JSM 2025 Program

01: A Framework for Loss Scale Determination in General Bayesian Updating

2:00 PM - 3:50 PM

Co-authors: YU JIN SEO (Department of Statistics, Kyungpook National University), Seung Jun Park (Department of Statistics, Kyungpook National University), YU JIN SEO (Department of Statistics, Kyungpook National University), Pamela Kim Salonga (Department of Statistics, Kyungpook National University), Kyeong Eun Lee (Department of Statistics, Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University)

General Bayesian updating Loss-likelihood bootstrap Generalized method of moments Kullback-Leibler divergence Monte Carlo Newton-Raphson method

02: A Graph Database Approach for Biomarker Discovery

2:00 PM - 3:50 PM

Co-authors: Yang Liu (SPH in The University of Texas Health Science Center at Houston | MD Anderson Cancer Center), Jason Huse (MD Anderson Cancer Center), Yang Liu (SPH in The University of Texas Health Science Center at Houston | MD Anderson Cancer Center), Kasthuri Kannan (MD Anderson Cancer Center)

graph database graph neural network biomarker feature engineering feature selection

03: A multivariate approach to estimating the withdrawal time in food animal species

2:00 PM - 3:50 PM

Co-authors: Farha Ferdous Sheela, Ronald Baynes (Dr.), Farha Ferdous Sheela, Jim Riviere (Professor), Jacqueline Hughes-Oliver (North Carolina State University), Majid Jaberi-Douraki (Professor)

TLM WDT Multivariate t distribution OLS GLS ECM

04: Active Safety Surveillance of the 2023–2024 COVID-19 Vaccine Formulation: Findings from VSD

2:00 PM - 3:50 PM

Co-authors: Lily Wang (CDC), Eric Weintraub (CDC), Lily Wang (CDC), Burney Kieke (Marshfield Clinic Research Institute), Tat’Yana Kenigsberg (CDC), Kimp Walton (CDC), Michael McNeil (CDC), Jonathan Duffy (CDC)

Vaccine Safety Post-Vaccination Surveillance Adverse Events Rare Events Signal Detection Rapid Cycle Analysis (RCA) Sequential Analysis Concurrent Comparator Design Pocock Alpha-Spending Real-Time Monitoring Vaccine Safety Datalink (VSD) ICD-10 Codes Healthcare Records Guillain-Barré Syndrome (GBS) Ischemic Stroke, Myocarditis Adjusted Rate Ratio (aRR) Risk and Comparison Intervals COVID-19 Vaccine Pfizer Moderna Novavax

05: An Unbiased Convex Estimator for Classical Linear Regression Model Using Prior Information

2:00 PM - 3:50 PM

Co-authors: Mustafa I. Alheety (University of Anbar), HM Nayem, HM Nayem, B M Golam Kibria (Florida International University)

Linear model MSE Unbiased ridge estimator Restricted least-squares estimator Multicollinearity

06: Analyzing Wildfire Patterns in Colorado, Montana, Utah, and Wyoming Using Spatio-Temporal Methods

2:00 PM - 3:50 PM

Co-authors: Princess Tagoe, Mostafa Zahed (East Tennessee State University), Princess Tagoe

Spatio-temporal analysis Wildfire patterns Forest Ecosystems Risk assessment Predictive modeling Remote sensing

07: Application of Analysis Methods for Vaccine Efficacy in a Dengue Trial

2:00 PM - 3:50 PM

Co-authors: Tulin Shekar (Merck & Co., Inc.), Jung-Jin Lee (MSD), Tulin Shekar (Merck & Co., Inc.)

Vaccine efficacy conditional exact method Poisson regression modified Poisson regression.

08: Bayesian Kernel Machine Regression Model for Analysing Sequence Count Data

2:00 PM - 3:50 PM

Co-authors: Mosammat Sonia Khatun, Ander Wilson (Colorado State University), Mosammat Sonia Khatun

09: Bayesian Likelihood-free Inference with High-dimensional Data

2:00 PM - 3:50 PM

Co-authors: Minhye Park (Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University), Minhye Park (Kyungpook National University), Dipak Dey (University of Connecticut)

Bayesian variable selection High-dimensional regression Likelihood-free Bayesian inference Loss-likelihood bootstrap (LLB)

10: Benchmarking Spatial Co-Localization Methods for Single-Cell Multiplex Imaging Data of Cancers

2:00 PM - 3:50 PM

Co-authors: Ishaan Gadiyar (Vanderbilt University Medical Center), Simon Vandekar (Vanderbilt University), Ishaan Gadiyar (Vanderbilt University Medical Center)

Co-Clustering Multiplex Imaging Spatial Biology Spatial Proteomics

11: Can You Learn Statistics Online with An AI Tutor? A First Look at the BEAR!

