9 citations · 17 across the 5 of their papers we have counts for
7 papers
Robust Inference for High-Dimensional Linear Models via Residual Randomization
Y. Samuel Wang, Si Kai Lee, Panos Toulis +1
We propose a residual randomization procedure designed for robust Lasso-based inference in the high-dimensional setting. Compared to earlier work that focuses on sub-Gaussian error…
Randomization Inference of Periodicity in Unequally Spaced Time Series with Application to Exoplanet Detection
Panos Toulis, Jacob Bean
The estimation of periodicity is a fundamental task in many scientific areas of study. Existing methods rely on theoretical assumptions that the observation times have equal or i.i…
Estimation of Covid-19 Prevalence from Serology Tests: A Partial Identification Approach
Panos Toulis
We propose a partial identification method for estimating disease prevalence from serology studies. Our data are results from antibody tests in some population sample, where the te…
Minimax designs for causal effects in temporal experiments with treatment habituation
Guillaume Basse, Yi Ding, Panos Toulis
Randomized experiments are the gold standard for estimating the causal effects of an intervention. In the simplest setting, each experimental unit is randomly assigned to receive t…
Dynamical systems theory for causal inference with application to synthetic control methods
Yi Ding, Panos Toulis
In this paper, we adopt results in nonlinear time series analysis for causal inference in dynamical settings.~Our motivation is policy analysis with panel data, particularly throug…
Propensity score methodology in the presence of network entanglement between treatments
Panos Toulis, Alexander Volfovsky, Edoardo M. Airoldi
In experimental design and causal inference, it may happen that the treatment is not defined on individual experimental units, but rather on pairs or, more generally, on groups of…