A new geometric first-order integer-valued autoregressive (NGINAR(1)) process

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Estimation in an Integer-Valued Autoregressive Process with Negative Binomial Marginals (NBINAR(1)) (2012, background): “( 2009 ) also gave some contribution to the analysis of negative-binomial thinning operator.”
Discrete dispersion models and their Tweedie asymptotics (2014, methodology): “…where X is discrete, this is a geometric compounding of the form N1 + · · · + NX , where N1, N2, . . . is a sequence of i.i.d. geometric random variables with mean c, independent of X , corresponding to the negative binomial thinning of Ristić et al. (2009) and Barreto-Souza & Bourguignon (2014).”
A geometric time series model with dependent Bernoulli counting series (2013, methodology): “…INAR(1) model with Poisson marginals (Al-Osh and Alzaid, 1987), NGINAR(1), a new geometric INAR(1) model based on negative binomial thinning (Ristić et al., 2009), mixed INAR(1) and mixed ab INAR(1) (Nastić and Ristić, 2012), INAR(1) models I1, I2 and I3 with negative binomial marginals…”
Zero‐Modified Geometric INAR(1) Process for Modelling Count Time Series with Deflation or Inflation of Zeros (2015, methodology): “An alternative to the Poisson INAR process was considered by Ristić et al. (2009) by using a negative binomial thinning operator, which is obtained by assuming that the Wi ’s in (1) follow a geometric distribution.”