2:00 PM - 3:50 PM

Co-authors: Yuhui Yao (The University of Alabama), Subhabrata Chakraborti (The University of Alabama), Yuhui Yao (The University of Alabama)

AI ChatGPT Online Statistical Education AI Tutoring

12: Deep Learning Models for Forecasting Treasury Bill Rates Using Gasoline Prices and Gold EPI

2:00 PM - 3:50 PM

Co-authors: JaNiah Harris, Mary Akinyemi (Austin Peay State University), JaNiah Harris

Deep Learning Recurrent Neural Network Treasury Bill Rate 3D Convolutional Neural Network Artificial Neural Network Machine Learning

13: Demographic Representativeness of the RADx-Up Cohort Compared to the U.S. Census Data

2:00 PM - 3:50 PM

Co-authors: Xue Yu (Stanford University), Meri Varkila (Stanford Univeristy), Xue Yu (Stanford University), Nivetha Subramanian (Stanford University), Julie Parsonnet (Stanford Univeristy), Shuchi Anand (Stanford University), Maria Montez-Rath (Stanford University), Glenn Chertow (Stanford University)

causal inference study propensity score model multiple imputation

14: Detecting Monotone Data Drift in Galaxy Luminosities

2:00 PM - 3:50 PM

Co-authors: Zixiang Xu, Jiayang Sun (George Mason University), Zixiang Xu, Mary Meyer (Colorado State University), Michael Woodroofe (Univ of Michigan)

selection bias semiparametric luminosity function

15: Detection of multiple change points for non-stationary network autoregressive models.

2:00 PM - 3:50 PM

Co-authors: Ruishan Lin, Abolfazl Safikhani (University of Florida), Ruishan Lin

Change Point Detection,Network Autoregressive (NAR) Model Network-Dependent Data Non-Stationary Processes Structural Changes

16: Developing NLP AND Supervised Machine Learning Techniques to Classify Mars Tasks

2:00 PM - 3:50 PM

Co-authors: Adam Kurth (Brown University School of Public Health), Mona Matar (NASA Glenn Research Center), Adam Kurth (Brown University School of Public Health), Hunter Rehm (HX5 LLC, NASA Glenn Research Center)

Natural Language Processing Machine Learning BERT (Bidirectional Encoder Representations from Transformers)NASA Human Research Program (HRP)Mars Task Classification Supervised Learning

17: Distributed Learning for Whole-Brain Functional Connectivity Analysis in Resting-State fMRI

2:00 PM - 3:50 PM

Co-authors: Wei Zhao, Emily Hector (North Carolina State University), Wei Zhao, Brian Reich (North Carolina State University)

rfMRI functional connectivity,oxel-level dependencies distributed learning ASD whole-brain modeling

18: Dynamic Functional Mediation Model in Geospatial Studies

2:00 PM - 3:50 PM

Co-authors: Miyeon Yeon (The University of Tennessee Health Science Center), Chao Huang (University of Georgia), Miyeon Yeon (The University of Tennessee Health Science Center)

COVID-19 dynamic interaction semiparametric function-on-scalar model mediation analysis penalized scalar-on-function linear regression

19: Dynamic Visualization of Complex Space-Time Processes Applied to Daily PM2.5 Concentrations

2:00 PM - 3:50 PM

Co-authors: Danielle Elterman, Dana Sylvan (Hunter College, City University of New York), Danielle Elterman, Peter Craigmile (Hunter College, CUNY)

Statistical Modeling PM2.5 Pollution Data Modeling

20: Enhancing Educational Approaches in Teaching Regression Techniques

2:00 PM - 3:50 PM

Co-authors: Sierra Merkes (Virginia Tech Statistics Department), Anne Driscoll, Sierra Merkes (Virginia Tech Statistics Department)

