652 research outputs found
Resistant estimates for high dimensional and functional data based on random projections
We herein propose a new robust estimation method based on random projections
that is adaptive and, automatically produces a robust estimate, while enabling
easy computations for high or infinite dimensional data. Under some restricted
contamination models, the procedure is robust and attains full efficiency. We
tested the method using both simulated and real data.Comment: 24 pages, 6 figure
Connectivity of inhomogeneous random graphs
We find conditions for the connectivity of inhomogeneous random graphs with
intermediate density. Our results generalize the classical result for G(n, p),
when p = c log n/n. We draw n independent points X_i from a general
distribution on a separable metric space, and let their indices form the vertex
set of a graph. An edge (i,j) is added with probability min(1, \K(X_i,X_j) log
n/n), where \K \ge 0 is a fixed kernel. We show that, under reasonably weak
assumptions, the connectivity threshold of the model can be determined.Comment: 13 pages. To appear in Random Structures and Algorithm
Resistant estimates for high dimensional and functional data based on random projections
We herein propose a new robust estimation method based on random projections that is adaptive and automatically produces a robust estimate, while enabling easy computations for high or infinite dimensional data. Under some restricted contamination models, the procedure is robust and attains full efficiency. We tested the method using both simulated and real data.Fil: Fraiman, Jacob Ricardo. Universidad de San Andrés; Argentina. Universidad de la República; Uruguay. Consejo Nacional de Investigaciones CientÃficas y Técnicas; ArgentinaFil: Svarc, Marcela. Consejo Nacional de Investigaciones CientÃficas y Técnicas; Argentina. Universidad de San Andrés; Argentin
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