Testing Serial Dependence in Time Series Models of Counts

By Robert C. Jung, A. Tremayne. 2000

47 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/91546d93cd0c397ea066319e00fef54ae17db66b

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Citations in the corpus

Analysis of low count time series data by poisson autoregression (2004, methodology): “See Freeland (1998) and Jung and Tremayne (2003) for specific tests of dependence in the PAR model.”
Binomial thinning models for integer time series (2006, background): “All these models have been considered extensively elsewhere, for example, Jung and Tremayne (2003, 2006) and Jung et al. (2005) for detailed references and also the articles by Brännäs and co-authors, including Brännäs and Hellström (2001) for a general article and Brännäs and Hall (2001), who are…”
Bayesian predictions of low count time series (2005, methodology): “…in the previous section using a generalization of the INAR(1) model for count time series introduced by Al-Osh and Alzaid (1987) and McKenzie (1988) and as further investigated by Ronning and Jung (1992), Brännäs (1994), Freeland and McCabe (2004a,b) and Jung and Tremayne (2003), amongst others.”
CUSUM Monitoring of First-Order Integer-Valued Autoregressive Processes of Poisson Counts (2009, methodology): “Recent reviews on advances in this field are provided by Knoth and Schmid (2004) and Psarakis and Papaleonida (2007). Distribution-based control charts may be applied to the original observations by adjusting the control limits to account for the autocorrelation or to the residuals after removing th”
Estimation in conditional first order autoregression with discrete support (2005, methodology): “This is exploited in Jung and Tremayne (2003) for testing purposes and will be utilized further in the estimation context of the present paper.”