Statistical Education Regression Analysis Course Enhancement

21: Enhancing SQL Code Efficiency in Insurance Data with LLMs: A Repeated Measures Approach

2:00 PM - 3:50 PM

Co-authors: Philip Wong (CSAA IG), Gabriel Cotapos Jr (CSAA), Philip Wong (CSAA IG), Sean McCarthy (CSAA)

LLM (Large Language Models)SQL Code Documentation Quality Evaluation Repeated Measures ANOVA Inter-Rater Reliability Statistics

22: Enhancing Time Series Forecasting with Diffusion Models and Conformal Prediction

2:00 PM - 3:50 PM

Co-authors: Yu-Ting Fan (Academia Sinica), Hsin-Cheng Huang (Academia Sinica), Yu-Ting Fan (Academia Sinica)

Generative models Diffusion models Conformal prediction Time series analysis Uncertainty quantification

23: Evaluating Exposure Mixture Analysis Techniques for Pooling Multiple Cohorts

2:00 PM - 3:50 PM

Co-authors: Yuyan Wang (New York University), Akhgar Ghassabian (NYU Langone Health), Yuyan Wang (New York University), Mengling Liu (New York University Grossman School of Medicine)

Environmental mixture analysis Machine learning Heterogeneity ECHO program

24: Heterogeneity-Aware Regression with Variable Selection: Applications to Readmission Prediction

2:00 PM - 3:50 PM

Co-authors: Wei Wang (University of Minnesota Twin Cities), Angela Bailey (University of Minnesota Twin Cities), Wei Wang (University of Minnesota Twin Cities), Jared Huling (University of Minnesota)

Readmission Prediction Heterogeneity Functional ANOVA Kernel Methods Sparsity-Inducing Regularization

25: High-dimensional Bayesian regression and classification using discretized hyperpriors

2:00 PM - 3:50 PM

Co-authors: Gwanyeong Choi (Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University), Gwanyeong Choi (Kyungpook National University), Dipak Dey (University of Connecticut)

Bayesian shrinkage priors Discretization Gibbs sampler High-dimensional regression and classification

26: Hypothesis Tests for Comparing Two Independent Population Proportions with Censored Data

2:00 PM - 3:50 PM

Co-authors: Lili Liu, Mohsen Rezapour (1Department of Biostatistics and Data Science, School of Public Health, UT Health Houston), Lili Liu, Vahed Maroufy (Department of Biostatistics and Data Science, School of Public Health, UTHealth Houston), Yashar Talebi (Department of Biostatistics and Data Science, School of Public Health, UTHealth Houston), Guo-qiang Zhang (Texas Institute for Restorative Neuro-technologies (TIRN), UTHealth Houston), Hulin Wu (University of Texas Health Science Center At Houston)

Adverse effects COVID-19 vaccine hypothesis testing with censored data IPCW

27: Impact of Performance Metrics in AI Model Evaluation

2:00 PM - 3:50 PM

Co-authors: Youssouf Salami (Fidelity Investments), Victor Lo (Fidelity Investments), Youssouf Salami (Fidelity Investments)

artificial intelligence machine learning performance evaluation performance metrics model testing model monitoring, performance thresholds

28: Implementation of Nonlinear Z-score Analysis for Cognitive Abnormality Detection

2:00 PM - 3:50 PM

Co-authors: Peijun Liu (University of California San Francisco), John Kornak (University of California-San Francisco), Peijun Liu (University of California San Francisco), Adam Staffaroni (University of California San Francisco), Julie Fields (Mayo Clinic), Jingxuan Wang (University of California, San Francisco), Elena Tsoy (University of California, San Francisco)

Neuropsychological Testing Z-Score Adjustment Censored Regression Nonlinear Modeling Cognitive Assessment

29: Improving naive Bayes classifiers with high-dimensional non-Gaussian data

2:00 PM - 3:50 PM

Co-authors: Mijin Jeong (Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University), Mijin Jeong (Kyungpook National University), Dipak Dey (University of Connecticut)

Bayes classifier Generative classifier High-dimensional variable selection Power transformation

30: Item-Level Imputation of Missing K10 Data in Unconditional Cash Transfer Trials Using XGBoost

