91 citations · 121 across the 11 of their papers we have counts for
11 papers
A Maximum Entropy Implementation of Differential Privacy Under Linear Invariants
Ryan Lafferty, Anindya Roy
Differential privacy is the standard for ensuring data privacy and is widely used in major data publications, including reporting results from the U.S. decennial census. Common imp…
Conic Sparsity: Estimation of Regression Parameters in Closed Convex Polyhedral Cones
Neha Agarwala, Arkaprava Roy, Anindya Roy
Statistical problems often involve linear equality and inequality constraints on model parameters. Direct estimation of parameters restricted to general polyhedral cones, particula…
FLIP: A Utility Preserving Privacy Mechanism for Time Series
Tucker McElroy, Anindya Roy, Gaurab Hore
Guaranteeing privacy in released data is an important goal for data-producing agencies. There has been extensive research on developing suitable privacy mechanisms in recent years.…
Efficient Integration of Aggregate Data and Individual Patient Data in One-Way Mixed Models
Neha Agarwala, Junyong Park, Anindya Roy
Often both Aggregate Data (AD) studies and Individual Patient Data (IPD) studies are available for specific treatments. Combining these two sources of data could improve the overal…
Constrained Parameterization of Reduced Rank and Co-integrated Vector Autoregression
Anindya Roy, Tucker S. McElroy
The paper provides a parametrization of Vector Autoregression (VAR) that enables one to look at the parameters associated with unit root dynamics and those associated with stable d…
Stochastic Approximation Algorithm for Estimating Mixing Distribution for Dependent Observations
Nilabja Guha, Anindya Roy
Estimating the mixing density of a mixture distribution remains an interesting problem in statistics literature. Using a stochastic approximation method, Newton and Zhang (1999) in…