Analysis of low count time series data by poisson autoregression

By R. Freeland, Brendan McCabe. 2004

183 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/f9399b65ac425f84fb12536923217d12b69d3c7d

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Citations in the corpus

Serial dependence and regression of Poisson INARMA models (2008, methodology): “This rich family includes the Poisson, the negative binomial, and even the generalized Poisson distribution, see Zhu and Joe (2003). It is, however, a disadvantage that in the latter two cases, the marginal distribution of the residuals is non-standard.”
A geometric time series model with dependent Bernoulli counting series (2013, unknown): “…and Alzaid (1987), Alzaid and Al-Osh (1988, 1990), Du and Li (1991), Al-Osh and Aly (1992), Franke and Subba Rao (1995), Latour (1997), Silva and Oliveira (2004), Freeland and McCabe (2004a, 2004b, 2005), Jung and Tremayne (2006), Weiß (2008a), Cui and Lund (2010) and Bakouch and Ristić (2010).”
Binomial thinning models for integer time series (2006, background): “Likelihood-based estimators are also studied by Freeland and McCabe (2004).”
Bayesian predictions of low count time series (2005, methodology): “Each component in (18) is evaluated using (15) and (17), with the appropriate adjustments made for the use of lead rather than lag notation, and for the fact that the predictive pmf is conditioned on the last value in the sample, yT .”
Flexible Bivariate INAR(1) Processes Using Copulas (2013, methodology): “Based on the definition of Freeland and McCabe (2004), Pedeli and Karlis (2011) distinguished between a set of residuals for the survival process r j 1t = j Xj t−1 − jXj t−1 and another for the innovation component r j 2t = Rjt − j , j = 1 2, of each one of the two series X1t X2t that comprise the B”
Model Selection, Estimation and Forecasting in INAR(p) Models: (2008, methodology): “So, generalising Freeland and McCabe (2004a), let k Xt k kXt k, t = p+1; :::; T , be the set of residuals for the kth thinning process and let "t be residual set for the arrivals component.”
A bivariate INAR(1) process with application (2011, methodology): “Freeland and McCabe (2004b) suggest Statistical Modelling 2011; 11(4): 325–349 instead the use of the median of this distribution which always lies in the support of the series and is therefore coherent.”
Efficient Estimation of Autoregression Parameters and Innovation Distributions forSemiparametric Integer-Valued AR(p) Models (Revision of DP 2007-23) (2008, unknown): “…Böckenholt (1999b), Berglund and Brännäs (2001), Brännäs and Hellström (2001), Rudholm (2001), Böckenholt (2003), Brännäs and Shahiduzzaman (2004), Freeland and McCabe (2004), Gourieroux and Jasiak (2004), and McCabe and Martin (2005); and Pickands III and Stine (1997) and Ahn et al.…”