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Carsten Jentsch

As seen in: arXiv, PeerJ
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Articles by Carsten Jentsch

[2610.11860] Nonparametric covariance estimation with bias correction for spatial lattice processes

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By Carsten Jentsch
| arXiv
[Submitted on 8 Oct 2026] Title:Nonparametric covariance estimation with bias correction for spatial lattice processes View a PDF of the paper titled Nonparametric covariance estimation with bias correction for spatial lattice processes, by Antonio Fioravanti and Carsten Jentsch View PDF HTML (experimental) Abstract:Accurate covariance estimation is crucial for spatial data analysis.
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[2601.22410] Word-Centered Semantic Graphs for Interpretable Diachronic Sense Tracking

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By Kai-Robin Lange, Jonas Rieger, Carsten Jentsch
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Zeitenwenden: Detecting changes in the German political discourse

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By Jonas Rieger, Carsten Jentsch, Niklas Benner
| arXiv
Open access is only possible with YOUR support. Give to arXiv this week to help keep science open for all.
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[2410.00942] AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction

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By Cabrel Teguemne, Carsten Jentsch, Michel Lang, Markus Pauly
| arXiv
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LDAPrototype: a model selection algorithm to improve reliability of latent Dirichlet allocation

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By Byun Y-C, Carsten Jentsch, Jörg Rahnenführer, Jordan MI
| PeerJ
Topic modeling is popular for understanding text data, though the analysis of the reliability of topic models is rarely part of applications. This is caused by plenty of possibilities for measuring stability, but missing strategies for increasing reliability without touching the original fitting procedure. We have presented a novel method to address the reliability issue caused by the inherent instability of the LDA procedure.
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The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States: Comment

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By Kurt G. Lunsford, Carsten Jentsch
| aeaweb.org
Abstract Mertens and Ravn (2013) estimate impulse response functions (IRFs) from income tax changes in a structural vector autoregression (SVAR) by using narrative accounts of tax liability changes as proxy variables. To produce confidence intervals for their IRFs, they use a residual-based wild bootstrap, which has subsequently become popular in the proxy SVAR literature. We argue that their wild bootstrap is not valid, producing confidence intervals that are much too small.
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