Change Detection in INARCH Time Series of Counts
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Publication:5280076
DOI10.1007/978-3-319-41582-6_4zbMath1366.62066OpenAlexW2519986650MaRDI QIDQ5280076
Simos G. Meintanis, Marie Hušková, Šárka Hudecová
Publication date: 20 July 2017
Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-41582-6_4
time series of countsempirical probability generating functionsequential monitoringinteger ARCH models
Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Sequential statistical analysis (62L10)
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Cites Work
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- Modelling time series of counts with overdispersion
- Decoupling change-point detection based on characteristic functions: methodology, asymptotics, subsampling and application
- Testing for the bivariate Poisson distribution
- A class of count models and a new consistent test for the Poisson distribution
- A goodness of fit test for the Poisson distribution based on the empirical generating function
- Recent and classical goodness-of-fit tests for the Poisson distribution
- A new weak dependence condition and applications to moment inequalities
- Compound Poisson INAR(1) processes: stochastic properties and testing for overdispersion
- Delay time in sequential detection of change
- Bootstrapping sequential change-point tests for linear regression
- Validation tests for the innovation distribution in INAR time series models
- On the use of estimating functions in monitoring time series for change points
- Extensions of some classical methods in change point analysis
- Weak dependence. With examples and applications.
- Observation-driven models for Poisson counts
- Bootstrap Procedures for Online Monitoring of Changes in Autoregressive Models
- Parameter Change Test for Poisson Autoregressive Models
- Poisson Autoregression
- Change‐point monitoring in linear models
- A Goodness‐of‐Fit Test for Integer‐Valued Autoregressive Processes
- Integer-Valued GARCH Process
- Bootstrapping Sequential Change-Point Tests
- A test of fit for lattice distributions
- A negative binomial integer-valued GARCH model
- Tests for time series of counts based on the probability-generating function
- Interventions in INGARCH processes
- Changepoints in times series of counts