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Very high dimensional semiparametric models. Abstracts from the workshop held October 2–8, 2011. (English) Zbl 1349.00200

Summary: Very high dimensional semiparametric models play a major role in many areas, in particular in signal detection problems when sparse signals or sparse events are hidden among high dimensional noise. Concrete examples are genomic studies in biostatistics or imaging problems. In a broad context all kind of statistical inference and model selection problems were discussed for high dimensional data.

MSC:

00B05 Collections of abstracts of lectures
00B25 Proceedings of conferences of miscellaneous specific interest
62-06 Proceedings, conferences, collections, etc. pertaining to statistics
62G10 Nonparametric hypothesis testing
62G05 Nonparametric estimation
62J15 Paired and multiple comparisons; multiple testing
62F15 Bayesian inference
62G20 Asymptotic properties of nonparametric inference
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References:

[1] J. Horowitz; E. Mammen, Rate-optimal estimation for a general class of nonparametric regression models with unknown link functions., Ann. Statist. 35 (2007). · Zbl 1129.62034
[2] A. Juditsky; O. Lepski; A. Tsybakov Nonparametric estimation of composite functions, Ann. Statist. 37 (2009). High-dimensional causal inference Peter B”uhlmann
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