A Semiparametric Kernel Independence Test With Application to Mutational Signatures

DOI10.1080/01621459.2020.1871357zbMath1506.62440OpenAlexW3120757972MaRDI QIDQ5881952

No author found.

Publication date: 14 March 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2020.1871357

zbMATH Keywords

test of independenceexcess zerosRosenblatt-Parzen kernel estimatormutational signature

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• R
• Python
• pyuvdata

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Measuring and testing dependence by correlation of distances
• Equivalence of distance-based and RKHS-based statistics in hypothesis testing
• A nonparametric test for equality of distributions with mixed categorical and continuous data
• A general class of zero-or-one inflated beta regression models
• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• On a weighted bootstrap approximation of the \(L_p\) norms of kernel density estimators
• Brownian distance covariance
• Equivalence between tie-corrected Spearman test and a chi-square test in a fourfold contingency table
• A nonparametric measure of independence under a hypothesis of independent components
• A quadratic measure of deviation of two-dimensional density estimates and a test of independence
• Testing independence by nonparametric kernel method
• A fast and objective multidimensional kernel density estimation method: fastKDE
• Constructions for a bivariate beta distribution
• Remarks on Some Nonparametric Estimates of a Density Function
• From Distance Correlation to Multiscale Graph Correlation
• Applied Nonparametric Econometrics
• Learning the parts of objects by non-negative matrix factorization
• Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation
• Distribution Free Tests of Independence Based on the Sample Distribution Function
• On Estimation of a Probability Density Function and Mode
• A Non-Parametric Test of Independence