Hypothesis Testing
All research related to Hypothesis Testing. A full list of topics is available on my research page.
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⭐ Universally Consistent K-Sample Tests via Dependence Measures
Sambit Panda*, Cencheng Shen*, Ronan Perry, Jelle Zorn, Antoine Lutz, Carey E. Priebe, Joshua T. Vogelstein
Statistics & Probability Letters, 2025Introduces the idea that the k-sample testing problem and independence testing problem are equivalent up to a transformation of the data.
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⭐ hyppo: A Multivariate Hypothesis Testing Python Package
Sambit Panda, Satish Palaniappan, Junhao Xiong, Eric W. Bridgeford, Ronak Mehta, Cencheng Shen, Joshua T. Vogelstein
arXiv, 2024Introduces
hyppo
, a package that incorporates conventional and novel multivariate hypothesis tests. -
📝 Learning sources of variability from high-dimensional observational studies
Eric W. Bridgeford, Jaewon Chung, Brian Gilbert, Sambit Panda, Adam Li, Cencheng Shen, Alexandra Badea, Brian Caffo, Joshua T. Vogelstein
arXiv, 2023Generalizes causal estimators to arbitrary dimensional space and uses this to develop a new test (Causal CDcorr).
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⭐ Learning Interpretable Characteristic Kernels via Decision Forests
Sambit Panda*, Cencheng Shen*, Joshua T. Vogelstein
arXiv, 2023Demonstrates the kernel derived from random forest is characteristic and develops a hypothesis test based on that fact (KMERF).
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Elucidating Relationships within Neurological Screening Batteries via Random Forest-Based Hypothesis Testing
Sambit Panda, Leslie R. Wilson, Jariatu Stallone, Dalisa Kendricks, Korey Stevanovic, Jesse D. Cushman
2023Applies a random forest based hypothesis test (specifically KMERF) to evaluate the effectiveness of a neurological screening test for mice.
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⭐ The Chi-Square Test of Distance Correlation
Cencheng Shen, Sambit Panda, Joshua T. Vogelstein
JCGS, 2022Derives an approximation to the p-value of distance correlation that bypasses the permutation test with no significant loss of power.
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🎓 Multivariate Independence and k-sample Testing
Sambit Panda
Johns Hopkins, 2020My master’s thesis, which introduces a Python package and a new framework for k-sample testing.