Books
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. New York and Cambridge, ENG: Cambridge University Press. (Second Edition in preparation)
1994
Advances in Social Network Analysis: Research from the Social and Behavioral Sciences
Wasserman, S., & Galaskiewicz, J. (eds). Newbury Park, CA: Sage Publications
1994
Models and Methods in Social Network Analysis
Carrington, P., Scott, J., & Wasserman, S. (eds). New York: Cambridge University Press. (Winner, 2006 Harrison White Outstanding Book Award from the Mathematical Sociology Section of the American Sociological Association)
2004
Journals
Circular Matern covariance functions and the associated conditionalautoregressive models on circles
Huang, C., and Li, A. Manuscript.
2022
Spectral density estimation for random processes with stationary increments
Chen, W. Huang, C., Zhang, H., and Schaer, M. Manuscript.
2022
Non-Homogeneity estimation and Universal kriging on the sphere
Bussberg, N., Shields, J., and Huang, C. arXiv:2017.02871.
2022
Guiding neural network initialization via marginal likelihood maximization
Tai, A., and Huang, C. arXiv:2012.09943.
2022
Popularity Adjusted Block Models are Generalized Random Dot Product
J. Koo, M. Tang, M.W. Trosset
arXiv:2109.01040, 2021. Submitted for publication.
On Levy's Brownian motion and white noise space on the circle
Huang, C., and Li, A. Statistics and Probability Letters, 171.
2021
ciftiTools: A package for reading, writing, visualizing and manipulating CIFTI files in R
Pham DD, Muschelli J and Mejia AF. NeuroImage
2022
Spencer D, Yue YR, Bolin D, Ryan S and Mejia AF. NeuroImage 249
2022
Local biplots for multidimensional scaling, with application to themicrobiome
Julia Fukuyama. Journal of Computational and Graphical Statistics
2021
Discussion on "Distributional independent component analysis for diverse neuroimaging modalities" by Ben Wu, Subhadip Pal, Jian Kang, and Ying Guo
Mejia AF. Biometrics
2021
Bayesian Sparse Spiked Covariance Model With a Continuous Matrix Shrinkage Prior
Xie, F., Xu, Y., Priebe, C.E., and Cape, J. Bayesian Analysis, accepted for publication
2021
Simultaneous Learning the Dimension and Parameter of a Statistical Model with Big Data
Wang, L., Xie, F., and Xu, Y. Statistics in Biosciences, accepted for publication
2021
Rehabilitating Isomap: Euclidean representation of geodesic structure
M.W. Trosset, G. Buyukbas
arXiv:2006.10858
2020. Submitted for publication.
Learning 1-dimensional submanifolds for subsequent inference on random dot product graphs
M.W. Trosset, M. Gao, M. Tang, C.E. Priebe
arXiv:2004.07348
2020. Submitted for publication.
Algorithm 1007: QNSTOP-quasi-Newton algorithm for stochastic
B.D. Amos, D.R. Easterling, L.T. Watson, W.I. Thacker, B.S. Castle, M.W. Trosset
ACM Transactions on Mathematical Software, 46(2):1-20, May 2020.
Mejia AF, Nebel MB, Wang Y, Caffo B and Guo Y. Journal of the American Statistical Association 115.531 (2020): 1151-1177
A Bayesian general linear modeling approach to cortical surface fMRI data analysis
Mejia AF*, Yue YR*, Bolin D, Lindgren F, Lindquist MA. Journal of the American Statistical Association 115.530 (2020): 501-520.
*Cofirst authors
Leveraging big data to understand the interactionof task and language during monologic spoken discourse in speakers with and without aphasia
Brielle Stark and Julia Fukuyama. Language, Cognition, and Neuroscience
2020
Lack of evidence for a substantial rate of templated mutagenesis in B cell diversification
Julia Fukuyama, Branden Olson, Frederick Matsen. Journal of Immunology
2020
Bayesian Projected Calibration for Computer Models
Xie, F. and Xu, Y. Journal of the American Statistical Association: Theory & Methods, in press
2020
Optimal Bayesian Estimation for Random Dot Product Graphs
Xie, F. and Xu, Y. Biometrika, 2020; 107 (4), 875-889.
Adaptive Bayesian Nonparametric Regression using a Kernel Mixtures of Local Polynomials with Application to Partial Linear Models
Xie, F. and Xu, Y. Bayesian Analysis, 2020; 15(1): 159-186.
