Statistics - 2023

Lee, W.-P., Wang, H., Dombroski, B., Cheng, P.-L., Tucci, A., Si, Y.-Q., … Schellenberg, G. (2023). Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer’s Diseases Sequencing Project Subjects. Research Square. https://doi.org/10.21203/rs.3.rs-3353179/v1

Wang, H., Dombroski, B. A., Cheng, P.-L., Tucci, A., Si, Y.-Q., Farrell, J. J., … Lee, W.-P. (2023). Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer’s Diseases Sequencing Project Subjects. https://doi.org/10.1101/2023.09.13.23295505

Tian, Y., Wu, J., Liu, H., Wu, Y., Si, Y., Wang, X., … Hu, Y. (2023). Ambient temperature variability and hospital admissions for pneumonia: A nationwide study. Science of the Total Environment, 856. https://doi.org/10.1016/j.scitotenv.2022.159294

Yang, Y., Xu, T., Conant, G., Kishino, H., Thorne, J. L., & Ji, X. (2023). Interlocus Gene Conversion, Natural Selection, and Paralog Homogenization. MOLECULAR BIOLOGY AND EVOLUTION, 40(9). https://doi.org/10.1093/molbev/msad198

Abba, M. A., Williams, J. P., & Reich, B. J. (2023). A PENALIZED COMPLEXITY PRIOR FOR DEEP BAYESIAN TRANSFER LEARNING WITH APPLICATION TO MATERIALS INFORMATICS. ANNALS OF APPLIED STATISTICS, 17(4), 3241–3256. https://doi.org/10.1214/23-AOAS1759

Shi, C., Wan, R., Song, G., Luo, S., Zhu, H., & Song, R. (2023). A MULTIAGENT REINFORCEMENT LEARNING FRAMEWORK FOR OFF-POLICY EVALUATION IN TWO-SIDED MARKETS. ANNALS OF APPLIED STATISTICS, 17(4), 2701–2722. https://doi.org/10.1214/22-AOAS1700

Du, X., & Tang, M. (2023). Hypothesis testing for equality of latent positions in random graphs. BERNOULLI, 29(4), 3221–3254. https://doi.org/10.3150/22-BEJ1581

Jeng, X. J., Hu, Y., Venkat, V., Lu, T.-P., & Tzeng, J.-Y. (2023). Transfer learning with false negative control improves polygenic risk prediction. PLOS GENETICS, 19(11). https://doi.org/10.1371/journal.pgen.1010597

Ali, M. S., Aneja, V., Ganguly, I., Sanyal, S., & Sengupta, S. (2023, November 8). Wildfire Pollution Emissions, Exposure, and Human Health: A Growing Air Quality Control Issue. https://doi.org/10.3390/ecas2023-15922

Dieffenderfer, J., Brewer, A., Noonan, M. A., Smith, M., Eichenlaub, E., Haley, K. L., … Bozkurt, A. (2023). A Wearable System for Continuous Monitoring and Assessment of Speech, Gait, and Cognitive Decline for Early Diagnosis of ADRD. 2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC. https://doi.org/10.1109/EMBC40787.2023.10339986

Mohottige, D., Davenport, C. A., Bhavsar, N., Schappe, T., Lyn, M. J., Maxson, P., … Boulware, L. E. (2023). Residential Structural Racism and Prevalence of Chronic Health Conditions. JAMA NETWORK OPEN, 6(12). https://doi.org/10.1001/jamanetworkopen.2023.48914

Luo, L., Wang, J., & Hector, E. C. (2023). Rejoinder: 'Statistical inference for streamed longitudinal data'. BIOMETRIKA, 110(4), 871–874. https://doi.org/10.1093/biomet/asad051

Wu, S., Sun, H., Kitavi, M., Hamilton, J. P., Gesteira, G. S., Mollinari, M., … Fei, Z. (2023). Advances in the Development of Chromosome-Scale Haplotype-Resolved Genome Assemblies of Hexaploid Sweetpotatoes. International Plant & Animal Genome 30 Conference. Poster presented at the International Plant & Animal Genome 30 Conference.

