Name
Abstract | ||
|---|---|---|
Multivariate mode hunting is of increasing practical importance. Only a few such methods exist, however, and there usually is a trade-off between practical feasibility and theoretical justification. In this paper we attempt to do both. We propose a method for locating isolated modes (or better, modal regions) in a multivariate data set without pre-specifying their total number. Information on significance of the findings is provided by means of formal testing for the presence of antimodes. Critical values of the tests are derived from large sample considerations. The method is designed to be computationally feasible in moderate dimensions, and it is complemented by diagnostic plots. Since the null hypothesis under consideration is highly composite the proposed tests involve calibration in order to ensure a correct (asymptotic) level. Our methods are illustrated by application to real data sets. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.jmva.2008.10.015 | J. Multivariate Analysis |
Keywords | Field | DocType |
vc-classes.,large sample consideration,multivariate mode hunting,secondary,critical value,data analytic tool,diagnostic plot,multivariate data,62g20,isolated mode,brownian bridge,practical importance,primary,distribution free,nearest neighbor method,vc-classes,testing for antimodes,practical feasibility,62g99,62h99,modality,formal testing | Econometrics,Nearest neighbour algorithm,Data set,Brownian bridge,Multivariate statistics,Null hypothesis,Multivariate analysis,Statistics,Statistical hypothesis testing,Mathematics,Modal | Journal |
Volume | Issue | ISSN |
100 | 6 | Journal of Multivariate Analysis |
Citations | PageRank | References |
8 | 0.78 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prabir Burman | 1 | 14 | 3.34 |
| Wolfgang Polonik | 2 | 12 | 1.93 |