A New Extension of Thinning-Based Integer-Valued Autoregressive Models for Count Data
Entropy, 2020 The thinning operators play an important role in the analysis of integer-valued autoregressive models, and the most widely used is the binomial thinning.
Zhengwei Liu, Fukang Zhu
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Inference for bivariate integer-valued moving average models based on binomial thinning operation. [PDF]
J Appl Stat, 2020 Time series of (small) counts are common in practice and appear in a wide variety of fields. In the last three decades, several models that explicitly account for the discreteness of the data have been proposed in the literature.
Silva I, Eduarda Silva M, Torres C.
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A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data
Entropy, 2023 Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming ...
Huaping Chen, Jiayue Zhang, Xiufang Liu
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On Some Stationary INAR(1) Processes with Compound Poisson Distributions
Revstat Statistical Journal, 2023 Aly and Bouzar ([2]) used the backward approach in presence of the binomial thinning operator to construct underdispersed stationary first-order autoregressive integer valued (INAR (1)) processes.
Emad-Eldin A. A. Aly, Nadjib Bouzar
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Maximum-Likelihood Estimation in a Special Integer Autoregressive Model
Econometrics, 2020 The paper is concerned with estimation and application of a special stationary integer autoregressive model where multiple binomial thinnings are not independent of one another.
Robert C. Jung, Andrew R. Tremayne
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Data thinning for convolution-closed distributions [PDF]
, 2023 We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as the original observation, up to a (known) scaling of a parameter.
Dharamshi, Ameer +3 more
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Two-Threshold-Variable Integer-Valued Autoregressive Model
Mathematics, 2023 In the past, most threshold models considered a single threshold variable. However, for some practical applications, models with two threshold variables may be needed. In this paper, we propose a two-threshold-variable integer-valued autoregressive model
Jiayue Zhang, Fukang Zhu, Huaping Chen
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A new First-Order mixture integer-valued threshold autoregressive process based on binomial thinning and negative binomial thinning [PDF]
, 2023 In this paper, we introduce a new first-order mixture integer-valued threshold autoregressive process, based on the binomial and negative binomial thinning operators. Basic probabilistic and statistical properties of this model are discussed. Conditional
Sun, Liuquan, Sheng, Danshu, Wang, Dehui
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Residual Analysis with Bivariate INAR(1) Models
Revstat Statistical Journal, 2018 In this paper we analyze forecasting errors made by random coefficients bivariate integer-valued autoregressive models of order one. These models are based on the thinning operator to support discreteness of data.
Predrag M. Popović +2 more
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Likelihood Inference for Generalized Integer Autoregressive Time Series Models
Econometrics, 2019 For modeling count time series data, one class of models is generalized integer autoregressive of order p based on thinning operators. It is shown how numerical maximum likelihood estimation is possible by inverting the probability generating function of
Harry Joe
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