Taniguti, C. H., Taniguti, L. M., Lau, J., Garcia, A. A. F., Mollinari, M., Byrne, D., & Riera-Lizarazu, O. (2023). Selecting the Best Bioinformatic Pipeline for Evaluating Diploid and Auto-Tetraploid Garden Rose Genotype-by-Sequencing Data. International Plant & Animal Genome 30 Conference. Poster presented at the International Plant & Animal Genome 30 Conference.

Gesteira, G. S., Mollinari, M., Pereira, G. da S., Olukolu, B. A., Oloka, B. M., Yencho, C., & Zeng, Z.-B. (2023). Genetic Mapping in Interconnected Hexaploid Sweetpotato Populations. International Plant & Animal Genome 30 Conference. Poster presented at the International Plant & Animal Genome 30 Conference, San Diego, CA.

Taniguti, C. H., Taniguti, L. M., Amadeu, R. R., Lau, J., Gesteira, G. de S., Oliveira, T. de P., … Garcia, A. A. F. (2023). Developing best practices for genotyping-by-sequencing analysis in the construction of linkage maps. GigaScience, 12. https://doi.org/10.1093/gigascience/giad092

da Costa Lima Moraes, A., Mollinari, M., Ferreira, R. C. U., Aono, A., de Castro Lara, L. A., Pessoa-Filho, M., … Vigna, B. B. Z. (2023). Advances in genomic characterization of Urochloa humidicola: exploring polyploid inheritance and apomixis. Theoretical and Applied Genetics, 136(11). https://doi.org/10.1007/s00122-023-04485-w

Rusyn, I., & Wright, F. A. (2023, December 23). Ten years of using key characteristics of human carcinogens to organize and evaluate mechanistic evidence in IARC Monographs on the identification of carcinogenic hazards to humans: Patterns and associations. TOXICOLOGICAL SCIENCES. https://doi.org/10.1093/toxsci/kfad134

C. L. Moraes Aline, Mollinari, M., Ulbricht, R., Aono, A., Castro Lara, L. A., Pessoa-Filho, M., … Vigna, B. (2023, September 3). Advances in genomic characterization of<i>Urochloa humidicola</i>: exploring polyploid inheritance and apomixis (Vol. 9). Vol. 9. https://doi.org/10.1101/2023.08.31.555743

Zhao, D., Mejia-Guerra, K. M., Mollinari, M., Samac, D., Irish, B., Heller-Uszynska, K., … Sheehan, M. J. (2023). A public mid-density genotyping platform for alfalfa (Medicago sativa L.). Genetic Resources, 4(8), 55–63. https://doi.org/10.46265/genresj.emor6509

Twiddy, J., Hector, E. C., & Dubljević, V. (2023). Perceived Invasiveness and Therapeutic Acceptability of Transcranial Magnetic Stimulation. AJOB Neuroscience. https://doi.org/10.1080/21507740.2022.2150710

Luo, L., Wang, J., & Hector, E. C. (2023). Statistical inference for streamed longitudinal data. Biometrika, doi: 10.1093/biomet/asad010.

Hector, E. C. (2023). Fused mean structure learning in data integration with dependence. To Appear in The Canadian Journal of Statistics, arXiv:2210.02198.

Hector, E. C., & Eloyan, A. (2023). Distributed model building and recursive integration for big spatial data modeling. ArXiv:2305.15951.

Kim, H., Ghosh, S., & Hector, E. C. (2023). Bayesian estimation of clustered dependence structures in functional neuroconnectivity. ArXiv, arXiv:2305.18044.

Huang, W., Hector, E. C., Cape, J., & McKennan, C. (2023). A statistical framework for GWAS of high dimensional phenotypes using summary statistics, with application to metabolite GWAS. ArXiv, arXiv:2303.10221.

