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Mallows’ quasi-likelihood estimation for log-linear Poisson autoregressions

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>10/2016
<mark>Journal</mark>Statistical Inference for Stochastic Processes
Issue number3
Number of pages25
Pages (from-to)337-361
Publication StatusPublished
Early online date26/12/15
<mark>Original language</mark>English


We consider the problems of robust estimation and testing for a log-linear model with feedback for the analysis of count time series. We study inference for contaminated data with transient shifts, level shifts and additive outliers. It turns out that the case of additive outliers deserves special attention. We propose a robust method for estimating the regression coefficients in the presence of interventions. The resulting robust estimators are asymptotically normally distributed under some regularity conditions. A robust score type test statistic is also examined. The methodology is applied to real and simulated data.