2:00 PM - 3:50 PM

Co-authors: Nidhi Tandon (University of Pennsylvania), Nidhi Tandon (University of Pennsylvania)

Multiple Imputation by Chained Equation (MICE)Item-level imputation XGBoost Randomized controlled trial (RCT)

31: Learning Smooth Populations of Parameters with Trial Heterogeneity

2:00 PM - 3:50 PM

Co-authors: JungHo Lee, Edward Kennedy, JungHo Lee

Binomial mixtures mixing distribution nonparametric density estimation criminal justice

32: Leveraging the Bayesian Stochastic Antecedent Model to Quantify Long-Term Drought Effects on Forest

2:00 PM - 3:50 PM

Co-authors: Ashlan Simpson, Ashlan Simpson

ecology time-series antecedent events causal inference tree growth

33: Light Absorption Enhancement in Coated Atmospheric Tar Balls Using Mie Theory

2:00 PM - 3:50 PM

Co-authors: Karen Magaña (Washington State University), Zezhen Cheng (Pacific Northwest National Laboratory), Karen Magaña (Washington State University), Manish Shrivastava (Pacific Northwest National Laboratory)

Mie Theory Atmospheric modeling light absorption light scattering Optical properties Core-shell particles

34: Mediation Approach to study Interplay of Poverty, Socioeconomic Status and Treatment on Mortality

2:00 PM - 3:50 PM

Co-authors: Demond Handley (The Ohio State University), Yesung Kweon (The Ohio State University), Demond Handley (The Ohio State University), Samiila Obeng-Gyasi (The Ohio State University Wexner Medical Center), Jesse Plascak (The Ohio State University Wexner Medical Center), Mohamed Elsaid

Causal Analysis Mediation Analysis Persistent Poverty Cancer Mortality

35: Modeling Autoregressive Conditional Regional Extremes with Applications to Solar Flare Prediction

2:00 PM - 3:50 PM

Co-authors: Steven Moen (University of Wisconsin-Madison), Jili Wang (University of Wisconsin-Madison), Steven Moen (University of Wisconsin-Madison), Zhengjun Zhang (University of Chinese Academy of Sciences)

big data solar flare detection time series of regional extremes extreme value theory tail index dynamics

36: Modeling Forage Quantity and Quality Using Machine Learning Models and Remote Sensing Data.

2:00 PM - 3:50 PM

Co-authors: Michael Abalo, Jameson Brennan (South Dakota State University), Michael Abalo, Hossein Moradi Rekabdarkolaee (South Dakota State University)

Livestock Forage Machine learning Remote sensing

37: Modeling Seasonal Time Series with Periodic Mean-Reverting Stochastic Differential Equations

2:00 PM - 3:50 PM

Co-authors: GM Fahad Bin Mostafa (Arizona State University), Linda J.S. Allen (Texas Tech University), GM Fahad Bin Mostafa (Arizona State University)

Parameter estimation Mean-reverting stochastic differential equations Confidence region Seasonal time series

38: On the Statistical Capacity of Deep Generative Models

2:00 PM - 3:50 PM

Co-authors: Edric Tam (Stanford University), David Dunson, Edric Tam (Stanford University)

Deep Generative Models Diffusion models Generative Adversarial Networks Variational Autoencoders Concentration of Measure

39: Orthogonal Multimodality Integration and Clustering in Single-cell Data

2:00 PM - 3:50 PM

Co-authors: Yufang Liu, Yongkai Chen, Yufang Liu, Haoran Lu (University of Georgia), Wenxuan Zhong (University of Georgia), Guo-cheng Yuan (Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai), Ping Ma (University of Georgia)

Multimodality Integration CITE-seq Cell Clustering

40: Personalized Dynamic Dose-Finding for Longitudinal Observational Data

2:00 PM - 3:50 PM

Co-authors: Md Nasim Saba Nishat (Department of Epidemiology and Biostatistics, University of South Carolina), Alexander McLain (University of South Carolina), Md Nasim Saba Nishat (Department of Epidemiology and Biostatistics, University of South Carolina)

Personalized medicine Optimal dose Longitudinal Data Analysis Implicit Delta Method

41: Practical Approaches to Machine Learning for Mental Illness Detection on Social Media