Approximate information tests on statistical submanifolds
M.W. Trosset, C.E. Priebe
arXiv:1903.08656
2019. Accepted for publication in Journal of Machine Learning Research.
Identifiability of two-component skew normal mixtures with one known
S. Jain, M. Levine, P. Radivojac, M.W. Trosset
Scandinavian Journal of Statistics, 46(4):955-986, December 2019.
Open data on industry payments to healthcare providers reveal potential hidden costs to the public
Mejia JM, Mejia AF, & Pestilli F. Nature Communications 10.1 (2019): 1-8
Julia Fukuyama, Genome Biology
2019
Adaptive gPCA: A method for structured dimensionality reduction
Julia Fukuyama. Annals of Applied Statistics
2019
Quasi-Newton stochastic optimization algorithm for parameter estimation of a stochastic model of the budding yeast cell cycle
M. Chen, B.D. Amos, L.T. Watson, J.J. Tyson, Y. Cao, C.A. Shaffer, M.W. Trosset, C. Oguz, G. Kakoti. IEEE/ ACM Transactions on Computational Biology f3 Bioinformatics, 16(1):301-311, 2019.
Mejia AF, Nebel MB, Barber AD, Choe AS, Pekar JJ, Caffo B and Lindquist MA. NeuroImage 172 (2018): 478-491.
PCA leverage: outlier detection for highdimensional functional magnetic resonance imaging data
Mejia AF, Nebel MB, Eloyan A, Caffo B and Lindquist MA. Biostatistics 18.3 (2017): 521-536.
Examining the literature on “Networks in space and in time”: An introduction
De Benedictis, L., Vitale, M.P., & Wasserman, S. Network Science. 3, 1–17.
2015
Fast embedding for JOFC using the raw stress criterion
V. Lyzinski, Y. Park, C.E. Priebe, M.W. Trosset
arXiv:1502.03391, 2015. Journal of Com putational f3 Graphical Statistics, 26(4):786-802, 2017.
Social network research: The foundation of network science. Handbook of Research Methods in Psychology.
Wasserman, S., & Robins, G. New York: APA Press.
2012
Network analysis: A definitional guide to important concepts. In Little, T.D. (ed.) Oxford Handbook of Quantitative Methods.
Green, H., & Wasserman, S. New York: Oxford University Press.
2012
Introduction: Special issue of Statistical Analysis and Data Mining on Networks. Statistical Analysis and Data Mining.
Steinley, D., & Wasserman, S. 4, 459–460.
2011
Parallel deterministic and stochastic global minimization of functions with very many minima
D.R. Easterling, L.T. Watson, M.L. Madigan, B.S. Castle, M.W. Trosset
Computational Optimization and Applications, 57:469-492, 2014.
"Risk consistency of cross-validation with lasso-type procedures," accepted Statistica Sinica.
Homrighausen, D., and McDonald, D.J.
2016
"On the Nystrom and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets,"
Homrighausen, D. and McDonald, D.J., Journal of Computational and Graphical Statistics, 25, 344-362.
2016
"Estimating beta-mixing coefficients via histograms"
McDonald, D.J., Shalizi, C.R., and Schervish, M., Electronic Journal of Statistics, 9(2), 2855-2883.
2015
“Leave-one-out cross-validation is risk consistent for lasso,” Machine Learning
Homrighausen, D., and McDonald, D.J., 97(1-2), 65-78
2014
Bayesian Simultaneous Edit and Imputation for Multivariate Categorical Data
Manrique-Vallier, D. and Reiter, J.P. (forthcoming) Journal of the American Statistical Association
Bayesian Population Size Estimation Using Dirichlet Process Mixtures
[PDF]
Manrique-Vallier, D. Biometrics
2016
A Non-parametric, Multiple Imputation-Based Method for the Retrospective Integration of Data Sets"
Carrig, M., Ranby, K. W., Manrique-Vallier, D., Reiter, J. and Hoyle, R, Multivariate Behavioral Research 50(4), 383-397
2015
Longitudinal Mixed Membership Trajectory Models for Disability Survey Data
[PDF]
Manrique-Vallier, D., Annals of Applied Statistics 8, 2268--2291.
2014
Bayesian Estimation of Discrete Multivariate Latent Structure Models with Structural Zeros
Manrique-Vallier, D. and Reiter, J., Journal of Computational and Graphical Statistics 23, 1061--1079.
