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A comparison of methods for bootstrapping in the local level model
Author(s) -
Franco Glaura C.,
Souza Reinaldo C.
Publication year - 2002
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.814
Subject(s) - bootstrapping (finance) , series (stratigraphy) , hyperparameter , parametric statistics , inference , monte carlo method , computer science , bootstrap model , prediction interval , statistical inference , confidence interval , mathematics , statistics , econometrics , algorithm , artificial intelligence , boson , paleontology , physics , particle decay , particle physics , biology
Bootstrap in time series models is not straightforward to implement, as in this case the observations are not independent. One of the alternatives is to bootstrap the residuals in order to obtain the bootstrap series and thus use these series for inference purposes. This work deals with the problem of assessing the accuracy of hyperparameters in structural models. We study the simplest case, the local level model, where the hyperparameters are given by the variances of the disturbance terms. As their distribution is not known, we employ the bootstrap to approximate the true distribution, using parametric and non‐parametric approaches. Bootstrap standard deviations are computed and their performances compared to the asymptotic and empirical standard errors, calculated using a Monte Carlo simulation. We also build confidence intervals to the hyperparameters, using four bootstrap methods and the results are compared by means of the length, shape and coverage probabilities of the intervals. Copyright © 2002 John Wiley & Sons, Ltd.