This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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176
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Type:
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Contributed
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Date/Time:
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Monday, August 2, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract - #309438 |
Title:
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Second-Order Inference for Nonstationary Time Series
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Author(s):
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Han Xiao*+ and Weibiao Wu
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Companies:
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The University of Chicago and The University of Chicago
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Address:
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5734 S University Ave, Chicago, IL, 60637,
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Keywords:
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nonstationary time series ;
locally stationary time series ;
time varying covariance function ;
auto-covariance matrix ;
time varying spectra ;
nonparametric estimation
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Abstract:
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We consider the following causal representation of the locally stationary time series $X_i=G(i/n,\mathcal{F}_i)$, where $\mathcal{F}_i=(\epsilon_i,\epsilon_{i-1},\ldots)$ consists of infinitely many independent and identically distributed innovations, and $G:\,\mathbb{R}^\infty \times \mathbb{R} \rightarrow \mathbb{R}$ is a measurable function. We address three problems under this setting. (i) Estimation of the time varying covariance functions and asymptotic distributions of the estimates. (ii) Estimation of the auto-covariance matrices and the consistency in terms of the operator norm. (iii) Estimation of the time varying spectra and their asymptotics.
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