Zobrazeno 1 - 10
of 157
pro vyhledávání: '"Akritas, P"'
Publikováno v:
Computational Science - ICCS 2006: 6th Int. Conf., UK, May 28-31, 2006. Proc., Part II, LNCS 3992, Springer Berlin, 486-489
The best method for computing the adjoint matrix of an order $n$ matrix in an arbitrary commutative ring requires $O(n^{\beta+1/3}\log n \log \log n)$ operations, provided the complexity of the algorithm for multiplying two matrices is $\gamma n^\bet
Externí odkaz:
http://arxiv.org/abs/1711.09450
Akademický článek
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Let X; Z be r and s-dimensional covariates, respectively, used to model the response variable Y as Y = m(X;Z) + \sigma(X;Z)\epsilon. We develop an ANOVA-type test for the null hypothesis that Z has no influence on the regression function, based on re
Externí odkaz:
http://arxiv.org/abs/1205.6843
Let X be a d dimensional vector of covariates and Y be the response variable. Under the nonparametric model Y = m(X) + {\sigma}(X) \in we develop an ANOVA-type test for the null hypothesis that a particular coordinate of X has no influence on the reg
Externí odkaz:
http://arxiv.org/abs/1205.6761
Autor:
Kim, Min Hee, Akritas, Michael G.
Publikováno v:
Annals of Statistics 2010, Vol. 38, No. 4, 2314-2350
A new thresholding method, based on L-statistics and called order thresholding, is proposed as a technique for improving the power when testing against high-dimensional alternatives. The new method allows great flexibility in the choice of the thresh
Externí odkaz:
http://arxiv.org/abs/1010.4123
We assess Coarse Graining by studying different partitions of the phase space of the Baker transformation and the periodic torus automorphisms. It turns out that the shape of autocorrelation functions for the Baker transformation is more or less repr
Externí odkaz:
http://arxiv.org/abs/physics/0101077
Akademický článek
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Publikováno v:
Astrophys.J. 470 (1996) 706
Two new methods are proposed for linear regression analysis for data with measurement errors. Both methods are designed to accommodate intrinsic scatter in addition to measurement errors. The first (BCES) is a direct extension of the ordinary least s
Externí odkaz:
http://arxiv.org/abs/astro-ph/9605002
Autor:
Akritas, M. G., Siebert, J.
A new procedure is presented, which allows, based on Kendall's $\tau$, to test for partial correlation in the presence of censored data. Further, a significance level can be assigned to the partial correlation -- a problem which hasn't been addressed
Externí odkaz:
http://arxiv.org/abs/astro-ph/9508018
Publikováno v:
Journal of Statistical Software, Vol 77, Iss 1, Pp 1-28 (2017)
We describe the R package NonpModelCheck for hypothesis testing and variable selection in nonparametric regression. This package implements functions to perform hypothesis testing for the significance of a predictor or a group of predictors in a full
Externí odkaz:
https://doaj.org/article/25edc6f37c1c43c385b0e44f6035a381
