Note: * indicates student/post-doctoral associate co-author

Pre-prints

Choi J*, Chung HC, Gaynanova I and Ni Y (2024+) Bayesian segmented Gaussian copula factor model for single-cell sequencing data. arXiv

Coulter A*, Aurora RN, Punjabi N and Gaynanova I (2024+). Fast variable selection for distributional regression with application to continuous glucose monitoring data arXiv

Chung HC*, Ni Y and and Gaynanova I (2024+). Sparse semiparametric discriminant analysis for high-dimensional zero-inflated data. arXiv

Yuan D*, Zhang Y*, Guo S, Wang W and Gaynanova I (2024+). Exponential canonical correlation analysis with orthogonal variation. arXiv [R code]

2024

Chun E*, Gaynanova I, Melanson E and Lyden, K (2024) Pre- Versus Postmeal Sedentary Duration; Impact on Postprandial Glucose in Older Adults with Overweight or Obesity. Journal for the Measurement of Physical Behaviour, Vol. 7, No. 1.

Cheong, SM and Gaynanova I (2024) Sensing the impact of extreme heat on physical activity and sleep. Digital Health, 10.

Sergazinov R*, Chun E*, Rogovchenko V*, Fernandes N*, Kasman N* and Gaynanova I (2024). GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks. International Conference on Learning Representations (ICLR). [GitHub repository]

2023

Yi S*, Wong R and Gaynanova I (2023). Hierarchical nuclear norm penalization for multi-view data. Biometrics, Vol. 79, No. 4, 2933-2946. [R code]

Sergazinov R*, Leroux A, Cui E, Crainiceanu C, Aurora RN, Punjabi N and Gaynanova I (2023). A case study of glucose levels during sleep using fast function on scalar regression inference. Biometrics, Vol. 79, No. 4, 3873-3882.

Sergazinov R*, Armandpour M and Gaynanova I (2023). Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) [Python code]

2022

Zhang Y* and Gaynanova I (2022). Joint association and classification analysis of multi-view data. Biometrics, Vol. 78, No. 4, 1614-1625. [R package]

Yuan D* and Gaynanova I (2022). Double-matched matrix decomposition for multi-view data. Journal of Computational and Graphical Statistics, Vol. 31, No. 4, 1114-1126. [R code]

Chung HC*, Gaynanova I and Ni Y (2022). Phylogenetically informed Bayesian truncated copula graphical models for microbial association networks. Annals of Applied Statistics, Vol. 16, No. 4, 2437–2457. [R code]

Schwenck J*, Punjabi N and Gaynanova I (2022). bp: Blood Pressure analysis in R. PLoS One, Vol. 17, No. 9, e0268934. [R package on CRAN] [R package on GitHub]

Gaynanova I (2022). Digital biomarkers of glucose control - reproducibility challenges and opportunities. ASA Biopharmaceutical Report, Vol. 29, No. 1, 21-26.

Aurora RN, Gaynanova I, Patel P*, and Punjabi N (2022). Glucose profiles in obstructive sleep apnea and type 2 diabetes mellitus. Sleep Medicine, Vol. 95, 105-111

Fernandes N*, Nguyen N*, Chun E*, Punjabi N and Gaynanova I (2022). Open-Source Algorithm to Calculate Mean Amplitude of Glycemic Excursions Using Short and Long Moving Averages. Journal of Diabetes Science and Technology, Vol. 16, No. 2, 576-577. [Github page to reproduce] [R package with implementation]

Gaynanova I, Punjabi N and Crainiceanu C (2022). Modeling continuous glucose monitoring (CGM) data during sleep. Biostatistics, Vol. 23, No. 1, 223-239. [R code]

2021

Lapanowski A* and Gaynanova I (2021). Compressing Large Sample Data for Discriminant Analysis 2021 IEEE International Conference on Big Data (Big Data), 1068-1076.

Huang M*, Müller C and Gaynanova I (2021). latentcor: An R package for estimating latent correlations from mixed data types. Journal of Open Source Software, Vol. 6, No. 65, 3634. [Github page] [Website]

Solhjoo S, Punjabi N, Ivanescu A, Crainiceanu C, Gaynanova I, Wicken C, Buckenmaier C, and Haigney M (2021) Methadone destabilizes cardiac repolarization during sleep. Clinical Pharmacology \& Therapeutics, Vol. 110, No. 4, 1066-1074.

