On autocorrelation in a Poisson regression model

By Richard A. Davis, W. Dunsmuir, Ying Wang. 2000

155 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e4010d0dcf810fcf12fe2d7b691f6b001d7845ea

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Citations in the corpus

Parameter change test for zero-inflated generalized Poisson autoregressive models (2016, background): “,[7] Fahrmeir and Tutz,[8] and Jung et al.”
Count Time Series Models (2012, background): “Further detailed study of model (38) can be found in in Davis et al. (2000) where the authors address the problem of existence of the latent stochastic process {ξt} and derive the asymptotic distribution of the regression coefficients when the latter exist.”
Integer-valued moving average modelling of the number of transactions in stocks (2010, background): “is asymptotically χ2(K) distributed. Davis and Dunsmuir (2000) and Lobato,”
Parameter Change Test for Poisson Autoregressive Models (2014, methodology): “With regard to the analysis of the polio data, the detection of a decreasing trend has been a classical issue among researchers (Zeger, 1988; Chan & Ledolter, 1995; Kuk & Cheng, 1997; Davis et al., 2000; Fahrmeir & Tutz, 2001; Davis & Wu, 2009).”
Theory and inference for a class of nonlinear models with application to time series of counts (2016, unknown): “…that the observations follow a Poisson distribution conditioned on an accompanying intensity process that drives the dynamics of the models, e.g., Davis, Dunsmuir, and Wang (2000), Davis, Dunsmuir, and Streett (2003), Fokianos, Rahbek, and Tjøstheim (2009), Neumann (2011), Streett (2000) and…”
Parameter change test for random coefficient integer‐valued autoregressive processes with application to polio data analysis (2009, background): “With regard to the analysis of the polio data, the detection of a decreasing trend has been a classical issue (See Chan and Ledolter, 1995; Kuk and Cheng, 1997; Jorgensen et al., 1999; Fahrmeir and Tutz, 1994; Davis et al., 2000).”
MCMC for Integer‐Valued ARMA processes (2007, unknown): “One approach that has been taken to avoid such problems is given in Davis et al. (2000), where a Poisson regression model is used with a standard ARMAðp; qÞ time-series forming part of the underlying latent process.”
Bayesian causality test for integer‐valued time series models with applications to climate and crime data (2017, methodology): “Some samples of the generalized linear model approach, particularly that based on log-linear models, are in Zeger (1988), Davis et al. (2000) and Jung et al. (2006), whereas regression models with an intensity process are in Ferland et al. (2006) and Fokianos et al. (2009).”
A negative binomial integer‐valued GARCH model (2011, methodology): “The literature on observation-driven models include Zeger (1988) and Davis et al. (2000, 2003), which discussed Poisson log-linear regression models.”