Monitoring correlated processes with binomial marginals

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Limit theorems for discrete-time metapopulation models (2010, background): “Finally, we remark that if nN0 follows the stationary Bin(N, q ∗) law, our representation nt+1 = Bin(nt, p1)+Bin(N −nt, q1) is termed binomial autoregressive [43, 44, 65, 66].”
Binomial AR(1) processes: moments, cumulants, and estimation (2013, background): “Such type of count-data time series can be observed in quite different real-world situations, for example, if monitoring the number of non-conforming units in samples from a production process 3 , or the utilization of a computer pool 4 , or accesses to a web server 5 .”
BINOMIAL AUTOREGRESSIVE PROCESSES WITH DENSITY‐DEPENDENT THINNING (2014, background): “…in time series count data with a fixed finite range ¹0; 1; : : : ; N º. Applications include the monitoring of computer pools (withN workstations) (Weiß, 2009; Weiß and Kim, 2013a), infections (with N individuals) (Daley and Gani, 1999, Section 4.4), metapopulations (with N patches) (Buckley…”