Ahmad, Ali and Francq, Christian (2014): Poisson qmle of count time series models.

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Abstract
Regularity conditions are given for the consistency of the Poisson quasimaximum likelihood estimator of the conditional mean parameter of a count time series. The asymptotic distribution of the estimator is studied when the parameter belongs to the interior of the parameter space and when it lies at the boundary. Tests for the significance of the parameters and for constant conditional mean are deduced. Applications to specific INAR and INGARCH models are considered. Numerical illustrations, on Monte Carlo simulations and real data series, are provided.
Item Type:  MPRA Paper 

Original Title:  Poisson qmle of count time series models 
Language:  English 
Keywords:  Boundary of the parameter space; Consistency and asymptotic normality; Integervalued AR and GARCH models; Nonnormal asymptotic distribution; Poisson quasimaximum likelihood estimator; Time series of counts. 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes 
Item ID:  59804 
Depositing User:  Christian Francq 
Date Deposited:  04 Jan 2015 21:12 
Last Modified:  27 Sep 2019 05:04 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/59804 