Rosenfeld, M., Faino, A. V., Qu, P., Onchiri, F. M., Blue, E. E., Collaco, J. M., … Gibson, R. L. (2023). Association of Pseudomonas aeruginosa infection stage with lung function trajectory in children with cystic fibrosis. JOURNAL OF CYSTIC FIBROSIS, 22(5), 857–863. https://doi.org/10.1016/j.jcf.2023.05.004

Sun, G., & Zhou, Y.-H. (2023). [Review of AI in healthcare: navigating opportunities and challenges in digital communication]. FRONTIERS IN DIGITAL HEALTH, 5. https://doi.org/10.3389/fdgth.2023.1291132

Collins, C., McCallum, E., Nordby, K., Aggarwal, S., Griffith, E., Thomas, C., & Dunn, C. (2023). Enrollment, Engagement, and Effectiveness of a Large-Scale Diabetes Prevention Program Using Synchronous Distance Technology. DIABETOLOGY, 4(4), 574–585. https://doi.org/10.3390/diabetology4040051

Hector, E. C. (2023, October 27). Fused mean structure learning in data integration with dependence. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, Vol. 10. https://doi.org/10.1002/cjs.11797

Cella, L., & Martin, R. (2023). Possibility-theoretic statistical inference offers performance and probativeness assurances. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 163. https://doi.org/10.1016/j.ijar.2023.109060

North, J. S., Schliep, E. M., Hansen, G. J. A., Kundel, H., Custer, C. A., Mclaughlin, P., & Wagner, T. (2023, November 28). Accounting for spatiotemporal sampling variation in joint species distribution models. JOURNAL OF APPLIED ECOLOGY, Vol. 11. https://doi.org/10.1111/1365-2664.14547

Newsome, M., Poore, M. H., Harmon, D. D., Shaeffer, A. D., Talbott, C. L., Fellner, V., & Griffith, E. H. (2023, November 6). The Effects of Varying Levels of Cotton Gin Byproduct and Wet brewers' Grains on Growth Performance of Growing and Finishing Steers. JOURNAL OF ANIMAL SCIENCE, Vol. 101, pp. 289–290. https://doi.org/10.1093/jas/skad281.345

Ghosal, R., & Maity, A. (2023, September 13). Variable selection in function-on-scalar single-index model via the alternating direction method of multipliers. TEST, Vol. 9. https://doi.org/10.1007/s11749-023-00884-9

Ghosh, S. (2023, October 5). Multivariate Dependence beyond Correlation: Nonparametric Copulas. https://doi.org/10.52843/cassyni.ms603h

Ghosh, T., Ma, Y., Song, R., & Zhong, P. (2023). Flexible inference of optimal individualized treatment strategy in covariate adjusted randomization with multiple covariates. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 1344–1370. https://doi.org/10.1214/23-EJS2127

Dixit, V., & Martin, R. (2023). Revisiting consistency of a recursive estimator of mixing distributions. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 1007–1042. https://doi.org/10.1214/23-EJS2121

Jeng, X. J. (2023). Estimating the proportion of signal variables under arbitrary covariance dependence. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 950–979. https://doi.org/10.1214/23-EJS2119

Yanchenko, E., Bondell, H. D., & Reich, B. J. (2023, October 27). Spatial regression modeling via the R2D2 framework. ENVIRONMETRICS, Vol. 10. https://doi.org/10.1002/env.2829

Zou, H., Zeng, D., Xiao, L., & Luo, S. (2023). BAYESIAN INFERENCE AND DYNAMIC PREDICTION FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA. ANNALS OF APPLIED STATISTICS, 17(3), 2574–2595. https://doi.org/10.1214/23-AOAS1733

Rhodes, G., Davidian, M., & Lu, W. (2023). DYNAMIC PREDICTION OF RESIDUAL LIFE WITH LONGITUDINAL COVARIATES USING LONG SHORT-TERM MEMORY NETWORKS. ANNALS OF APPLIED STATISTICS, 17(3), 2039–2058. https://doi.org/10.1214/22-AOAS1706