2:00 PM - 3:50 PM

Co-authors: Zhongyan Wang (New York University), Yuchen Cao (Northeastern University), Zhanyi Ding (New York University), Yexin Tian (Georgia Institute of Technology), Jianglai Dai (UC Berkeley), Xiaorui Shen (Northeastern University), Yeyubei Zhang (University of Pennsylvania), Yunchong Liu (University of Pennsylvania), Yuchen Cao (Northeastern University)

Machine Learning Deep Learning Mental Health Social Media NLP Multi-Class Classification

42: Predicting EGFR Expression from Lung Cancer Pathology images Using DNN

2:00 PM - 3:50 PM

Co-authors: Yibo ZHAI, Tong Wang (Yale University), Yibo ZHAI, Shuangge Ma

Feature images extraction Deep Neural Network Gene expression prediction

44: Random Processes with Stationary Increments and Intrinsic Random Functions on the Real Line

2:00 PM - 3:50 PM

Co-authors: Jongwook Kim (Indiana University Bloomington), Chunfeng Huang (Indiana University), Jongwook Kim (Indiana University Bloomington)

intrinsic random function random process with stationary increment non-stationary random process spatial statistics time series

45: Recent Regulatory Guidance Trends for Randomization Monitoring in Clinical Trials

2:00 PM - 3:50 PM

Co-authors: Jennifer Ross (Almac Group), Kevin Venner (Almac Group), Jennifer Ross (Almac Group), Noelle Sassany (Almac Group), Brian Stella (Almac)

Randomization Monitoring Clinical Trial Monitoring Randomization Regulatory Guidance Review

46: Refining Community Characteristic Composites Representing American Community Survey Item Data

2:00 PM - 3:50 PM

Co-authors: Scott Rega (Vanderbilt University Medical Center), Wali Johnson (Vanderbilt University Medica Center), Irene Feurer (Vanderbilt University Medical Center), Irene Feurer (Vanderbilt University Medical Center)

Latent variable models and principal components analysis American Community Survey data United States county community characteristics Social determinants of health

47: Resilience Forecasting through Advanced Predictive Models: A Transformer-Based Approach for Dynamic Analysis

2:00 PM - 3:50 PM

Co-authors: Fatemeh Salboukh (University of Massachusetts at Dartmouth), Hesam Saki (Department of Computer Engineering, University of Tehran), Fatemeh Salboukh (University of Massachusetts at Dartmouth), Lance Fiondella

Resilience prediction time-varying covariates Long-term prediction Time series TimeGPT models

48: Risk Analysis of Flowlines in the Oil and Gas Sector: A GIS and Machine Learning Approach

2:00 PM - 3:50 PM

Co-authors: Isabella Chittumuri, Soutir Bandyopadhyay (Colorado School of Mines), Isabella Chittumuri

Risk Analysis Flowlines Machine Learning GIS

49: Scalable Bayesian regression with massive and high-dimensional data

2:00 PM - 3:50 PM

Co-authors: Gyeongmin Park (Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University), Gyeongmin Park (Kyungpook National University), Dipak Dey (University of Connecticut)

Acceptance-rejection method Gibbs sampling High-dimensional Bayesian regression Scalable Bayesian computation

2:00 PM - 3:50 PM

Co-authors: Charles Smith (North Carolina State Univ.), David McMurray (Kagoshima International University), Charles Smith (North Carolina State Univ.)

haiku regression diagnostics data visualization AI haiku basketball plots

51: STIFT: Spatiotemporal Transcriptomics Integration by Spatially Informed Multi-Timepoint Bridging

2:00 PM - 3:50 PM

Co-authors: Ji Qi, Muyang Ge (The Chinese University of Hong Kong), Ji Qi, Jishuai MIAO (The Chinese University of Hong Kong), Xiaocheng Zhou (The Chinese University of Hong Kong), Zhixiang Lin (The Chinese University of Hong Kong)

spatial transcriptomics spatiotemporal data integration graph attention autoencoder developmental biology

52: Stratified Differential Privacy in Randomized Response: A Simulation Study

2:00 PM - 3:50 PM

Co-authors: Grace Kim (Wayzata High School, Minnesota, USA), Grace Kim (Wayzata High School, Minnesota, USA)

Data Privacy Randomized response technique Stratified Random Sampling Probability

