2 citations · 3 across the 9 of their papers we have counts for
24 papers
fastfrechet: An R package for fast implementation of Fréchet regression with distributional responses
Alexander Coulter, Rebecca Lee, Irina Gaynanova
Distribution-as-response regression problems are gaining wider attention, especially within biomedical settings where observation-rich patient specific data sets are available, suc…
A Sparse Linear Model for Positive Definite Estimation of Covariance Matrices
Rakheon Kim, Irina Gaynanova
Sparse covariance matrices play crucial roles by encoding the interdependencies between variables in numerous fields such as genetics and neuroscience. Despite substantial studies…
Beyond fixed thresholds: optimizing summaries of wearable device data via piecewise linearization of quantile functions
Junyoung Park, Neo Kok, Irina Gaynanova
Wearable devices, such as actigraphy monitors and continuous glucose monitors (CGMs), capture high-frequency data, which are often summarized by the percentages of time spent withi…
Learning Joint and Individual Structure in Network Data with Covariates
Carson James, Dongbang Yuan, Irina Gaynanova +1
Datasets consisting of a network and covariates associated with its vertices have become ubiquitous. One problem pertaining to this type of data is to identify information unique t…
Bayesian segmented Gaussian copula factor model for single-cell sequencing data
Junsouk Choi, Hee Cheol Chung, Irina Gaynanova +1
Single-cell sequencing technologies have significantly advanced molecular and cellular biology, offering unprecedented insights into cellular heterogeneity by allowing for the meas…
singR: An R package for Simultaneous non-Gaussian Component Analysis for data integration
Liangkang Wang, Irina Gaynanova, Benjamin Risk
This paper introduces an R package that implements Simultaneous non-Gaussian Component Analysis for data integration. SING uses a non-Gaussian measure of information to extract fea…