Interests:
Time Series Analysis
Econometrics
Neuroimaging Data Analysis
Deep Neural Networks
External Funding:
National Science Foundation - Division of Mathematical Sciences, #2418371, Role: PI (Ongoing, 2024-2027)
National Institute of Justice, #15PNIJ-22-GK-00246-BRND, Role: co-PI (Completed, 2022-2023)
National Institutes of Health, #R01NS129643, Role: Biostatistician (Ongoing, 2023-2028)
Publications/Preprints:
K. Wu, R. Sundararajan, M.F.C. Haddad, L. Piancastelli and W. Barreto-Souza - Mixed Time Series Quasi-Likelihood Models for Uncovering Covid-19 Viral Load and Mortality Dynamics. Preprint.
Z. Xiang**, R. Sundararajan and H. Ombao - High-Dimensional Locally Stationary Models for Identifying Neuroimaging Biomarkers in Autism Spectrum Disorder, Annals of Applied Statistics (under revision) ( R Code )(Data Processing/Visualization)
R. Sundararajan and S. Bruce - Frequency Band Analysis of Nonstationary Multivariate Time Series, Biometrics, 81(3), 2025 ( R Code )
Y. Jang**, R. Sundararajan, W. Barreto-Souza - A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference, Statistics and Computing, 34 (1), 2024 ( R Code )
Y. Jang**, R. Sundararajan, W. Barreto-Souza, E. Wheaton - Determining economic factors for sex trafficking in the United States using count time series regression, Empirical Economics, 2024 ( R Code )
R. Sundararajan - Factor Modeling of Multivariate Time Series: A Frequency Components Approach, Journal of Multivariate Analysis, 2023 ( R Code )
R. Sundararajan and W. Barreto-Souza - Student-t Stochastic Volatility Model with Composite Likelihood EM-algorithm, Journal of Time Series Analysis, 2022 ( R Code )
S. Ariyarathne**, H. Gangammanavar, R. Sundararajan - Change Point Detection in Nonstationary Sub-Hourly Wind Time Series, Applied Energy, 310, 118501, 2022
M.C. Duker, V. Pipiras and R. Sundararajan - Cotrending: Testing for Common Deterministic Trends in Varying Means Model, Journal of Multivariate Analysis, 104825, 2021
R. Sundararajan - Principal Component Analysis using Frequency Components of Multivariate Time Series, Computational Statistics & Data Analysis, 157, 107164, 2021 ( R Code )
R. Sundararajan, R. D. Frostig and H. Ombao - Modeling Spectral Properties in Stationary Processes of Varying Dimensions with Applications to Brain Local Field Potential Signals, Entropy, 22 (12), 1375, 2020
R. Sundararajan, V. Pipiras and M. Pourahmadi - Stationary Subspace Analysis of Nonstationary Covariance Processes: Eigenstructure Description and Testing, Bernoulli, 27 (1), 381-418, 2021
R. Sundararajan and M. Pourahmadi - Stationary Subspace Analysis of Nonstationary Processes, Journal of Time Series Analysis, 39 (3), 338-355, 2018 ( R Code )
R. Sundararajan and M. Pourahmadi - Nonparametric Change Point Detection in Multivariate Piecewise Stationary Time Series, Journal of Nonparametric Statistics, 30 (4), 926-956, 2018 ( R Code )
R. Sundararajan, M.A. Palma and M. Pourahmadi - Reducing Brain Signal Noise in the Prediction of Economic Choices: A Case Study in Neuroeconomics, Frontiers in Neuroscience, 11 (2017): 704
M. Aghashahi, R. Sundararajan, M. Pourahmadi, M.K. Banks - Water Distribution Systems Analysis - Battle of the Attack Detection Algorithms (BATADAL), Journal of Water Resources Planning and Management, 144 (8), 04018048, 2018
** Graduate student