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Number of items: 5.
Thesis
Kevork, Sevag
(24. August 2017):
Separable Temporal Exponential Random Graph Models.
Master Thesis,
Ludwig-Maximilians-Universität München
[PDF, 2MB]
[PDF, 2MB]
Journal article
Kevork, Sevag und Kauermann, Goeran
(2022):
Bipartite exponential random graph models with nodal random effects.
In: Social Networks, Vol. 70: pp. 90-99
Kevork, Sevag 
ORCID: https://orcid.org/0000-0001-6324-4713 und Kauermann, Göran
(2021):
Iterative estimation of mixed exponential random graph models with nodal random effects.
In: Network Science, Vol. 9, No. 4: pp. 478-498
ORCID: https://orcid.org/0000-0001-6324-4713 und Kauermann, Göran
(2021):
Iterative estimation of mixed exponential random graph models with nodal random effects.
In: Network Science, Vol. 9, No. 4: pp. 478-498
Pollath, Nadja; Garcia-Gonzalez, Ricardo; Kevork, Sevag; Mutze, Ursula; Zimmermann, Michaela I.; Ozbassaran, Mihriban und Peters, Joris
(2021):
A non-linear prediction model for ageing foetal and neonatal sheep reveals basic issues in early neolithic husbandry.
In: Journal of Archaeological Science, Vol. 130, 105344
Witting, Maximilian; Filimon, Sascha und Kevork, Sevag
(2021):
Carry along or not? Decision-making on carrying standard avalanche safety gear among ski tourers in a German touring region.
In: Safety Science, Vol. 143, 105406