On the Concept of Depth for Functional Data

The statistical analysis of functional data is a growing need in many research areas. In particular, a robust methodology is important to study curves, which are the output of many experiments in applied statistics. As a starting point for this robust analysis, we propose, analyze, and apply a new d...

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Vydané v:	Journal of the American Statistical Association Ročník 104; číslo 486; s. 718 - 734
Hlavní autori:	López-Pintado, Sara, Romo, Juan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Alexandria, VA Taylor & Francis 01.06.2009 American Statistical Association Taylor & Francis Ltd
Predmet:	Applications Boys Child development Children Coordinate systems Data Data analysis Data depth Datasets Estimation Exact sciences and technology Experiments Functional analysis Functional data General topics Girls Insurance, economics, finance Marketing Mathematical analysis Mathematical functions Mathematics Measurement Median Modeling Multivariate analysis Observation Outliers Probability and statistics Property Quantitative analysis Rank test for functions Rank tests Research methodology Sampling Sciences and techniques of general use Simulation Simulations Statistical analysis Statistical median Statistical methods Statistics Studies Tests Theory and Methods Weather Functional data Prediction theory Median Multivariate analysis Stochastic process Microarray Marketing Statistical data Outlier Statistical test Depth function Ordering Rank test Child Human Wilcoxon test Discriminant analysis Data analysis Statistical analysis Finance Functional analysis Statistical estimation Mean estimation Data depth Rank test for functions Growth curve Trimmed mean Functional Statistical method Graphics Simulation Observation data Filtering theory Application
ISSN:	0162-1459, 1537-274X
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