The balanced discrete triplet Lindley model and its INAR(1) extension: properties and COVID-19 applications
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Publication:6636248
DOI10.1515/IJB-2022-0001MaRDI QIDQ6636248
Naushad A. Mamode Khan, Célestin C. Kokonendji, Masoumeh Shirozhan
Publication date: 12 November 2024
Published in: The International Journal of Biostatistics (Search for Journal in Brave)
Cites Work
- A Poisson INAR(1) model with serially dependent innovations
- A new geometric first-order integer-valued autoregressive (NGINAR(1)) process
- A zero-inflated geometric INAR(1) process with random coefficient.
- A combined geometric \(INAR(p)\) model based on negative binomial thinning
- Thinning operations for modeling time series of counts -- a survey
- Modelling with the novel INAR(1)-PTE process
- A new lifetime distribution and its power transformation
- Model-based INAR bootstrap for forecasting INAR\((p)\) models
- Modeling time series of counts with a new class of INAR(1) model
- Estimation in an Integer-Valued Autoregressive Process with Negative Binomial Marginals (NBINAR(1))
- Forecasting in INAR(1) model
- Autoregressive moving-average processes with negative-binomial and geometric marginal distributions
- Bootstrap predictive inference for ARIMA processes
- FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
- Thinning-based models in the analysis of integer-valued time series: a review
- Integer-valued autoregressive processes with prespecified marginal and innovation distributions: a novel perspective
- Extended Poisson INAR(1) processes with equidispersion, underdispersion and overdispersion
- An INAR(1) model based on the Pegram and thinning operators with serially dependent innovation
- Predictive Model Assessment for Count Data
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