Modeling and inference for multivariate time series of counts based on the INGARCH scheme
type: Item
instance of: scholarly article
title: Modeling and inference for multivariate time series of counts based on the INGARCH scheme
author: Sangyeol Lee
author: Dongwon Kim
author: Byungsoo Kim
published in: Computational Statistics and Data Analysis
publication date: 2022-10-17T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 7602494
zbMATH Keywords: multivariate time series of counts
zbMATH Keywords: MINGARCH model
zbMATH Keywords: QMLE
zbMATH Keywords: MDPDE
zbMATH Keywords: change point test
describes a project that uses: ZIM
MaRDI profile type: Publication
full work available at URL: j.csda.2022.107579
OpenAlex ID: W4286566125
cites work: Poisson QMLE of count time series models
cites work: FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
cites work: Robust and efficient estimation by minimising a density power divergence
cites work: Parametric Statistical Change Point Analysis
cites work: QUASI-LIKELIHOOD INFERENCE FOR NEGATIVE BINOMIAL TIME SERIES MODELS
cites work: Q4348180
cites work: A new bivariate integer-valued GARCH model allowing for negative cross-correlation
cites work: Bivariate integer-autoregressive process with an application to mutual fund flows
cites work: Theory and inference for a class of nonlinear models with application to time series of counts
cites work: A negative binomial model for time series of counts
cites work: Asymptotic properties of quasi-maximum likelihood estimators in observation-driven time series models
cites work: Integer-Valued GARCH Process
cites work: Interventions in INGARCH processes
cites work: Interventions in log-linear Poisson autoregression
cites work: Retrospective change detection for binary time series models
cites work: Poisson Autoregression
cites work: Multivariate count autoregression
cites work: Changepoints in times series of counts
cites work: Structural changes in autoregressive models for binary time series
cites work: Tests for Structural Changes in Time Series of Counts
cites work: First‐order integer valued AR processes with zero inflated poisson innovations
cites work: Minimum density power divergence estimator for Poisson autoregressive models
cites work: Parameter Change Test for Poisson Autoregressive Models
cites work: A robust approach for testing parameter change in Poisson autoregressive models
cites work: Robust estimation for zero-inflated poisson autoregressive models based on density power divergence
cites work: Robust estimation for general integer-valued time series models
cites work: The Cusum Test for Parameter Change in Time Series Models
cites work: Parameter change test for zero-inflated generalized Poisson autoregressive models
cites work: Test for parameter change based on the estimator minimizing density-based divergence meas\-ures
cites work: CUSUM test for general nonlinear integer-valued GARCH models: comparison study
cites work: Asymptotic normality and parameter change test for bivariate Poisson INGARCH models
cites work: A test for a change in a parameter occurring at an unknown point
cites work: A bivariate INAR(1) process with application
cites work: Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
cites work: A data-based method for selecting tuning parameters in minimum distance estimators
cites work: Choosing a robustness tuning parameter
cites work: An Introduction to Discrete‐Valued Time Series
cites work: Limit theorems for iterated random functions
cites work: Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued GARCH models
cites work: Zero-inflated Poisson and negative binomial integer-valued GARCH models
DOI: 10.1016/J.CSDA.2022.107579
description: scientific article; zbMATH DE number 7602494