Stable limits for empirical processes on vapnik-cervonenk is classes of functions

Alexander' s (1987) central limit theorem for empirical processes on Vapnik-Cervonenkis classes of functions is extended to the case with non-Gaussian stable limits. The corresponding weak laws of large numbers are also established

New stochastic approach to the renormalization of the supersymmetric \phi^4 with ultrametric

We present a new real space renormalization-group map, on the space of probabilities, to study the renormalization of the SUSY \phi^4. In our approach we use the random walk representation on a lattice labeled by an ultrametric space. Our method can be extended to any \phi^n. New stochastic meaning is given to the parameters involved in the flow of the map and results are provided.Comment: 17 pages, Latex 2e, to appear in Int. Jour. of Mod. Phys.

Blaxican Identity: An Exploratory Study of Blacks/Chicanas/os in California

Abstract: This paper explores the racial/ethnic identities of multiracial Black-Mexicans or ‘Blaxicans.’ In- depth interviews with 12 Blaxican individuals in California reveal how they negotiate distinct cultural systems to accomplish multiracial identities. I argue that choosing, accomplishing, and asserting a Blaxican identity challenges the dominant monoracial discourse in the United States, in particular among African American and Chicana/o communities. That is, Blaxican respondents are held accountable by African Americans and Chicanas/os/Mexicans to monoracial notions of ‘authenticity.’ The process whereby Blaxicans move between these monoracial spaces to create multiracial identities illustrates crucial aspects of the social construction of race/ethnicity in the United States

Shape Outlier Detection and Visualization for Functional Data: the Outliergram

We propose a new method to visualize and detect shape outliers in samples of curves. In functional data analysis we observe curves defined over a given real interval and shape outliers are those curves that exhibit a different shape from the rest of the sample. Whereas magnitude outliers, that is, curves that exhibit atypically high or low values at some points or across the whole interval, are in general easy to identify, shape outliers are often masked among the rest of the curves and thus difficult to detect. In this article we exploit the relation between two depths for functional data to help visualizing curves in terms of shape and to develop an algorithm for shape outlier detection. We illustrate the use of the visualization tool, the outliergram, through several examples and asses the performance of the algorithm on a simulation study. We apply them to the detection of outliers in a children growth dataset in which the girls sample is contaminated with boys curves and viceversa.Comment: 27 pages, 5 figure