This article uses wavelet theory to propose a frequency domain nonparametric and tuning parameter-free family of unit root tests. The proposed test exploits the wavelet power spectrum of the observed series and its fractional partial sum to construct a test of the unit root based on the ratio of the resulting scaling energies. The proposed statistic enjoys good power properties and is robust to severe size distortions even in the presence of serially correlated MA(1) errors with a highly negative moving average (MA) parameter, as well as in the presence of random additive outliers. Any remaining size distortions are effectively eliminated using a novel wavestrapping algorithm. 2016 Copyright © Taylor & Francis Group, LL
Cataloged from PDF version of article.Includes bibliographical references (leaves 83-87).Thesis (Ph....
In this paper, we propose a Nonlinear Dickey-Fuller F test for unit root against first order Logisti...
In this article a statistical procedure for identifying if a time series set follows the same model ...
This paper develops a wavelet (spectral) approach to test the presence of a unit root in a stochasti...
This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stocha...
Unit root tests typically suffer from low power, severe size distortions, and dependence on tuning p...
This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stocha...
This paper develops a wavelet (spectral) approach to test the presence of a unit root in a stochasti...
In the literature, there are no nonlinear wavelet-based unit root tests with structural breaks. To f...
This thesis consists of four essays linked with the use of wavelet methodologies in unit root testin...
Test for unit root based in wavelets theory is recently defined (Gençay and Fan, 2007). While the ne...
In this paper, we apply the wavelet methods in the popular Augmented Dickey-Fuller and M types of un...
URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/CESFramDP2008.htmDocuments de travail...
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, an...
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, an...
Cataloged from PDF version of article.Includes bibliographical references (leaves 83-87).Thesis (Ph....
In this paper, we propose a Nonlinear Dickey-Fuller F test for unit root against first order Logisti...
In this article a statistical procedure for identifying if a time series set follows the same model ...
This paper develops a wavelet (spectral) approach to test the presence of a unit root in a stochasti...
This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stocha...
Unit root tests typically suffer from low power, severe size distortions, and dependence on tuning p...
This paper develops a wavelet (spectral) approach to testing the presence of a unit root in a stocha...
This paper develops a wavelet (spectral) approach to test the presence of a unit root in a stochasti...
In the literature, there are no nonlinear wavelet-based unit root tests with structural breaks. To f...
This thesis consists of four essays linked with the use of wavelet methodologies in unit root testin...
Test for unit root based in wavelets theory is recently defined (Gençay and Fan, 2007). While the ne...
In this paper, we apply the wavelet methods in the popular Augmented Dickey-Fuller and M types of un...
URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/CESFramDP2008.htmDocuments de travail...
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, an...
This paper presents a family of simple nonparametric unit root tests indexed by one parameter, d, an...
Cataloged from PDF version of article.Includes bibliographical references (leaves 83-87).Thesis (Ph....
In this paper, we propose a Nonlinear Dickey-Fuller F test for unit root against first order Logisti...
In this article a statistical procedure for identifying if a time series set follows the same model ...