Outlier detection algorithms for least squares time series regression
Bent Nielsen – Professor at Department of Economics at University of Oxford

We review recent asymptotic results on some robust methods for time series regression. The methods classify observations as outliers or not. From the asymptotic results we establish a new asymptotic theory for the gauge of these methods, which is the expected frequency of falsely detected outliers. The asymptotic theory involves Poisson exceedence theory.

Download:Nuffield Discussion Paper 2014-W04 & Method implemented in R-package ForwardSearch.


Bent Nielsen

1997 Ph.D. in mathematical statistics from University of Copenhagen.
Since then based in Oxford.
Work with time series econometrics

 

“Shifts in the macro economic are a kind of extreme events. I work on outlier detection methods and calibrate them using extreme event theory.”

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