Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Katharina Proksch"'
Publikováno v:
Scandinavian journal of statistics, 48(3), 1001-1017. Wiley-Blackwell
The question whether structural changes in time-resolved images are of statistical significance or merely emerge from random noise is of great relevance in many practical applications such as live cell fluorescence microscopy, where intracellular dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb8dbd929aab8a34612f40992182f058
http://www.scopus.com/inward/record.url?scp=85102782882&partnerID=8YFLogxK
http://www.scopus.com/inward/record.url?scp=85102782882&partnerID=8YFLogxK
In various applications of regression analysis, in addition to errors in the dependent observations also errors in the predictor variables play a substantial role and need to be incorporated in the statistical modeling process. In this paper we consi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d988ed8437546ee0bc09d00119b2c47
http://arxiv.org/abs/2009.00936
http://arxiv.org/abs/2009.00936
Publikováno v:
Topics in Applied Physics ISBN: 9783030344122
In this chapter we discuss how to obtain statistical guarantees in photonic imaging. We start with an introduction to hypothesis testing in the context of imaging, more precisely we describe how to test if there is signal in a specific region of inte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76e100c8abf6f599ad8e92dcf187bcae
https://doi.org/10.1007/978-3-030-34413-9_11
https://doi.org/10.1007/978-3-030-34413-9_11
Publikováno v:
Annals of the Institute of Statistical Mathematics. 70:647-689
In this paper we propose methods for inference of the geometric features of a multivariate density. Our approach uses multiscale tests for the monotonicity of the density at arbitrary points in arbitrary directions. In particular, a significance test
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3d6319116803f8790b9074e4cf36a82
https://doi.org/10.1007/s10463-017-0605-1
https://doi.org/10.1007/s10463-017-0605-1
Publikováno v:
Electron. J. Statist. 13, no. 2 (2019), 2257-2306
Electronic Journal of Statistics, 13(2), 2257-2306. Institute of Mathematical Statistics
Electronic Journal of Statistics, 13(2), 2257-2306. Institute of Mathematical Statistics
The random coefficients model is an extension of the linear regression model that allows for unobserved heterogeneity in the population by modeling the regression coefficients as random variables. Given data from this model, the statistical challenge
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https://explore.openaire.eu/search/publication?articleId=doi_dedup___::926021b9fe015abb2dd43880021d1fd3
https://projecteuclid.org/euclid.ejs/1562140822
https://projecteuclid.org/euclid.ejs/1562140822
Publikováno v:
Frontiers in Veterinary Science. 6
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef4f15d99c7f1f70cabd8b3c046a7870
https://doi.org/10.3389/conf.fvets.2019.05.00059
https://doi.org/10.3389/conf.fvets.2019.05.00059
Publikováno v:
Ann. Statist. 46, no. 6B (2018), 3569-3602
The Annals of Statistics
The Annals of Statistics
In this paper we propose a multiscale scanning method to determine active components of a quantity $f$ w.r.t. a dictionary $\mathcal{U}$ from observations $Y$ in an inverse regression model $Y=Tf+\xi$ with linear operator $T$ and general random error
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ed3f454ca9e05754842c50bfc772f06
https://projecteuclid.org/euclid.aos/1536631284
https://projecteuclid.org/euclid.aos/1536631284
Autor:
Christoph Brune, Felix Lucka, Katharina Proksch, Holger Dette, Martin Burger, Frank Wübbeling, Nicolai Bissantz
Publikováno v:
Inverse Problems and Imaging, 12(5), 1121-1155. American Institute of Mathematical Sciences
Inverse Problems and Imaging, 12(5), 1121-1155
Inverse Problems and Imaging, 12(5), 1121-1155
This paper discusses the properties of certain risk estimators that recently regained popularity for choosing regularization parameters in ill-posed problems, in particular for sparsity regularization. They apply Stein’s unbiased risk estimator (SU
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a837b4291ebe2b5159a0abb55e462152
https://research.utwente.nl/en/publications/0bc26618-5e6e-4097-a08c-4b38b425fc2d
https://research.utwente.nl/en/publications/0bc26618-5e6e-4097-a08c-4b38b425fc2d
Autor:
Katharina Proksch
Publikováno v:
Annals of the Institute of Statistical Mathematics. 68:209-236
In a multivariate nonparametric regression problem with fixed, deterministic design asymptotic, uniform confidence bands for the regression function are constructed. The construction of the bands is based on the asymptotic distribution of the maximal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::916ca09fdd8804602a53e34abca0f1a9
https://doi.org/10.1007/s10463-014-0494-5
https://doi.org/10.1007/s10463-014-0494-5
Publikováno v:
Journal of Multivariate Analysis. 128:86-107
Recovering a function f from its integrals over hyperplanes (or line integrals in the two-dimensional case), that is, recovering f from the Radon transform R f of f , is a basic problem with important applications in medical imaging such as computeri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62eb4f140ebca39016b041a2a22b21ff
https://doi.org/10.1016/j.jmva.2014.03.005
https://doi.org/10.1016/j.jmva.2014.03.005