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Modelling heavy-tailedness in count time series (Q2174735)

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Language	Label	Description	Also known as
English	Modelling heavy-tailedness in count time series	scientific article

Statements

scholarly article

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Modelling heavy-tailedness in count time series (English)

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Applied Mathematical Modelling

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publication date

27 April 2020

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zbMATH Keywords

count time series

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diagnostics

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generalized Poisson-inverse Gaussian

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heavy-tailedness

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\(h\)-step forecast

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maximum likelihood

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MaRDI profile type

MaRDI publication profile

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full work available at URL

https://doi.org/10.1016/j.apm.2020.02.001

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FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS

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Discrete analogues of self-decomposability and stability

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First‐order integer valued AR processes with zero inflated poisson innovations

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Inferential aspects of the zero-inflated Poisson INAR(1) process

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First order non-negative integer valued autoregressive processes with power series innovations

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On first-order integer-valued autoregressive process with Katz family innovations

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Extended Poisson INAR(1) processes with equidispersion, underdispersion and overdispersion

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Modeling time series of count with excess zeros and ones based on INAR(1) model with zero-and-one inflated Poisson innovations

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A new geometric first-order integer-valued autoregressive (NGINAR(1)) process

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Inference for INAR\((p)\) processes with signed generalized power series thinning operator

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Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued autoregressive processes

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An Introduction to Discrete‐Valued Time Series

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Beyond mean modelling: Bias due to misspecification of dispersion in Poisson‐inverse Gaussian regression

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Mixed Poisson INAR(1) processes

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Modelling heavy-tailed count data using a generalised Poisson-inverse Gaussian family

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Modelling of low count heavy tailed time series data consisting large number of zeros and ones

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Asymptotic properties of CLS estimators in the Poisson AR(1) model

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Analysis of low count time series data by poisson autoregression

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Maximum likelihood estimation of higher-order integer-valued autoregressive processes

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Efficient Estimation of Auto-Regression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(<i>p</i>) Models

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Estimation of Parameters in the NLAR(p) Model

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Predictive Model Assessment for Count Data

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Useful models for time series of counts or simply wrong ones?

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One mixed negative binomial distribution with application

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Selecting nonlinear time series models using information criteria

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Integer-valued autoregressive models for counts showing underdispersion

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On the performance of information criteria for model identification of count time series

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Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data

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A regression model for time series of counts

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A negative binomial model for time series of counts

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A negative binomial integer-valued GARCH model

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Parameter Change Test for Poisson Autoregressive Models

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Modelling Non-Stationary Multivariate Time Series of Counts via Common Factors

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Identifiers

zbMATH Open document ID

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10.1016/j.apm.2020.02.001

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:2174735

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