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pro vyhledávání: '"Chakraborty, Anirvan"'
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How can we discern whether the covariance operator of a stochastic process is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functiona
Externí odkaz:
http://arxiv.org/abs/1901.02333
Contamination of covariates by measurement error is a classical problem in multivariate regression, where it is well known that failing to account for this contamination can result in substantial bias in the parameter estimators. The nature and degre
Externí odkaz:
http://arxiv.org/abs/1712.04290
We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the
Externí odkaz:
http://arxiv.org/abs/1702.03556
Autor:
Das, Shantanab, Karuri, Saikat, Chakraborty, Joyeeta, Basu, Baidehi, Chandra, Aditi, Aravindan, S., Chakraborty, Anirvan, Paul, Debashis, Ray, Jay Gopal, Lechner, Matt, Beck, Stephan, Teschendorff, E. Andrew, Chatterjee, Raghunath
Publikováno v:
European Journal of Medical Research; 9/11/2024, Vol. 29 Issue 1, p1-15, 15p
We consider the problem of estimating the slope function in a functional regression with a scalar response and a functional covariate. This central problem of functional data analysis is well known to be ill-posed, thus requiring a regularised estima
Externí odkaz:
http://arxiv.org/abs/1610.00951
Tests based on sample mean vectors and sample spatial signs have been studied in the recent literature for high dimensional data with the dimension larger than the sample size. For suitable sequences of alternatives, we show that the powers of the me
Externí odkaz:
http://arxiv.org/abs/1505.05691
The sign and the signed-rank tests for univariate data are perhaps the most popular nonparametric competitors of the t test for paired sample problems. These tests have been extended in various ways for multivariate data in finite dimensional spaces.
Externí odkaz:
http://arxiv.org/abs/1411.6219
The Wilcoxon-Mann-Whitney test is a robust competitor of the t-test in the univariate setting. For finite dimensional multivariate data, several extensions of the Wilcoxon-Mann-Whitney test have been shown to have better performance than Hotelling's
Externí odkaz:
http://arxiv.org/abs/1403.0201
Publikováno v:
Annals of Statistics 2014, Vol. 42, No. 3, 1203-1231
The spatial distribution has been widely used to develop various nonparametric procedures for finite dimensional multivariate data. In this paper, we investigate the concept of spatial distribution for data in infinite dimensional Banach spaces. Many
Externí odkaz:
http://arxiv.org/abs/1402.3480