Crossref Citations
This Book has been
cited by the following publications. This list is generated based on data provided by Crossref.
Bedbur, Stefan
and
Kamps, Udo
2021.
Multivariate Exponential Families: A Concise Guide to Statistical Inference.
p.
5.
Ghosh, Subir
and
Nyquist, Hans
2021.
Stochastic Processes and Functional Analysis.
Vol. 774,
Issue. ,
p.
37.
Fort, G.
Gach, P.
and
Moulines, E.
2021.
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence.
Statistics and Computing,
Vol. 31,
Issue. 4,
Kwasniok, Frank
and
Daniels, Bryan C
2021.
Semiparametric maximum likelihood probability density estimation.
PLOS ONE,
Vol. 16,
Issue. 11,
p.
e0259111.
Bedbur, Stefan
and
Kamps, Udo
2021.
Multivariate Exponential Families: A Concise Guide to Statistical Inference.
p.
43.
Bedbur, Stefan
and
Kamps, Udo
2021.
Multivariate Exponential Families: A Concise Guide to Statistical Inference.
p.
1.
Spanos, Aris
2022.
Frequentist Model-based Statistical Induction and the Replication Crisis.
Journal of Quantitative Economics,
Vol. 20,
Issue. S1,
p.
133.
Schweinberger, Michael
Bomiriya, Rashmi P.
and
Babkin, Sergii
2022.
A semiparametric Bayesian approach to epidemics, with application to the spread of the coronavirus MERS in South Korea in 2015.
Journal of Nonparametric Statistics,
Vol. 34,
Issue. 3,
p.
628.
Nguyen, Hien Duy
and
Forbes, Florence
2022.
Global implicit function theorems and the online expectation–maximisation algorithm.
Australian & New Zealand Journal of Statistics,
Vol. 64,
Issue. 2,
p.
255.
Schweinberger, Michael
2022.
Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo.
Statistical Methods & Applications,
Vol. 31,
Issue. 2,
p.
253.
Nielsen, Frank
2022.
Revisiting Chernoff Information with Likelihood Ratio Exponential Families.
Entropy,
Vol. 24,
Issue. 10,
p.
1400.
Lauritzen, Steffen
and
Zwiernik, Piotr
2022.
Locally associated graphical models and mixed convex exponential families.
The Annals of Statistics,
Vol. 50,
Issue. 5,
Bodnar, Olha
and
Bodnar, Taras
2023.
Objective Bayesian Meta-Analysis Based on Generalized Marginal Multivariate Random Effects Model.
Bayesian Analysis,
Vol. -1,
Issue. -1,
Malyk, I.
and
Litvinchuk, Y.
2023.
ABOUT ONE APPROACH TO THE CONSTRUCTION OF SELF-ADAPTIVE ALGORITHMS BASED ON DISTRIBUTION MIXTURES.
Bukovinian Mathematical Journal,
Vol. 11,
Issue. 2,
p.
183.
Sheena, Yo
2023.
Convergence of estimative density: criterion for model complexity and sample size.
Statistical Papers,
Vol. 64,
Issue. 1,
p.
117.
Hoffman, Marion
Block, Per
and
Snijders, Tom A. B.
2023.
Modeling Partitions of Individuals.
Sociological Methodology,
Vol. 53,
Issue. 1,
p.
1.
Hashemi, Meraj
Schneider, Kristan A.
and
Abonazel, Mohamed R.
2024.
Estimating multiplicity of infection, allele frequencies, and prevalences accounting for incomplete data.
PLOS ONE,
Vol. 19,
Issue. 3,
p.
e0287161.
Asmussen, Søren
and
Glynn, Peter W.
2024.
Refined behaviour of a conditioned random walk in the large deviations regime.
Bernoulli,
Vol. 30,
Issue. 1,