This Title All WIREs
How to cite this WIREs title:
WIREs Comp Stat

Hypothesis tests with precedence probabilities and precedence‐type tests

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Precedence probabilities are important tools in a statistician's toolkit. Precedence probabilities can be defined as the probability of observing single samples from K populations in a particular order. Noting that there are K ! possible orders of K populations; these K ! parameters are a useful way to measure the effectiveness of a classifier (AUC/VUS/HUM). Receiver operating characteristic (ROC) curve/surface/manifold, which can be generated by any classifier leads to calculation of the area under curve (AUC)/volume under surface (VUS)/hyper‐volume under manifold (HUM) can be approximated by a single precedence probability and can be nonparametrically estimated via rank‐based U‐statistic. Precedence probabilities can also be used to test equality of K > 2 distribution functions. Hypothesis tests related to both these problems mentioned above are discussed. On the other hand, when we are interested in testing if the K distributions are stochastically ordered, we perform a precedence‐type test. Different nonparametric tests are also discussed in relation to precedence‐type tests. WIREs Comput Stat 2018, 10:e1417. doi: 10.1002/wics.1417 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Nonparametric Methods

Browse by Topic

Statistical and Graphical Methods of Data Analysis > Nonparametric Methods

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts