@techreport{c2b1e4b9e1ee4bd1bc8a14cacbf2d758,
title = "Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models (Subsequently replaced by DP 2008-53)",
abstract = "Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on the nonnegative integers, called an immigration or innovation distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to belong to a parametric family. This paper instead considers a more realistic semiparametric INAR(p) model: essentially there are no restrictions on the innovation distribution. We provide an (semiparametrically) efficient estimator of the autoregression parameters and the innovation distribution.",
keywords = "count data, nonparametric maximum likelihood, infinite-dimensional Z-estimator, semiparametric efficiency",
author = "F.C. Drost and {van den Akker}, R. and B.J.M. Werker",
note = "Subsequently replaced by CentER DP 2008-53 Pagination: 38",
year = "2007",
language = "English",
volume = "2007-23",
series = "CentER Discussion Paper",
publisher = "Econometrics",
type = "WorkingPaper",
institution = "Econometrics",
}