-std 5 0.9670567 0.5040 5 3.1140463 0.0106 0.0004010655
sGARCH-ged 1 -1.3732854 1.0000 3 0.2171015 0.9940 0.0003986329
sGARCH-snorm 2 -1.3024221 1.0000 2 0.0837766 0.9998 0.0003982803
sGARCH-sstd 3 -0.4687476 1.0000 1 -0.0837766 1.0000 0.0003977886
p-value :
[1] 0.504
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