Two‐sample test based on classification probability

Haiyan Cai; Bryan Goggin; Qingtang Jiang

doi:10.1002/SAM.11438

Two‐sample test based on classification probability

Haiyan Cai, Bryan Goggin, Qingtang Jiang

University of Missouri-St. Louis

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	Statistical Analysis and Data Mining
Volume	13
DOIs	https://doi.org/10.1002/SAM.11438
State	Published - Feb 1 2020

Disciplines

Computer Sciences
Artificial Intelligence and Robotics

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@article{d7e25880f7674b8aae16721978fc6183,

title = "Two‐sample test based on classification probability",

author = "Haiyan Cai and Bryan Goggin and Qingtang Jiang",

note = "Robust classification algorithms have been developed in recent years with great success. We take advantage of this development and recast the classical two‐sample test problem in the framework of classification. Based on the estimates of classification probabilities from a classifier trained from the samples, a test statistic is proposed.",

year = "2020",

month = feb,

day = "1",

doi = "10.1002/SAM.11438",

language = "American English",

volume = "13",

journal = "Statistical Analysis and Data Mining",

}

TY - JOUR

T1 - Two‐sample test based on classification probability

AU - Cai, Haiyan

AU - Goggin, Bryan

AU - Jiang, Qingtang

N1 - Robust classification algorithms have been developed in recent years with great success. We take advantage of this development and recast the classical two‐sample test problem in the framework of classification. Based on the estimates of classification probabilities from a classifier trained from the samples, a test statistic is proposed.

PY - 2020/2/1

Y1 - 2020/2/1

UR - https://onlinelibrary.wiley.com/doi/full/10.1002/sam.11438

U2 - 10.1002/SAM.11438

DO - 10.1002/SAM.11438

M3 - Article

VL - 13

JO - Statistical Analysis and Data Mining

JF - Statistical Analysis and Data Mining

ER -

Two‐sample test based on classification probability

Disciplines

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