Efficient Estimation of Autoregression Parameters and Innovation Distributions forSemiparametric Integer-Valued AR(p) Models (Revision of DP 2007-23)

By F. C. Drost, Ramon van den Akker, B. Werker. 2008

88 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Poisson QMLE of Count Time Series Models (2016, methodology): “Since it is not obvious to compute the MLE of a parameterdriven model, several alternative techniques and algorithms have been proposed in the literature (e.g., Drost et al., 2009; Pavlopoulos and Karlis, 2008; Pedeli et al., 2014).”
Count Time Series Models (2012, background): “However, in a recent contribution, Drost et al. (2009) consider the problem of semiparametric maximum likelihood estimation for INAR(p) models.”
Some recent progress in count time series (2011, background): “10 who recently studied the problem of parametric and semiparametric maximum-likelihood estimation, respectively.”