Results 1 to 10 of about 425,494 (113)
Partial Autocorrelation Diagnostics for Count Time Series [PDF]
Entropy, 2023 In a time series context, the study of the partial autocorrelation function (PACF) is helpful for model identification. Especially in the case of autoregressive (AR) models, it is widely used for order selection.
Christian H. Weiß +3 more
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State Space Modeling of Event Count Time Series [PDF]
Entropy, 2023 This paper proposes a class of algorithms for analyzing event count time series, based on state space modeling and Kalman filtering. While the dynamics of the state space model is kept Gaussian and linear, a nonlinear observation function is chosen.
Sidratul Moontaha +2 more
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Multivariate epidemic count time series model. [PDF]
PLoS ONE, 2023 An infectious disease spreads not only over a single population or community but also across multiple and heterogeneous communities. Moreover, its transmissibility varies over time because of various factors such as seasonality and epidemic control ...
Shinsuke Koyama
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ZOTMPo–INAR(1) Process: Entropy and Modeling of Epidemiological Count Time Series Data [PDF]
EntropyIn this article, we propose a first-order integer-valued autoregressive (INAR(1)) model based on binomial thinning, in which the innovation sequence follows a zero–one–two-modified Poisson (ZOTMPo) distribution.
Manik Awale +5 more
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Association between respiratory hospital admissions and air quality in Portugal: A count time series approach. [PDF]
PLoS ONE, 2021 Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays.
Ana Martins +4 more
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Multivariate Count Data Models for Time Series Forecasting
Entropy, 2021 Count data appears in many research fields and exhibits certain features that make modeling difficult. Most popular approaches to modeling count data can be classified into observation and parameter-driven models. In this paper, we review two models from
Yuliya Shapovalova +2 more
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Modeling spatially dependent count time series data using COM-poisson INGARCH Models [PDF]
PLoS ONEStephanie Colwell +4 more
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Analysis of Count Time Series: A Bayesian GARMA(p, q) Approach
Austrian Journal of Statistics, 2023 Extensions of the Autoregressive Moving Average, ARMA(p, q), class for modeling non-Gaussian time series have been proposed in the literature in recent years, being applied in phenomena such as counts and rates.
Luiz Otávio de Oliveira Pala +2 more
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A Class of Copula-Based Bivariate Poisson Time Series Models with Applications
Computation, 2021 A class of bivariate integer-valued time series models was constructed via copula theory. Each series follows a Markov chain with the serial dependence captured using copula-based transition probabilities from the Poisson and the zero-inflated Poisson ...
Mohammed Alqawba +2 more
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A New First-Order Integer-Valued Autoregressive Model with Bell Innovations
Entropy, 2021 A Poisson distribution is commonly used as the innovation distribution for integer-valued autoregressive models, but its mean is equal to its variance, which limits flexibility, so a flexible, one-parameter, infinitely divisible Bell distribution may be ...
Jie Huang, Fukang Zhu
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