Local asymptotic normality and efficient estimation for INAR(p) models
Integer-valued autoregressive (INAR) processes have been introduced to model non-negative integer-valued phenomena that evolve in time. The distribution of an INAR(p) process is determined by two parameters: a vector of survival probabilities and a probability distribution on the non-negative integers, called an immigration distribution. This paper provides an efficient estimator of the parameters, and in particular, shows that the INAR(p) model has the Local Asymptotic Normality property. Copyright 2008 The Authors. Journal compilation 2008 Blackwell Publishing Ltd
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Volume (Year): 29 (2008)
Issue (Month): 5 (09)
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References listed on IDEAS
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"Generic Uniform Convergence,"
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- Donald W.K. Andrews, 1990. "Generic Uniform Convergence," Cowles Foundation Discussion Papers 940, Cowles Foundation for Research in Economics, Yale University.
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- R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 701-722, 09.
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- Gourieroux, C. & Jasiak, J., 2004. "Heterogeneous INAR(1) model with application to car insurance," Insurance: Mathematics and Economics, Elsevier, vol. 34(2), pages 177-192, April. Full references (including those not matched with items on IDEAS)
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