Dynamic network models based on the Generalized Poisson distribution capture unequal dispersion in temporal count data for improved fit and prediction.
The result in (Vershynin 2018, Lemma 2.7.6, ii)) and the log-mgf bound in Lemma 1 gives ||Y||ψ1≤C (√v+b ) =C( √ λ (1−θ)3/2 + |2θ+ 1| 3(1−θ)2 + (1−θ)3r 12λ Br(θ,λ))
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Generalized Poisson Dynamic Network Models
Dynamic network models based on the Generalized Poisson distribution capture unequal dispersion in temporal count data for improved fit and prediction.