Risk B and Gaynanova I (2021). Simultaneous Non-Gaussian Component Analysis (SING) for Data Integration in Neuroimaging Annals of Applied Statistics, Vol. 15, No. 3, 1431-1454. [R code]

Broll S*, Urbanek J, Buchanan D*, Chun E*, Muschelli J, Punjabi N and Gaynanova I (2021).Interpreting blood glucose data with R package iglu. PLoS One, Vol. 16, No. 4, e0248560. [R package]

Yoon G*, Müller C and Gaynanova I (2021). Fast computation of latent correlations. Journal of Computational and Graphical Statistics, Vol. 30, No. 4, 1249-1256. [R package] [R code to reproduce simulations]

2020

Taylor NJ, Gaynanova I, Eschrich SA, Welsh EA, Garrett TJ, Beecher C, Sharma R, Koomen JM, Smalley KSM, Messina JL, Kanetsky PA (2020). Metabolomics of primary cutaneous melanoma and matched adjacent extratumoral microenvironment. PLoS One, Vol. 15, No.10, e0240849.

Yoon G*, Carroll R and Gaynanova I (2020). Sparse semiparametric canonical correlation analysis for data of mixed types. Biometrika, Vol. 107, No. 3, 609-625. [R package]

Gaynanova I (2020). Prediction and estimation consistency of sparse multi-class penalized optimal scoring. Bernoulli, Vol. 26, No. 1, 286-322. Erratum for the proof of Theorem 5

2019

Gaynanova I and Li G (2019). Structural learning and integrative decomposition of multi-view data. Biometrics, Vol. 75, No. 4, 1121-1132. [R package]

Bien J, Gaynanova I, Lederer J and Müller C (2019). Prediction Error Bounds for Linear Regression With the TREX. TEST, Vol. 28, No. 2, 451-474.

Yoon G*, Gaynanova I and Müller C (2019). Microbial networks in SPRING - Semi-parametric rank-based correlation and partial correlation estimation for quantitative microbiome data. Frontiers in Genetics, Vol. 10, 516. [R package]

Lapanowski A* and Gaynanova I (2019). Sparse feature selection in kernel discriminant analysis via optimal scoring. Artificial Intelligence and Statistics (AISTATS). [R package]

Lederer J, Lu Y and Gaynanova I (2019). Oracle inequalities for high-dimensional prediction. Bernoulli, Vol. 25, No. 2, 1225-1255.

Gaynanova I and Wang T* (2019). Sparse quadratic classification rules via linear dimension reduction. Journal of Multivariate Analysis, Vol. 169, 278-299. [R package]

2018

Hokamp J, Leidy S, Gaynanova I, Cianciolo R and Nabity M (2018). Correlation of electrophoretic urine protein banding patterns with severity of renal damage in dogs with proteinuric chronic kidney disease. Veterinary Clinical Pathology, Vol. 47, No. 3, 425-434.

Li G and Gaynanova I (2018). A general framework for association analysis of heterogeneous data. Annals of Applied Statistics, Vol 12, No. 3, 1700-1726. [MATLAB code]

Gaynanova I, Urbanek J and Punjabi N (2018). Letter to the Editor: Corrections of equations on glycemic variability and quality of glycemic control. Diabetes Technology & Therapeutics, Vol. 20, No. 4, 317.

Bien J, Gaynanova I, Lederer J and Müller C (2018). Non-convex global minimization and false discovery rate control for the TREX. Journal of Computational and Graphical Statistics, Vol. 27, No. 1, 23-33. [MATLAB code]

2017 and older

Gaynanova I, Booth GJ and Wells TM (2017). Penalized versus constrained generalized eigenvalue problems. Journal of Computational and Graphical Statistics, Vol. 26, No. 2, 379-387.

Gaynanova I, Booth GJ and Wells TM (2016). Simultaneous sparse estimation of canonical vectors in the p»N setting. Journal of the American Statistical Association, Vol. 111, No. 514, 696-706. [R package]

Gaynanova I and Kolar M (2015). Optimal variable selection in multi-group sparse discriminant analysis. Electronic Journal of Statistics, Vol. 9, No. 2, 2007-2034.