Empirical likelihood-based inference in Poisson autoregressive model with conditional moment restrictions
DOI10.1186/s13660-015-0725-1zbMath1333.62215OpenAlexW2103246747WikidataQ59434859 ScholiaQ59434859MaRDI QIDQ264921
De-Hui Wang, Cui-Xin Peng, Zhi-Wen Zhao
Publication date: 1 April 2016
Published in: Journal of Inequalities and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s13660-015-0725-1
asymptotic distributionempirical likelihoodconditional moment restrictionleast square estimatorPoisson autoregressive model
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Markov processes: estimation; hidden Markov models (62M05)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Large Sample Properties of Generalized Method of Moments Estimators
- Estimation and testing for a Poisson autoregressive model
- An empirical likelihood approach to quantile regression with auxiliary information
- Empirical likelihood ratio confidence regions
- Empirical likelihood and general estimating equations
- \(M\)-estimation and quantile estimation in the presence of auxiliary information
- Thinning operations for modeling time series of counts -- a survey
- Observation-driven models for Poisson counts
- On estimating distribution functions and quantiles from survey data using auxiliary information
- Inference for pth-order random coefficient integer-valued autoregressive processes
- An integer-valued pth-order autoregressive structure (INAR(p)) process
- Integer-Valued GARCH Process
- Variance Estimation Using Auxiliary Information
- Empirical likelihood ratio confidence intervals for a single functional
- Empirical likelihood estimation for finite populations and the effective usage of auxiliary information
This page was built for publication: Empirical likelihood-based inference in Poisson autoregressive model with conditional moment restrictions