Nag, P., Sun, Y., & Reich, B. J. (2023). Spatio-temporal DeepKriging for interpolation and probabilistic forecasting. SPATIAL STATISTICS, 57. https://doi.org/10.1016/j.spasta.2023.100773

Lu, L., & Ghosh, S. (2023). Nonparametric Estimation of Multivariate Copula Using Empirical Bayes Methods. MATHEMATICS, 11(20). https://doi.org/10.3390/math11204383

Swaminathan, A. C., Snyder, L. D., Hong, H., Stevens, S. R., Long, A. S., Yanchenko, E., … Palmer, S. M. (2023). External Control Arms in Idiopathic Pulmonary Fibrosis Using Clinical Trial and Real-World Data Sources. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 208(5), 579–588. https://doi.org/10.1164/rccm.202210-1947OC

Mondino, A., Ludwig, C., Menchaca, C., Russell, K., Simon, K. E., Griffith, E., … Olby, N. J. (2023). Development and validation of a sleep questionnaire, SNoRE 3.0, to evaluate sleep in companion dogs. SCIENTIFIC REPORTS, 13(1). https://doi.org/10.1038/s41598-023-40048-1

Li, Y., Reed, S. D., Winger, J. G., Hyland, K. A., Fisher, H. M., Kelleher, S. A., … Somers, T. J. (2023). Cost-Effectiveness Analysis Evaluating Delivery Strategies for Pain Coping Skills Training in Women With Breast Cancer. JOURNAL OF PAIN, 24(9), 1712–1720. https://doi.org/10.1016/j.jpain.2023.05.004

North, J. S., Wikle, C. K., & Schliep, E. M. (2023, September 29). A Review of Data-Driven Discovery for Dynamic Systems. INTERNATIONAL STATISTICAL REVIEW, Vol. 9. https://doi.org/10.1111/insr.12554

Kanodia, S., He, M. Y., Ford, E. B., Ghosh, S. K., & Wolfgang, A. (2023). Beyond Two-dimensional Mass-Radius Relationships: A Nonparametric and Probabilistic Framework for Characterizing Planetary Samples in Higher Dimensions. ASTROPHYSICAL JOURNAL, 956(2). https://doi.org/10.3847/1538-4357/acf3e7

Liu, S., Zhang, Y., Golm, G. T., Liu, G., & Yang, S. (2023, September 26). Robust analyzes for longitudinal clinical trials with missing and non-normal continuous outcomes. STATISTICAL THEORY AND RELATED FIELDS, Vol. 9. https://doi.org/10.1080/24754269.2023.2261351

Burgener, L., Hyland, E., Reich, B. J., & Scotese, C. (2023). Cretaceous climates: Mapping paleo-Koppen climatic zones using a Bayesian statistical analysis of lithologic, paleontologic, and geochemical proxies. PALAEOGEOGRAPHY PALAEOCLIMATOLOGY PALAEOECOLOGY, 613. https://doi.org/10.1016/j.palaeo.2022.111373

Sninsky, J. A., Staicu, A.-M., & Barnes, E. L. (2023, September 21). In Acute Severe Ulcerative Colitis Patients Who Receive Rescue Therapy, Prior Maintenance Therapy and Day 3 C-Reactive Protein After Rescue Therapy Are Associated With 12-Month Colectomy Risk. INFLAMMATORY BOWEL DISEASES, Vol. 9. https://doi.org/10.1093/ibd/izad215

Zhou, W., & Lahiri, S. (2023, August 25). Stationary Jackknife. JOURNAL OF TIME SERIES ANALYSIS. https://doi.org/10.1111/jtsa.12714

