A General Approach for Monitoring Serially Dependent Categorical Processes
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DOI: 10.1080/00224065.2017.11918003
Abstract: We consider the statistical surveillance for serially dependent categorical processes, where observations exhibit temporal dependence and have several attribute levels. In the literature, relevant methods focus on serially dependent binary data with two attribute levels… read more here.
Keywords: categorical processes; general approach; approach monitoring; dependent categorical ... See more keywords
Threshold integer-valued autoregressive model with serially dependent innovation
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2024.2404470
Abstract: ABSTRACT Nonlinearity in count time series is commonly encountered in practice. To better explain the nonlinear phenomena in count time series, this article introduces a new threshold INAR(1) model using the idea of serially dependent… read more here.
Keywords: dependent innovation; integer valued; model; serially dependent ... See more keywords
The assessment of kurtosis in the case of serially dependent data
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DOI: 10.1080/00949655.2025.2479065
Abstract: Though kurtosis is often identified with Pearson's standardized fourth moment $ \beta _2 $ β2, a long debate has been carried over about its actual meaning and the aspects of the shape which $ \beta… read more here.
Keywords: case serially; dependent data; kurtosis; assessment kurtosis ... See more keywords
A mixed INAR(p) model with serially dependent innovation with application to some COVID-19 data
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DOI: 10.1080/03610926.2023.2300305
Abstract: Abstract. This present work proposes a new mixed INAR(p) model (SDMINAR(p)) based on binomial thinning and negative binomial thinning operators, where the innovations are supposed to be serially dependent on the population at time {t−1,t−2,⋯,t−p}.… read more here.
Keywords: least squares; inar model; model; mixed inar ... See more keywords
Monitoring serially dependent categorical processes with ordinal information
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DOI: 10.1080/24725854.2018.1429695
Abstract: ABSTRACT In many industrial applications, there is usually a natural order among the attribute levels of categorical process variables or factors, such as good, marginal, and bad. We consider monitoring a serially dependent categorical process… read more here.
Keywords: dependent categorical; serially dependent; attribute levels; monitoring serially ... See more keywords