RT Book, Section
T1 On the combination of depth-based ranks
A1 Cascos Fernández, Ignacio
A1 Montes, Ignacio
AB The depth of a multivariate observation assesses its degree of centrality with respect to a probability distribution, and thus it can be interpreted as a measurement of the fit of the observation wrt the distribution. If such depth is transformed into a (depth-based) rank, then we obtain a kind of p-value of a goodness-of-fit test run on a single observation. For a sample of observations, the goal is to combine their ranks in order to decide whether they were taken from some prescribed distribution. From the meta-analysis literature, it is well known that there does not exist a combination procedure for such p-values (or ranks) that outperforms the remaining ones in all possible scenarios. Here we explore several combination procedures of the depth-based ranks and analyse their behaviour in the detection of some given shifts from a prescribed distribution.
PB Springer
SN 978-3-319-73847-5
YR 2018
FD 2018-01-01
LK https://hdl.handle.net/10016/32245
UL https://hdl.handle.net/10016/32245
LA eng
NO This work was started while Ignacio Montes was with the Department of Statistics of the Universidad Carlos III de Madrid. We acknowledge the financial support by projects ECO2015-66593 and TIN2014-59543-P.
DS e-Archivo
RD 26 jun. 2024