Analyzing the full BINMA time series process using a robust GQL approach
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Publication:1695684
DOI10.1515/jtse-2015-0019zbMath1499.62310OpenAlexW2565452212MaRDI QIDQ1695684
Naushad Mamode Khan, Yuvraj Sunecher, Vandna Jowaheer
Publication date: 7 February 2018
Published in: Journal of Time Series Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/jtse-2015-0019
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Generalized linear models (logistic models) (62J12)
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Cites Work
- Remarks on asymptotic efficient estimation for regression effects in stationary and nonstationary models for panel count data
- Dynamic mixed models for familial longitudinal data
- Time series of count data: Modeling, estimation and diagnostics
- Discrete analogues of self-decomposability and stability
- An overview on regression models for discrete longitudinal responses
- Estimating time series models for count data using efficient importance sampling
- Bivariate Time Series Modeling of Financial Count Data
- Autoregressive moving-average processes with negative-binomial and geometric marginal distributions
- Miscellanea. On the efficiency of regression estimators in generalised linear models for longitudinal data
- Testing for serial dependence in time series models of counts
- REGRESSION IN THE BIVARIATE POISSON DISTRIBUTION
- FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
- Monte Carlo EM Estimation for Time Series Models Involving Counts
- Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives
- Conditional Heteroskedasticity in Count Data Regression: Self-Feeding Activity in Fish
- On generating multivariate Poisson data in management science applications
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