2014
Bayesian Multiple Imputation for Large-Scale Categorical Data with Structural Zeros
Manrique-Vallier, D. and Reiter, J., Survey Methodology 40, 125-134
2014
Estimating Identification Disclosure Risk Using Mixed Membership Models
Manrique-Vallier, D. and Reiter, J., Journal of the American Statistical Association 107, 1385-1394.
2012
Statistical estimation of T1 relaxation time using conventional magnetic resonance imaging.
Mejia AF, Sweeney EM, Dewey B, Nair G, Sati P, Shea C, Reich D and Shinohara RT. In press at NeuroImage.
Severity of muscle weakness independently associates with disability as measured by the Health Assessment Questionnaire-Disability Index (HAQ-DI) in scleroderma.
Paik J, Wigley FM, Mejia AF, Hummers LK. In press at Arthritis Care and Research.
Improving reliability of subject-level resting-state fMRI parcellations with shrinkage.
Mejia AF, Nebel MB, Shou H, Crainiceanu CM, Pekar JJ, Mostofsky SH, Caffo B and Lindquist MA. NeuroImage 112: 14-29.
2015
Zen and the art of multiple comparisons.
Lindquist MA and Mejia AF. Psychosomatic Medicine 77.2: 114-125.
2015
Shrinkage prediction of seed-voxel brain connectivity using resting-state fMRI.
Shou H, Eloyan A, Nebel MB, Mejia AF, Pekar JJ, Mostofsky S, Caffo B, Lindquist MA and Crainiceanu, CM. NeuroImage.
2014
Left-hemispheric microstructural abnormalities in children with high functioning Autism Spectrum Disorder.
Peterson D, Rajneesh M, Crocetti D, Mejia AF, Mostofsky SH. Autism Research.
2014
Evidence for specificity of motor impairments in catching and balance in children with autism.
Ament K, Mejia A, Buhlman R, Erklin S, Caffo B, Mostofsky S, & Wodka E. Journal of Autism and Developmental Disorders: 1-10.
2014
"Fitting ERGMs on Big Networks."
An, Weihua. Social Science Research 59: 107-119. (Special issue on Big Data in the Social Sciences)
2016
"On the Directionality Test of Peer Effects in Social Networks."
An, Weihua. Sociological Methods and Research 45(4): 635-650.
2016
"Multilevel Meta Network Analysis with Application to Studying Network Dynamics of Network Interventions."
An, Weihua. Social Networks 43: 48-56.
2015
"Instrumental Variables Estimates of Peer Effects in Social Networks."
An, Weihua. Social Science Research 50: 382-394.
2015
"Health Surveillance through Social Networks."
An, Weihua and Long Doan. Social Networks 42: 8-17.
2015
"The Origins of Asymmetric Ties in Friendship Networks: From Status Differential to Self-perceived Centrality."
An, Weihua and William McConnell. Network Science 3(2): 269-292.
2015
"Analysis of Contested Reports in Exchange Networks Based on Actors' Credibility."
An, Weihua and Sam Schramski. Social Networks 40: 25-33.
2015
"LARF: Instrumental Variable Estimation of Causal Effects through Local Average Response Functions."
An, Weihua and Xuefu Wang. Journal of Statistical Software 71(1): 1-13.
2016
"Causal Inference in Panel Data with Application to Estimating Race-of-Interviewer Effects in the General Social Survey."
An, Weihua and Christopher Winship. Sociological Methods and Research. (In Press)
2015
"Intrinsic random functions and universal kriging on the circle"
Huang, C., Zhang, H., and Robeson, S., Statistics and Probability Letters, 108, 33-39
2016
"Point-pattern analysis on the sphere"
Robeson, S., Li, A., and Huang, C., Spatial Statistics, 10, 76-86
2014
"Spectral density estimation through a regularized inverse problem"
Huang, C., Hsing, T., and Cressie, N. Statistica Sinica, 21, 1115-1144.
2011
"Nonparametric Estimation of Variogram and its Spectrum"
Huang, C., Hsing, T., and Cressie, N. Biometrika, 98, 775-789.
2011
“Psychological strategies for winning a geopolitical forecasting tournament,”
Mellers B, Ungar L, Baron J, Ramos J, Gurcay B, Fincher K, Scott SE, Moore D, Atanasov P, Swift SA, Murray T, Stone E, Tetlock PE. Psychological Science, May 1;25(5):1106-15
2014
