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pro vyhledávání: '"Jankowski, Hanna"'
Autor:
Jankowski, Hanna Katarzyna.
Thesis (Ph. D.)--University of Toronto, 2006.
Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3834. Advisor: Jeremy Quastel.
Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3834. Advisor: Jeremy Quastel.
We study the problem of multiple hypothesis testing for multidimensional data when inter-correlations are present. The problem of multiple comparisons is common in many applications. When the data is multivariate and correlated, existing multiple com
Externí odkaz:
http://arxiv.org/abs/1411.1329
Autor:
Jankowski, Hanna
Publikováno v:
Annals of Statistics 2014, Vol. 42, No. 2, 625-653
Under the assumption that the true density is decreasing, it is well known that the Grenander estimator converges at rate $n^{1/3}$ if the true density is curved [Sankhy\={a} Ser. A 31 (1969) 23-36] and at rate $n^{1/2}$ if the density is flat [Ann.
Externí odkaz:
http://arxiv.org/abs/1207.6614
Publikováno v:
J. R. Stat. Soc. Ser. B Stat. Methodol., 2013, 75(4), 769-790
The assumption of log-concavity is a flexible and appealing nonparametric shape constraint in distribution modelling. In this work, we study the log-concave maximum likelihood estimator (MLE) of a probability mass function (pmf). We show that the MLE
Externí odkaz:
http://arxiv.org/abs/1107.3904
Autor:
Jankowski, Hanna K., Wellner, Jon A.
We study and compare three estimators of a discrete monotone distribution: (a) the (raw) empirical estimator; (b) the "method of rearrangements" estimator; and (c) the maximum likelihood estimator. We show that the maximum likelihood estimator strict
Externí odkaz:
http://arxiv.org/abs/0910.3221
Image analysis frequently deals with shape estimation and image reconstruction. The ob jects of interest in these problems may be thought of as random sets, and one is interested in finding a representative, or expected, set. We consider a definition
Externí odkaz:
http://arxiv.org/abs/0903.1869
Shape estimation and object reconstruction are common problems in image analysis. Mathematically, viewing objects in the image plane as random sets reduces the problem of shape estimation to inference about sets. Currently existing definitions of the
Externí odkaz:
http://arxiv.org/abs/0903.1846
We establish limit theory for the Grenander estimator of a monotone density near zero. In particular we consider the situation when the true density $f_0$ is unbounded at zero, with different rates of growth to infinity. In the course of our study we
Externí odkaz:
http://arxiv.org/abs/0902.4453
Akademický článek
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Autor:
Jankowski, Hanna K., Wellner, Jon A.
Publikováno v:
Bernoulli 2009, Vol. 15, No. 4, 1010-1035
In this paper, we study the nonparametric maximum likelihood estimator (MLE) of a convex hazard function. We show that the MLE is consistent and converges at a local rate of $n^{2/5}$ at points $x_0$ where the true hazard function is positive and str
Externí odkaz:
http://arxiv.org/abs/0801.0712