By Dr Pavel Krivitsky

Journal articles

Forouzandeh S; Krivitsky PN; Chandra R, 2025, 'Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems', Expert Systems with Applications, 291, http://dx.doi.org/10.1016/j.eswa.2025.128378

Dekker D; Krackhardt D; Doreian P; Krivitsky PN, 2024, 'Balance correlations, agentic zeros, and networks: The structure of 192 years of war and peace', Plos One, 19, http://dx.doi.org/10.1371/journal.pone.0315088

Leaver VL; Clark RG; Krivitsky PN; Birrell CL, 2024, 'A comparison of likelihood-based methods for size-biased sampling', Journal of Statistical Planning and Inference, 230, http://dx.doi.org/10.1016/j.jspi.2023.106115

Krivitsky PN; Coletti P; Hens N, 2024, 'Correction', Journal of the American Statistical Association, 119, pp. 1694 - 1695, http://dx.doi.org/10.1080/01621459.2024.2344624

Krivitsky PN; Coletti P; Hens N, 2023, 'A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks', Journal of the American Statistical Association, 118, pp. 2213 - 2224, http://dx.doi.org/10.1080/01621459.2023.2242627

Krivitsky PN; Hunter DR; Morris M; Klumb C, 2023, 'ergm 4: New Features for Analyzing Exponential-Family Random Graph Models', Journal of Statistical Software, 105, pp. 1 - 44, http://dx.doi.org/10.18637/jss.v105.i06

Krivitsky PN; Kuvelkar AR; Hunter DR, 2023, 'Likelihood-based inference for exponential-family random graph models via linear programming', Electronic Journal of Statistics, 17, pp. 3337 - 3356, http://dx.doi.org/10.1214/23-EJS2176

Krivitsky PN; Coletti P; Hens N, 2023, 'Rejoinder to Discussion of “A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks”', Journal of the American Statistical Association, 118, pp. 2235 - 2238, http://dx.doi.org/10.1080/01621459.2023.2280383

Krivitsky PN; Morris M; Bojanowski M, 2022, 'Impact of survey design on estimation of exponential-family random graph models from egocentrically-sampled data', Social Networks, 69, pp. 22 - 34, http://dx.doi.org/10.1016/j.socnet.2020.10.001

Mazur L; Suesse T; Krivitsky PN, 2022, 'Investigating foreign portfolio investment holdings: Gravity model with social network analysis', International Journal of Finance and Economics, 27, pp. 554 - 570, http://dx.doi.org/10.1002/ijfe.2168

Chandra R; Jain M; Maharana M; Krivitsky PN, 2022, 'Revisiting Bayesian Autoencoders With MCMC', IEEE Access, 10, pp. 40482 - 40495, http://dx.doi.org/10.1109/ACCESS.2022.3163270

Chandra R; Bhagat A; Maharana M; Krivitsky PN, 2021, 'Bayesian Graph Convolutional Neural Networks via Tempered MCMC', IEEE Access, 9, pp. 130353 - 130365, http://dx.doi.org/10.1109/ACCESS.2021.3111898

Krivitsky PN; Koehly LM; Marcum CS, 2020, 'Exponential-Family Random Graph Models for Multi-Layer Networks', Psychometrika, 85, pp. 630 - 659, http://dx.doi.org/10.1007/s11336-020-09720-7

Schweinberger M; Krivitsky PN; Butts CT; Stewart JR, 2020, 'Exponential-Family Models of Random Graphs: Inference in Finite, Super and Infinite Population Scenarios', Statistical Science, 35, pp. 627 - 662, http://dx.doi.org/10.1214/19-STS743

Krivitsky PN; Butts CT, 2017, 'Exponential-family random graph models for rank-order relational data', Sociological Methodology, 47, pp. 68 - 112, http://dx.doi.org/10.1177/0081175017692623

Karwa V; Krivitsky PN; Slavković AB, 2017, 'Sharing social network data: differentially private estimation of exponential family random-graph models', Journal of the Royal Statistical Society Series C Applied Statistics, 66, pp. 481 - 500, http://dx.doi.org/10.1111/rssc.12185

Krivitsky PN; Morris M, 2017, 'Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US', Annals of Applied Statistics, 11, pp. 427 - 455, http://dx.doi.org/10.1214/16-AOAS1010

Krivitsky PN, 2017, 'Using contrastive divergence to seed Monte Carlo MLE for exponential-family random graph models', Computational Statistics and Data Analysis, 107, pp. 149 - 161, http://dx.doi.org/10.1016/j.csda.2016.10.015

Carnegie NB; Krivitsky PN; Hunter DR; Goodreau SM, 2015, 'An Approximation Method for Improving Dynamic Network Model Fitting', Journal of Computational and Graphical Statistics, 24, pp. 502 - 519, http://dx.doi.org/10.1080/10618600.2014.903087

Cressie N; Burden S; Davis W; Krivitsky PN; Mokhtarian P; Suesse T; Zammit-Mangion A, 2015, 'Capturing multivariate spatial dependence: Model, estimate and then predict', Statistical Science, 30, pp. 170 - 175, http://dx.doi.org/10.1214/15-STS517

Krivitsky PN; Kolaczyk ED, 2015, 'On the question of effective sample size in network modeling: An asymptotic inquiry', Statistical Science, 30, pp. 184 - 198, http://dx.doi.org/10.1214/14-STS502

Krivitsky PN; Handcock MS, 2014, 'A separable model for dynamic networks', Journal of the Royal Statistical Society Series B Statistical Methodology, 76, pp. 29 - 46, http://dx.doi.org/10.1111/rssb.12014

Krivitsky PN, 2012, 'Exponential-family random graph models for valued networks', Electronic Journal of Statistics, 6, pp. 1100 - 1128, http://dx.doi.org/10.1214/12-EJS696

Hunter DR; Krivitsky PN; Schweinberger M, 2012, 'Computational statistical methods for social network models', Journal of Computational and Graphical Statistics, 21, pp. 856 - 882, http://dx.doi.org/10.1080/10618600.2012.732921

Krivitsky PN; Handcock MS; Morris M, 2011, 'Adjusting for network size and composition effects in exponential-family random graph models', Statistical Methodology, 8, pp. 319 - 339, http://dx.doi.org/10.1016/j.stamet.2011.01.005

Krivitsky PN; Handcock MS; Raftery AE; Hoff PD, 2009, 'Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects models', Social Networks, 31, pp. 204 - 213, http://dx.doi.org/10.1016/j.socnet.2009.04.001

Krivitsky PN; Handcock MS, 2008, 'Fitting position latent cluster models for social networks with latentnet', Journal of Statistical Software, 24, http://dx.doi.org/10.18637/jss.v024.i05

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