
Poisson QMLE for changepoint detection in general integervalued time series models
We consider together the retrospective and the sequential changepoint d...
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A general procedure for changepoint detection in multivariate time series
We consider the changepoint detection in multivariate continuous and in...
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Testing for Stochastic Order in IntervalValued Data
We construct a procedure to test the stochastic order of two samples of ...
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Empirical Likelihood for Change Point Detection in Autoregressive Models
Change point analysis has become an important research topic in many fie...
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αBall divergence and its applications to changepoint problems for Banachvalued sequences
In this paper, we extend a measure of divergence between two distributio...
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Hypothesis testing for populations of networks
It has become an increasingly common practice for scientists in modern s...
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Consistent nonparametric change point detection combining CUSUM and marked empirical processes
A weakly dependent time series regression model with multivariate covari...
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Epidemic changepoint detection in general integervalued time series
In this paper, we consider the structural change in a class of discrete valued time series, which the true conditional distribution of the observations is assumed to be unknown. The conditional mean of the process depends on a parameter θ^* which may change over time. We provide sufficient conditions for the consistency and the asymptotic normality of the Poisson quasimaximum likelihood estimator (QMLE) of the model. We consider an epidemic changepoint detection and propose a test statistic based on the QMLE of the parameter. Under the null hypothesis of a constant parameter (no change), the test statistic converges to a distribution obtained from a difference of two Brownian bridge. The test statistic diverges to infinity under the epidemic alternative, which establishes that the proposed procedure is consistent in power. The effectiveness of the proposed procedure is illustrated by simulated and real data examples.
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