A geometric time series model with inflated-parameter Bernoulli counting series

DOI10.1016/j.spl.2016.08.012zbMath1398.62222OpenAlexW2516406894MaRDI QIDQ334058

Fabio Fajardo Molinares, Patrick Borges, Marcelo Bourguignon

Publication date: 31 October 2016

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.08.012

zbMATH Keywords

estimation\(\rho\)-binomial thinning\(\rho\)-GINAR(1) processinflated-parameter Bernoulli distribution

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Point estimation (62F10)

Related Items (11)

A new thinning-based \(\mathrm{INAR}(1)\) process for underdispersed or overdispersed counts ⋮ Fractional approaches for the distribution of innovation sequence of INAR(1) processes ⋮ Extended binomial AR(1) processes with generalized binomial thinning operator ⋮ Portmanteau tests for generalized integer-valued autoregressive time series models. Portmanteau tests for GINAR models ⋮ Regularized estimation in GINAR(\(p\)) process ⋮ Penalized empirical likelihood inference for the GINAR(p) model ⋮ A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases ⋮ Alternative procedures in dependent counting INAR process with application on COVID-19 ⋮ A time series model based on dependent zero inflated counting series ⋮ A new geometric INAR(1) process based on counting series with deflation or inflation of zeros ⋮ Flexible INAR(1) models for equidispersed, underdispersed or overdispersed counts

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