Results 11 to 20 of about 425,593 (212)
INGARCH-based fuzzy clustering of count time series with a football application
Machine Learning with Applications, 2022 Although there are many contributions in the time series clustering literature, few studies still deal with count time series data. This paper aims to develop a fuzzy clustering procedure for count time series data.
Roy Cerqueti +4 more
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Count Data Time Series Modelling in Julia—The CountTimeSeries.jl Package and Applications
Entropy, 2021 A new software package for the Julia language, CountTimeSeries.jl, is under review, which provides likelihood based methods for integer-valued time series.
Manuel Stapper
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Count time series with excess zeros: A Bayesian perspective using zero-adjusted distributions
Semina: Ciências Exatas e Tecnológicas, 2022 Models for count data which are temporally correlated have been studied using many conditional distributions, such as the Poisson distribution, and the insertion of different dependence structures. Nonetheless, excess of zeros and over dispersion may be
Luiz Otávio de Oliveira Pala +2 more
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Binomial Thinning Integer-Valued AR (1) with Poisson – α Fold Zero Modified Geometric Innovations [PDF]
Journal of Sciences, Islamic Republic of Iran, 2022 Real count data time series often show the phenomenon of the overdispersion. In this paper, we introduce the first-order integer-valued autoregressive process.
Maryam Shalbaf +2 more
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Axioms, 2023 INAR models have the great advantage of being able to capture the conditional distribution of a count time series based on their past observations, thus allowing it to be tailored to meet the unique characteristics of count data.
Fatimah E. Almuhayfith +5 more
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On Discrete Poisson–Mirra Distribution: Regression, INAR(1) Process and Applications
Axioms, 2022 Several pieces of research have spotlighted the importance of count data modelling and its applications in real-world phenomena. In light of this, a novel two-parameter compound-Poisson distribution is developed in this paper.
Radhakumari Maya +4 more
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On Outliers and Interventions in Count Time Series following GLMs
Austrian Journal of Statistics, 2014 We discuss the analysis of count time series following generalised linear models in the presence of outliers and intervention effects. Different modifications of such models are formulated which allow to incorporate, detect and to a certain degree ...
Roland Fried +4 more
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Reaction to the COVID-19 pandemic in Seoul with biostatistics
Infectious Disease Modelling, 2022 This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic. First, we focus on short-term forecasting for the number of new confirmed cases and severe cases.
Seungpil Jung +3 more
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Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance
Journal of Statistical Software, 2016 Public health surveillance aims at lessening disease burden by, e.g., timely recognizing emerging outbreaks in case of infectious diseases. Seen from a statistical perspective, this implies the use of appropriate methods for monitoring time series of ...
Maëlle Salmon +2 more
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A Systematic Review of INGARCH Models for Integer-Valued Time Series
Entropy, 2023 Count time series are widely available in fields such as epidemiology, finance, meteorology, and sports, and thus there is a growing demand for both methodological and application-oriented research on such data.
Mengya Liu +3 more
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