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A New Type of Discrete Self-Decomposability and Its Application to Continuous-Time Markov Processes for Modeling Count Data Time Series
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Generalized Gamma Convolutions and Related Classes of Distributions and Densities
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Continuous-Time Markov Chains
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An introduction to probability theory and its applications
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Some results for dams with Markovian inputs
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First order autoregressive time series with negative binomial and geometric marginals
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Explicit stationary distributions for some galton-watson processes with immigration
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FIRST‐ORDER INTEGER‐VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
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SOME SIMPLE MODELS FOR DISCRETE VARIATE TIME SERIES 1
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Stochastic Processes and Population Growth
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On the Generalized "Birth-and-Death" Process
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Discrete Analogues of Self-Decomposability and Stability
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On continuous-time generalized AR(1) processes : models, statistical inference, and applications to non-normal time series
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Autoregressive moving-average processes with negative-binomial and geometric marginal distributions
inferredcites →https://doi.org/10.2307/1427362openalex-snapshot
Some ARMA models for dependent sequences of poisson counts
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An Introduction to Probability Theory and Its Applications.
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Generalized Poisson Distributions: Properties and Applications.
inferredcites →https://doi.org/10.5860/choice.29-2762openalex-snapshot
Continuous-time Markov chains: an applications-oriented approach
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Controlling correlated processes of Poisson counts
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Models for Integer-Valued Time Series
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Likelihood Inference for Exponential-Trawl Processes
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Models for Z+-Valued Time Series Based on Thinning
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Models for Z+-Valued Time Series Based on Thinning
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An INAR(1) process for modeling count time series with equidispersion, underdispersion and overdispersion
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Expectation Thinning Operators Based on Linear Fractional Probability Generating Functions
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Negative binomial time series models based on expectation thinning operators
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The combined INAR(p) models for time series of counts
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On a flexible construction of a negative binomial model
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Simultaneous confidence regions for the parameters of a Poisson INAR(1) model
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SUPERPOSITIONED STATIONARY COUNT TIME SERIES
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A new geometric INAR(1) process based on counting series with deflation or inflation of zeros
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Fully observed INAR(1) processes
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Optimal Alarm Systems for Count Processes
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A New Class of Autoregressive Models for Time Series of Binomial Counts
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Estimation in an Integer-Valued Autoregressive Process with Negative Binomial Marginals (NBINAR(1))
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Count Data Time Series Models Based on Expectation Thinning
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Modelling Count Data Time Series with Markov Processes Based on Binomial Thinning
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Integer‐valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes
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Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case
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Likelihood Inference for Generalized Integer Autoregressive Time Series Models
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Extremes of Periodic Integer-Valued Sequences with Exponential Type Tails
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