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Statistics Colloquium : Dr. Timothy McMurry

Univ of Virginia

Location

Sherman Hall : 145

Date & Time

September 7, 2018, 11:00 am12:00 pm

Description

Title:  Time series inference and prediction through estimation of the autocovariance matrix

Abstract:  This talk addresses the problem of estimating the autocovariance matrix of a stationary process.  Under short range dependence assumptions, convergence rates are established for a gradually tapered version of the sample autocovariance matrix and for its inverse. The proposed estimator is formed by leaving the main diagonals of the sample autocovariance matrix intact while gradually down-weighting off-diagonal entries towards zero.  We then develop 3 applications for this estimator: (i) the Linear Process Bootstrap, a new time-series bootstrap; (ii) a new approach to optimal time series prediction; and (iii) a modification of the innovations algorithm which can be shown to produce a consistent estimate for the sequence of MA parameters.