A dynamic count process
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Publication:6592803
DOI10.1016/j.jspi.2024.106187MaRDI QIDQ6592803
Yingcun Xia, Nam Hyun Kim, Pipat Wongsa-art
Publication date: 26 August 2024
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
quasi maximum likelihood estimationSETAR processdynamic count processfinite semiparametric exponential mixture
Cites Work
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- AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
- Log-linear Poisson autoregression
- Absolute regularity and ergodicity of Poisson count processes
- The geometry of mixture likelihoods, part II: The exponential family
- The geometry of mixture likelihoods: A general theory
- On the convergence properties of the EM algorithm
- The fractional calculus. Theory and applications of differentiation and integration to arbitrary order
- Efficient maximum likelihood estimation in semiparametric mixture models
- Nonlinear Poisson autoregression
- Consistency and limiting distribution of the least squares estimator of a threshold autoregressive model
- Theory and inference for a class of nonlinear models with application to time series of counts
- Maximum likelihood estimation of a generalized threshold stochastic regression model
- Poisson Autoregression
- Non-linear time series and Markov chains
- A negative binomial model for time series of counts
- A regression model for time series of counts
- Criteria for classifying general Markov chains
- Limiting properties of the least squares estimator of a continuous threshold autoregressive model
- A state space model for multivariate longitudinal count data
- On autocorrelation in a Poisson regression model
- Self-Excited Threshold Poisson Autoregression
- Mixtures of Nonlinear Poisson Autoregressions
- Count Time Series: A Methodological Review
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