Somers, T. J. J., Winger, J. G. G., Fisher, H. M. M., Hyland, K. A. A., Davidian, M., Laber, E. B. B., … Keefe, F. J. J. (2023). Behavioral cancer pain intervention dosing: results of a Sequential Multiple Assignment Randomized Trial. PAIN, 164(9), 1935–1941. https://doi.org/10.1097/j.pain.0000000000002915

Li, R., & Xiao, L. (2023, September 4). Latent factor model for multivariate functional data. BIOMETRICS, Vol. 9. https://doi.org/10.1111/biom.13924

Larsen, N., Stallrich, J., Sengupta, S., Deng, A., Kohavi, R., & Stevens, N. T. (2023, October 17). Statistical Challenges in Online Controlled Experiments: A Review of A/B Testing Methodology. AMERICAN STATISTICIAN, Vol. 10. https://doi.org/10.1080/00031305.2023.2257237

Cordova, A. C., Dodds, J. N., Tsai, H.-H. D., Lloyd, D. T., Roman-Hubers, A. T., Wright, F. A., … Rusyn, I. (2023, August 22). Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. https://doi.org/10.1002/etc.5727

Ji, X., Fisher, A. A., Su, S., Thorne, J. L., Potter, B., Lemey, P., … Suchard, M. A. (2023, July 17). Scalable Bayesian Divergence Time Estimation With Ratio Transformations. SYSTEMATIC BIOLOGY. https://doi.org/10.1093/sysbio/syad039

Sakolish, C., Moyer, H. L., Tsai, H.-H. D., Ford, L. C., Dickey, A. N., Wright, F. A., … Rusyn, I. (2023). Analysis of reproducibility and robustness of a renal proximal tubule microphysiological system OrganoPlate 3-lane 40 for in vitro studies of drug transport and toxicity. TOXICOLOGICAL SCIENCES. https://doi.org/10.1093/toxsci/kfad080

Yang, H., Ruiz-Suarez, S., Reich, B. J., Guan, Y., & Rappold, A. G. (2023). A Data-Fusion Approach to Assessing the Contribution of Wildland Fire Smoke to Fine Particulate Matter in California. REMOTE SENSING, 15(17). https://doi.org/10.3390/rs15174246

Wagner, T., Schliep, E. M., North, J. S., Kundel, H., Custer, C. A., Ruzich, J. K., & Hansen, G. J. A. (2023). Predicting climate change impacts on poikilotherms using physiologically guided species abundance models. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 120(15). https://doi.org/10.1073/pnas.2214199120

Clark, K., Fu, W., Liu, C.-L., Ho, P.-C., Wang, H., Lee, W.-P., … Tzeng, J.-Y. (2023). The prediction of Alzheimer's disease through multi-trait genetic modeling. FRONTIERS IN AGING NEUROSCIENCE, 15. https://doi.org/10.3389/fnagi.2023.1168638

Zahan, N., Shohan, S., Harris, D., & Williams, L. (2023). Do Software Security Practices Yield Fewer Vulnerabilities? 2023 IEEE/ACM 45TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN PRACTICE, ICSE-SEIP, pp. 292–303. https://doi.org/10.1109/ICSE-SEIP58684.2023.00032

Koner, S., & Williams, J. P. (2023). The EAS approach to variable selection for multivariate response data in high-dimensional settings. ELECTRONIC JOURNAL OF STATISTICS, 17(2), 1947–1995. https://doi.org/10.1214/23-EJS2141

Werthmann, D., Joode, B. van W., Cuffney, M. T., Reich, B. J., Soto-Martinez, M. E., Corrales-Vargas, A., … Hoppin, J. A. (2023). A cross-sectional analysis of medical conditions and environmental factors associated with fractional exhaled nitric oxide (FeNO) in women and children from the ISA birth cohort, Costa Rica. ENVIRONMENTAL RESEARCH, 233. https://doi.org/10.1016/j.envres.2023.116449

