Work

Guarding against Spurious Discoveries in High Dimensions

Year: 2015

Type: article

Abstract: -regression. Such an asymptotic distribution depends on the sample size, ambient dimension, the number of variables used in the fit, and the covariance information. It can be consistently estimated by multiplier bootstrapping and used as a benchmark to guard against spurious discoveries. It can also be applied to model selection, which considers only candidate models with goodness of fits better than those by spurious fits. The theory and method are convincingly illustrated by simulated examples and an application to the binary outcomes from German Neuroblastoma Trials.

Source: PubMed

DOI: 10.48550/arxiv.1512.01617

Authors: Fan, Jianqing, Zhou, Wen-Xin

Institution: Princeton University

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, National Institute of General Medical Sciences