Results 41 to 50 of about 3,700 (150)

Randomness Test of Thinning Parameters for the NBRCINAR(1) Process

Axioms
Non-negative integer-valued time series are usually encountered in practice, and a variety of integer-valued autoregressive processes based on various thinning operators are commonly used to model these count data with temporal dependence. In this paper,
Shuanghong Zhang
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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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Maximum-likelihood estimation of the Po-MDDRCINAR(p) model with analysis of a COVID-19 data

Statistical Theory and Related Fields
Integer-valued data are frequently encountered in time series studies. A pth-order mixed dependence-driven random coefficient integer-valued autoregressive time series model (Po-MDDRCINAR(p)) in view of binomial and negative binomial operators, where the
Xiufang Liu, Jianlong Peng, Dehui Wang, Huaping Chen   +3 more
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A Two-Step Estimation Method for a Time-Varying INAR Model

Axioms, 2023
This paper proposes a new time-varying integer-valued autoregressive (TV-INAR) model with a state vector following a logistic regression structure.
Yuxin Pang, Dehui Wang, Mark Goh
doaj   +1 more source

Prediction Limits for Poisson INAR(1) Process

Journal of Mathematical and Fundamental Sciences, 2015
We discuss the problem of deriving an estimative prediction limit as well as a simulation-based improved prediction limit for a future realization from the stationary, first-order Poisson INAR(1) process.
Khreshna Syuhada, Abdulhamid Alzaid, Salah Djemili   +2 more
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Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient

Entropy, 2021
In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate.
Cong Li, Shuai Cui, Dehui Wang
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First-Order Integer-Valued Moving Average Process with Power Series Innovations

Journal of Statistical Theory and Applications (JSTA), 2020
In this paper, we introduce a first-order nonnegative integer-valued moving average process with power series innovations based on a Poisson thinning operator (PINMAPS(1)) for modeling overdispersed, equidispersed and underdispersed count time series ...
Eisa Mahmoudi, Ameneh Rostami
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Minification Integer-Valued Split-BREAK Process with Power Series Innovations and Application in Fire Safety Dynamics

Axioms
This manuscript introduces a new class of count time series models, referred to as the minification integer-valued Split-BREAK (MIN–SB) process. The proposed framework extends the Split-BREAK modeling philosophy to the integer-valued setting and provides
Vladica S. Stojanović, Nikola Mitrović, Kristina Tomović, Hassan S. Bakouch, Shuhrah Alghamdi   +4 more
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Stationary Underdispersed INAR(1) Models based on the Backward Approach

Revstat Statistical Journal
Most of the stationary first-order autoregressive integer-valued (INAR(1)) models in the literature have been developed using the idea of binomial thinning. Two approaches have been adopted to establish the distributional properties of a stationary INAR(
Emad-Eldin A. A. Aly, Nadjib Bouzar
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Advances in spatial integer-valued time series modeling

Journal of Applied Statistics
This study develops an empirical Bayes (EB) spatial hurdle INGARCH model for weekly dengue fever counts and compares it with a spatial zero-inflated generalized Poisson (ZIGP) INGARCH framework, both of which capture spatio-temporal dependence and excess zeros.
Cathy W.S. Chen, Chun-Shu Chen, Hsiao-Hsuan Liao   +2 more
openaire   +1 more source