Regression Models for Time Series Analysis

By B. Ray. Technometrics, 2003

302 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e0b501859fc495c6bf67af4ac9224948e72d15c7

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In Statistics and Probability

Citations in the corpus

Some recent progress in count time series (2011, methodology): “Our point of view is primarily influenced by the generalized linear models (GLM) theory, see McCullagh and Nelder [2] for independent data and Kedem and Fokianos [3] for dependent data.”
Interventions in log-linear Poisson autoregression (2012, background): “Note that this is a major difference in the proposed methodology when compared to the Gaussian time series case, see Chen and Liu (1993) for instance.”
Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator (2012, methodology): “Among the models proposed so far, observation-driven models introduced by Cox (1981) plays an important role (see (Kedem and Fokianos, 2002, Chapter 4) for a comprehensive account and Tjøstheim (2012) for a recent survey).”
Hawkes and INAR($\infty$) processes (2015, methodology): “For INARMA time series, a moving-average part is added to the autoregressive part in the defining difference equations (2); see Fokianos and Kedem (2012).”
Kumaraswamy autoregressive moving average models for double bounded environmental data (2017, methodology): “Residuals are an important measure for determining whether the fitted model provides a good fit to the data (Kedem and Fokianos, 2002).”
QUASI‐LIKELIHOOD INFERENCE FOR NEGATIVE BINOMIAL TIME SERIES MODELS (2013, methodology): “…log-linear models for time series of counts include the works by Zeger and Qaqish (1988), Brumback et al. (2000), Fahrmeir and Tutz (2001), Kedem and Fokianos (2002), Davis et al. (2003), Jung et al. (2006) and more recently Fokianos and Tjøstheim (2011), Woodard et al. (2011) and Douc et…”
Binomial thinning models for integer time series (2006, methodology): “4, our approach to INMA(2) modelling follows McKenzie (1988), but any attempt to fit either of the other two feasible specifications of such a model from Brännäs and Hall (2001) fails for similar reasons.”
Absolute regularity and ergodicity of Poisson count processes (2011, methodology): “It is fulfilled, for example, by the conditional maximum likelihood estimator studied in Fokianos, Rahbek and Tjøstheim [17].”
Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity (2011, unknown): “The monographs of Kedem and Fokianos (2002) and McKenzie (2003) provided excellent overviews.”
Interventions in INGARCH processes (2010, unknown): “The form of the score test (12) depends upon the type of the outlier considered–see (3). For the general INGARCH(p, q) the first two conditions of Lemma 1 are assumed to hold since the region of ergodicity for such processes is still unknown. For the INGARCH(1,1) case, Fokianos et al. (2008) show th”
Integer‐Valued GARCH Process (2006, unknown): “…literature on the analysis of discrete time series is now available and is proving effective in statistical analysis (see MacDonald and Zucchini, 1997 2006 The Authors Journal compilation 2006 Blackwell Publishing Ltd. JOURNAL OF TIME SERIES ANALYSIS Vol. 27, No. 6 or Kedem and Fokanios, 2002).”
Count Time Series Models (2012, methodology): “…we resort to log-linear models for count time series; see Zeger and Qaqish (1988), Li (1994), MacDonald and Zucchini (1997), Brumback et al. (2000), Kedem and Fokianos (2002), Benjamin et al. (2003), Davis et al. (2003), Fokianos and Kedem (2004), Jung et al. (2006), Creal et al. (2008) and…”