Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued GARCH models

By Fukang Zhu. 2012

147 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/69858e567ce0f4b7cef7c3dae35689f15bf81943

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Citations in the corpus

Parameter change test for zero-inflated generalized Poisson autoregressive models (2016, background): “Remark 3 Ferland et al. [10] investigated the properties of Poisson-INGARCH(p, q) models; Doukhan and Kengne [32] considered the change point test problem for the model with λt = fθ (Yt−1, . . .); Zhu [35,36] verified the stationarity of ZIP-INGARCH(p, q) and GPINGARCH(p, q) models.”
Underdispersion models: Models that are “under the radar” (2017, methodology): “This model has been applied in the development of various statistical models including regressions (Famoye 1993), multivariate distributions (Famoye and Consul 1995), control chart theory (Famoye 2007), and time-series models (Zhu 2012a; Weiss 2013).”
Theory and inference for a class of nonlinear models with application to time series of counts (2016, background): “Zhu (2012a) considered the INGARCH with generalized Poisson as the conditional distribution.”
Infinitely Divisible Distributions in Integer‐Valued Garch Models (2015, unknown): “Replacing the distribution of deviates by other particular discrete ones, like negative binomial or generalized Poisson, analogous integer-valued GARCH models have been proposed and studied (Zhu, 2011, 2012a).”
Poisson QMLE of Count Time Series Models (2016, methodology): “Zhu (2012b) has shown that the expectation of the COM-Poisson distribution can be approximated by WDP1 kD1 k k .kŠ/ S. ; / ' 1 2 .”
Integer-valued autoregressive models for counts showing underdispersion (2013, methodology): “As the benchmark models, the equidispersed Poisson distribution as well as the underdispersed GP distribution (using the parametrization of [34]) were considered.”
Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator (2012, methodology): “observation-driven time series models in which the parameter depends solely the past observations. Examples of such models include Poisson integer-valued GARCH (INGARCH) (see Ferland et al. (2006) or Zhu (2012), Fokianos et al. (2009)), Poisson threshold models (see Henderson et al. (2011)), log-lin”