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M. Schwarz

4 papers hereh-index 6151 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.ST4
same name
  • M. Schwarz — 24 papers, h 12
  • M. Schwarz — 12 papers, h 8
  • M. Schwarz — 9 papers, h 13
  • M. Schwarz — 8 papers, h 13
  • M. Schwarz — 6 papers, h 3
  • M. Schwarz — 5 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092013
most citedOn the identifiability of copulas in bivariate competing risks models

19 citations · 32 across the 2 of their papers we have counts for

collaborators

4 papers

math.ST2013★ 19 cited

On the identifiability of copulas in bivariate competing risks models

Maik Schwarz, Geurt Jongbloed, Ingrid Van Keilegom

In competing risks models, the joint distribution of the event times is not identifiable even when the margins are fully known, which has been referred to as the "identifiability c…

math.ST2012★ 13 cited

Adaptive Gaussian inverse regression with partially unknown operator

Jan Johannes, Maik Schwarz

This work deals with the ill-posed inverse problem of reconstructing a function f given implicitly as the solution of g=Af, where A is a compact linear operator with unknow…

math.ST2010

Partially adaptive nonparametric instrumental regression

Jan Johannes, Maik Schwarz

We consider the problem of estimating the structural function in nonparametric instrumental regression, where in the presence of an instrument W a response Y is modeled in dependen…

math.ST2009

Adaptive circular deconvolution by model selection under unknown error distribution

Jan Johannes, Maik Schwarz

We consider a circular deconvolution problem, in which the density f of a circular random variable X must be estimated nonparametrically based on an i.i.d. sample from a noisy…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.