Ray, M., Guha, S., Dhungana, R. R., Karak, A., Choudhury, B., Ray, B., … Selker, H. P. (2023). Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies. INTERNATIONAL JOURNAL OF CARDIOLOGY CARDIOVASCULAR RISK AND PREVENTION, 18. https://doi.org/10.1016/j.ijcrp.2023.200195

Small, G. W., Akhtari, F. S., Green, A. J., Havener, T. M., Sikes, M., Quintanhila, J., … Wiltshire, T. (2023). Pharmacogenomic Analyses Implicate B Cell Developmental Status and MKL1 as Determinants of Sensitivity toward Anti-CD20 Monoclonal Antibody Therapy. CELLS, 12(12). https://doi.org/10.3390/cells12121574

Liu, Z., Clifton, J., Laber, E. B., Drake, J., & Fang, E. X. (2023, July 8). Deep Spatial Q-Learning for Infectious Disease Control. JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS. https://doi.org/10.1007/s13253-023-00551-4

Awasthi, C., Archfield, S. A., Reich, B. J., & Sankarasubramanian, A. (2023). Beyond Simple Trend Tests: Detecting Significant Changes in Design-Flood Quantiles. GEOPHYSICAL RESEARCH LETTERS, 50(13). https://doi.org/10.1029/2023GL103438

Sahoo, I., Guinness, J., & Reich, B. J. J. (2023, July 6). Estimating atmospheric motion winds from satellite image data using space-time drift models. ENVIRONMETRICS, Vol. 7. https://doi.org/10.1002/env.2818

Weishampel, A., Staicu, A.-M., & Rand, W. (2023). Classification of social media users with generalized functional data analysis. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 179. https://doi.org/10.1016/j.csda.2022.107647

Cordova, A. C., Klaren, W. D., Ford, L. C., Grimm, F. A., Baker, E. S., Zhou, Y.-H., … Rusyn, I. (2023). Integrative Chemical-Biological Grouping of Complex High Production Volume Substances from Lower Olefin Manufacturing Streams. TOXICS, 11(7). https://doi.org/10.3390/toxics11070586

Gonzalez, R. D., Small, G. W., Green, A. J., Akhtari, F. S., Havener, T. M., Quintanilha, J. C. F., … Wiltshire, T. (2023). RYK Gene Expression Associated with Drug Response Variation of Temozolomide and Clinical Outcomes in Glioma Patients. PHARMACEUTICALS, 16(5). https://doi.org/10.3390/ph16050726

Li, M., Liu, W., Si, J., Stallrich, J. W., & Huang, H. (2023). Hierarchical Optimization for Control of Robotic Knee Prostheses Toward Improved Symmetry of Propulsive Impulse. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 70(5), 1634–1642. https://doi.org/10.1109/TBME.2022.3224026

Gao, C., & Yang, S. (2023). Pretest estimation in combining probability and non-probability samples. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 1492–1546. https://doi.org/10.1214/23-EJS2137

Tabaie, A., Sengupta, S., Pruitt, Z. M., & Fong, A. (2023). A natural language processing approach to categorise contributing factors from patient safety event reports. BMJ Health & Care Informatics, 30(1), e100731. https://doi.org/10.1136/bmjhci-2022-100731

Majumder, R., & Reich, B. J. (2023). A deep learning synthetic likelihood approximation of a non-stationary spatial model for extreme streamflow forecasting. SPATIAL STATISTICS, 55. https://doi.org/10.1016/j.spasta.2023.100755

Gonzalez, R. D., Small, G. W., Green, A. J., Akhtari, F. S., Motsinger-Reif, A. A., Quintanilha, J. C. F., … Wiltshire, T. (2023). MKX-AS1 Gene Expression Associated with Variation in Drug Response to Oxaliplatin and Clinical Outcomes in Colorectal Cancer Patients. PHARMACEUTICALS, 16(5). https://doi.org/10.3390/ph16050757