53: Supervised Variational Autoencoder with Mixture-of-Experts Prediction

2:00 PM - 3:50 PM

Co-authors: Jaeyoung Lee (Virginia Tech), Hongxiao Zhu (Virginia Tech), Jaeyoung Lee (Virginia Tech)

Variational Autoencoder Data Heterogeneity Stick-breaking Process Supervised machine learning

54: Survival Analysis of Tumor Incidence in a Randomized Placebo-Controlled Clinical Trial

2:00 PM - 3:50 PM

Co-authors: Tingting Zhai (University of Kentucky), Tingting Zhai (University of Kentucky)

Kaplan-Meier longitudinal modeling malignancies

55: Synthetic Control by Covariate Balancing Propensity Score for Disaggregated Data

2:00 PM - 3:50 PM

Co-authors: Yanran Li, Yanran Li

causal inference synthetic control method Covariate Balancing Propensity Score Disaggregated Data

56: Tensor Response Regression with Low Tubal Rank and Sparsity

2:00 PM - 3:50 PM

Co-authors: Jiping Wang, Xin Zhang (Florida State University), Jiping Wang

ADMM multidimensional array multivariate linear regression reduced rank regression tubal rank fourier transform

57: Test methods for missing at random mechanism in clustered data

2:00 PM - 3:50 PM

Co-authors: Haoyu Zhou (Temple University), Recai Yucel (Temple University), Haoyu Zhou (Temple University), Resa M. Jones (Temple University, Department of Epidemiology & Biostatistics), Edoardo Airoldi (Temple University)

MAR missingness mechanism test clustering effects

58: Testing Against Parametric Regression Function using Shape-constrained Splines with AR(p) Errors

2:00 PM - 3:50 PM

Co-authors: Musfiq Nabeen (Colorado State University), Mary Meyer (Colorado State University), Musfiq Nabeen (Colorado State University)

Shape restrictions Regression splines Parametric function Autoregressive errors Consistent

59: The Impact of Lymphovascular Invasion on 2-Year Survival in HNSC: A Copula Regression Approach

2:00 PM - 3:50 PM

Co-authors: Yang Ou (Indiana University), Roger S Zoh (Indiana University), Yang Ou (Indiana University)

Lymphovascular invasion survival analysis copula regression endogeneity miRNA

60: Using Statistical Modeling to Revolutionize Ultimate Frisbee Strategy

2:00 PM - 3:50 PM

Co-authors: Leo Shi, Leo Shi

Ultimate frisbee modeling and simulation in sports sports analytics statistical modeling

61: Utilizing Variational Autoencoders to Shift Individual Level Data Towards Summary Level Statistics

2:00 PM - 3:50 PM

Co-authors: Sarah Milligan, Janice Weinberg (Boston Univ School of Public Health), Sarah Milligan, Fatema Shafie Khorassani

Variational Autoencoders Synthetic Data Distribution Shift Machine Learning Generative Modeling Summary Level Data

62: Weakly Supervised Transformer for Rare Disease Phenotyping

2:00 PM - 3:50 PM

Co-authors: Kimberly Greco (Harvard University), Zongxin Yang (Harvard Medical School), Kimberly Greco (Harvard University), Mengyan Li (Bentley University), Han Tong (Columbia University), Alon Geva (Boston Children's Hospital), Kenneth Mandl (Boston Children's Hospital), Tianxi Cai (Harvard University)

Semi-Supervised Learning Transformers Phenotyping Electronic Health Records Rare Diseases Machine Learning

63: Weighted Bayesian Bootstrap for Reduced Rank Regression with Singular Value Decomposition

2:00 PM - 3:50 PM

Co-authors: Wonbin Jung (Department of Statistics, Kyungpook National University), Hyeonji Shin (Kyungpook National University), Wonbin Jung (Department of Statistics, Kyungpook National University), Hyewon Oh (Kyungpook National University), Yeonsu Lee (Kyungpook National University), Minseok Kim (Kyungpook National University), Seongyun Kim (Kyungpook National University), Gyuhyeong Goh (Department of Statistics, Kyungpook National University)

Bayesian Reudced Rank Regression Singular Value Decomposition Weighted Bayesian Bootstrap Bayes factors

SPAAC Poster Competition — Topic Contributed Poster Presentations

62 Presentations