The Chi-Square Test of Distance Correlation
Fuente:
arXiv
Saved in:
| Main Authors: | Shen, Cencheng, Panda, Sambit, Vogelstein, Joshua T. |
|---|---|
| Format: | Preprint |
| Published: |
2019
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning Interpretable Characteristic Kernels via Decision Forests
by: Panda, Sambit, et al.
Published: (2018)
by: Panda, Sambit, et al.
Published: (2018)
hyppo: A Multivariate Hypothesis Testing Python Package
by: Panda, Sambit, et al.
Published: (2019)
by: Panda, Sambit, et al.
Published: (2019)
High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020)
by: Shen, Cencheng, et al.
Published: (2020)
Independence Testing for Temporal Data
by: Shen, Cencheng, et al.
Published: (2019)
by: Shen, Cencheng, et al.
Published: (2019)
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
by: Shen, Cencheng, et al.
Published: (2018)
by: Shen, Cencheng, et al.
Published: (2018)
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
by: Shen, Dennis, et al.
Published: (2023)
by: Shen, Dennis, et al.
Published: (2023)
Network Dependence Testing via Diffusion Maps and Distance-Based Correlations
by: Lee, Youjin, et al.
Published: (2017)
by: Lee, Youjin, et al.
Published: (2017)
From Distance Correlation to Multiscale Graph Correlation
by: Shen, Cencheng, et al.
Published: (2017)
by: Shen, Cencheng, et al.
Published: (2017)
Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing
by: Yan, Jian, et al.
Published: (2022)
by: Yan, Jian, et al.
Published: (2022)
Robust Point Matching with Distance Profiles
by: Hur, YoonHaeng, et al.
Published: (2023)
by: Hur, YoonHaeng, et al.
Published: (2023)
Community Correlations and Testing Independence Between Binary Graphs
by: Shen, Cencheng, et al.
Published: (2019)
by: Shen, Cencheng, et al.
Published: (2019)
Scalable Kernel-Based Distances for Statistical Inference and Integration
by: Naslidnyk, Masha
Published: (2026)
by: Naslidnyk, Masha
Published: (2026)
Pearson Chi-squared Conditional Randomization Test
by: Javanmard, Adel, et al.
Published: (2021)
by: Javanmard, Adel, et al.
Published: (2021)
Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation
by: Chung, Junhyoung, et al.
Published: (2026)
by: Chung, Junhyoung, et al.
Published: (2026)
Transfer Learning with Distance Covariance for Random Forest: Error Bounds and an EHR Application
by: Li, Chenze, et al.
Published: (2025)
by: Li, Chenze, et al.
Published: (2025)
A renormalization-group inspired lattice-based framework for piecewise generalized linear models
by: Chang, Joshua C.
Published: (2026)
by: Chang, Joshua C.
Published: (2026)
Compress Then Test: Powerful Kernel Testing in Near-linear Time
by: Domingo-Enrich, Carles, et al.
Published: (2023)
by: Domingo-Enrich, Carles, et al.
Published: (2023)
Inference in Randomized Least Squares and PCA via Normality of Quadratic Forms
by: Wang, Leda, et al.
Published: (2024)
by: Wang, Leda, et al.
Published: (2024)
Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
by: Pantazis, Konstantinos, et al.
Published: (2024)
by: Pantazis, Konstantinos, et al.
Published: (2024)
Nearest Neighbor Matching as Least Squares Density Ratio Estimation and Riesz Regression
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Leveraging Optimal Transport for Distributed Two-Sample Testing: An Integrated Transportation Distance-based Framework
by: Lin, Zhengqi, et al.
Published: (2025)
by: Lin, Zhengqi, et al.
Published: (2025)
On Ranking-based Tests of Independence
by: Limnios, Myrto, et al.
Published: (2024)
by: Limnios, Myrto, et al.
Published: (2024)
Sequential Kernelized Independence Testing
by: Podkopaev, Aleksandr, et al.
Published: (2022)
by: Podkopaev, Aleksandr, et al.
Published: (2022)
On the Robustness of Kernel Goodness-of-Fit Tests
by: Liu, Xing, et al.
Published: (2024)
by: Liu, Xing, et al.
Published: (2024)
Testing for Outliers with Conformal p-values
by: Bates, Stephen, et al.
Published: (2021)
by: Bates, Stephen, et al.
Published: (2021)
Boosting the Power of Kernel Two-Sample Tests
by: Chatterjee, Anirban, et al.
Published: (2023)
by: Chatterjee, Anirban, et al.
Published: (2023)
Statistical Hypothesis Testing for Information Value (IV)
by: Rojas, Helder, et al.
Published: (2023)
by: Rojas, Helder, et al.
Published: (2023)
Multi-Armed Sequential Hypothesis Testing by Betting
by: Sandoval, Ricardo J., et al.
Published: (2026)
by: Sandoval, Ricardo J., et al.
Published: (2026)
Minimax-Optimal Two-Sample Test with Sliced Wasserstein
by: Tran, Binh Thuan, et al.
Published: (2025)
by: Tran, Binh Thuan, et al.
Published: (2025)
A Permutation-free Kernel Two-Sample Test
by: Shekhar, Shubhanshu, et al.
Published: (2022)
by: Shekhar, Shubhanshu, et al.
Published: (2022)
Hypothesis Testing for High-Dimensional Matrix-Valued Data
by: Cui, Shijie, et al.
Published: (2024)
by: Cui, Shijie, et al.
Published: (2024)
Multiple Testing of Linear Forms for Noisy Matrix Completion
by: Ma, Wanteng, et al.
Published: (2023)
by: Ma, Wanteng, et al.
Published: (2023)
Max-Rank: Efficient Multiple Testing for Conformal Prediction
by: Timans, Alexander, et al.
Published: (2023)
by: Timans, Alexander, et al.
Published: (2023)
Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
by: Jain, Saksham, et al.
Published: (2026)
by: Jain, Saksham, et al.
Published: (2026)
Kernel Two-Sample Testing via Directional Components Analysis
by: Cui, Rui, et al.
Published: (2025)
by: Cui, Rui, et al.
Published: (2025)
A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations
by: Chatalic, Antoine, et al.
Published: (2025)
by: Chatalic, Antoine, et al.
Published: (2025)
Universal Inference Meets Random Projections: A Scalable Test for Log-concavity
by: Dunn, Robin, et al.
Published: (2021)
by: Dunn, Robin, et al.
Published: (2021)
A Conditional Distribution Equality Testing Framework using Deep Generative Learning
by: Zheng, Siming, et al.
Published: (2025)
by: Zheng, Siming, et al.
Published: (2025)
Online Selective Conformal Prediction with Asymmetric Rules: A Permutation Test Approach
by: Zheng, Mingyi, et al.
Published: (2026)
by: Zheng, Mingyi, et al.
Published: (2026)
Conditional Predictive Inference for General Structured Data with Group Symmetries
by: Shen, Yichen, et al.
Published: (2026)
by: Shen, Yichen, et al.
Published: (2026)
Similar Items
-
Learning Interpretable Characteristic Kernels via Decision Forests
by: Panda, Sambit, et al.
Published: (2018) -
hyppo: A Multivariate Hypothesis Testing Python Package
by: Panda, Sambit, et al.
Published: (2019) -
High-Dimensional Independence Testing via Maximum and Average Distance Correlations
by: Shen, Cencheng, et al.
Published: (2020) -
Independence Testing for Temporal Data
by: Shen, Cencheng, et al.
Published: (2019) -
The Exact Equivalence of Distance and Kernel Methods for Hypothesis Testing
by: Shen, Cencheng, et al.
Published: (2018)