Leshchev, D., J. S. Valentine, A., Kim, P., Mills, A. W., Roy, S., Chakraborty, A., … Chen, L. X. X. (2023, May 31). Revealing Excited-State Trajectories on Potential Energy Surfaces with Atomic Resolution in Real Time. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION. https://doi.org/10.1002/anie.202304615

Kline, E., & Sengupta, S. (2023). How AI can Help us Understand and Mitigate Error Propagation in Radiation Oncology. In Artificial Intelligence in Radiation Oncology (pp. 305–334). https://doi.org/10.1142/9789811263545_0014

Komolafe, T., Fong, A., & Sengupta, S. (2023). Scalable Community Extraction of Text Networks for Automated Grouping in Medical Databases. Journal of Data Science. https://doi.org/10.6339/22-JDS1038

Yanchenko, E., & Sengupta, S. (2023). Core-periphery structure in networks: A statistical exposition. Statistics Surveys, 17(none), 42–74. https://doi.org/10.1214/23-SS141

Dixit, V., & Martin, R. (2023). A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions. STATISTICS AND COMPUTING, 33(4). https://doi.org/10.1007/s11222-023-10242-2

Ting, B. W. W., Wright, F. A., & Zhou, Y.-H. (2023, May 22). Simultaneous modeling of multivariate heterogeneous responses and heteroskedasticity via a two-stage composite likelihood. BIOMETRICAL JOURNAL. https://doi.org/10.1002/bimj.202200029

Tsai, H.-H. D., House, J. S., Wright, F. A., Chiu, W. A., & Rusyn, I. (2023, April 20). A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo. TOXICOLOGICAL SCIENCES. https://doi.org/10.1093/toxsci/kfad041

Chu, J., Lu, W., & Yang, S. (2023, March 15). Targeted optimal treatment regime learning using summary statistics. BIOMETRIKA, Vol. 3. https://doi.org/10.1093/biomet/asad020

Zhou, Y.-H., Gallins, P. J., Pace, R. G., Dang, H., Aksit, M. A., Blue, E. E., … Knowles, M. R. (2023). Genetic Modifiers of Cystic Fibrosis Lung Disease Severity. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 207(10), 1324–1333. https://doi.org/10.1164/rccm.202209-1653OC

Gao, Y., Shi, C., & Song, R. (2023). Deep spectral Q-learning with application to mobile health. STAT, 12(1). https://doi.org/10.1002/sta4.564

Wang, K., & Ghosal, S. (2023). Posterior contraction and testing for multivariate isotonic regression. ELECTRONIC JOURNAL OF STATISTICS, 17(1), 798–822. https://doi.org/10.1214/23-EJS2115

Ganguly, I., Buhrman, G., Kline, E., Mun, S. K. K., & Sengupta, S. (2023). Automated Error Labeling in Radiation Oncology via Statistical Natural Language Processing. DIAGNOSTICS, 13(7). https://doi.org/10.3390/diagnostics13071215

Hector, E. C., & Reich, B. J. (2023, April 12). Distributed Inference for Spatial Extremes Modeling in High Dimensions. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 4. https://doi.org/10.1080/01621459.2023.2186886

Stallrich, J., Allen-Moyer, K., & Jones, B. (2023, April 7). D- and A-Optimal Screening Designs. TECHNOMETRICS. https://doi.org/10.1080/00401706.2023.2183262

Chen, H., Lu, W., Song, R., & Ghosh, P. (2023, April 12). On Learning and Testing of Counterfactual Fairness through Data Preprocessing. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 4. https://doi.org/10.1080/01621459.2023.2186885

Koner, S., & Staicu, A.-M. (2023). Second-Generation Functional Data. ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 10, 547–572. https://doi.org/10.1146/annurev-statistics-032921-033726

Gao, C., Yang, S., & Kim, J. K. (2023, March 2). Soft calibration for selection bias problems under mixed-effects models. BIOMETRIKA, Vol. 3. https://doi.org/10.1093/biomet/asad016

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