16 citations · 48 across the 17 of their papers we have counts for
17 papers
Achieving Privacy Utility Balance for Multivariate Time Series Data
Gaurab Hore, Tucker McElroy, Anindya Roy
Utility-preserving data privatization is of utmost importance for data-producing agencies. The popular noise-addition privacy mechanism distorts autocorrelation patterns in time se…
Polyspectral Mean Estimation of General Nonlinear Processes
Dhrubajyoti Ghosh, Tucker McElroy, Soumendra Lahiri
Higher-order spectra (or polyspectra), defined as the Fourier Transform of a stationary process' autocumulants, are useful in the analysis of nonlinear and non Gaussian processes.…
Grouping predictors via network-wide metrics
Brandon Woosuk Park, Anand N. Vidyashankar, Tucker S. McElroy
When multitudes of features can plausibly be associated with a response, both privacy considerations and model parsimony suggest grouping them to increase the predictive power of a…
Skip-sampling: subsampling in the frequency domain
Tucker McElroy, Dimitris Politis
Over the last 35 years, several bootstrap methods for time series have been proposed. Popular `time-domain' methods include the block-bootstrap, the stationary bootstrap, the linea…
Local Quadratic Spectral and Covariance Matrix Estimation
Tucker S. McElroy, Dimitris N. Politis
The problem of estimating the spectral density matrix of a multivariate time series is revisited with special focus on the frequencies and . Recognizing that the…
Statistical inference for high-dimensional spectral density matrix
Jinyuan Chang, Qing Jiang, Tucker S. McElroy +1
The spectral density matrix is a fundamental object of interest in time series analysis, and it encodes both contemporary and dynamic linear relationships between component process…