Time series regression for zero-inflated and overdispersed count data: a functional response model approach

DOI10.1007/s42519-020-00094-8zbMath1443.62257OpenAlexW3023973206MaRDI QIDQ777816

D. Kharzeev

Publication date: 7 July 2020

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42519-020-00094-8

zbMATH Keywords

time seriesoverdispersionregressionestimating functionzero-inflation

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional data analysis (62R10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12)

Related Items (2)

Zero-modified count time series with Markovian intensities ⋮ Autoregressive and moving average models for zero‐inflated count time series

Uses Software

• ZIM

Cites Work

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• Godambe estimating functions and asymptotic optimal inference
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• Testing for zero inflation and overdispersion in INAR(1) models
• The foundations of finite sample estimation in stochastic processes
• A regression model for time series of counts
• On autocorrelation in a Poisson regression model
• Fitting Nonlinear and Constrained Generalized Estimating Equations with Optimization Software
• State-space models for count time series with excess zeros
• Modern Applied U‐Statistics

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