Carsten Jentsch
Carsten Jentsch
Professor of Business and Social Statistics, TU Dortmund University
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Zitiert von
Zitiert von
Inference in VARs with conditional heteroskedasticity of unknown form
R Brüggemann, C Jentsch, C Trenkler
Journal of econometrics 191 (1), 69-85, 2016
Covariance matrix estimation and linear process bootstrap for multivariate time series of possibly increasing dimension
C Jentsch, DN Politis
Annals of Statistics 43 (3), 1117-1140, 2015
A test for second order stationarity of a multivariate time series
C Jentsch, SS Rao
Journal of Econometrics 185 (1), 124-161, 2015
The multiple hybrid bootstrap—resampling multivariate linear processes
C Jentsch, JP Kreiss
Journal of Multivariate Analysis 101 (10), 2320-2345, 2010
The dynamic effects of personal and corporate income tax changes in the United States: Comment
C Jentsch, KG Lunsford
American Economic Review 109 (7), 2655-78, 2019
Proxy SVARs: asymptotic theory, bootstrap inference, and the effects of income tax changes in the United States
C Jentsch, KG Lunsford
FRB of Cleveland Working Paper, 2016
Testing equality of spectral densities using randomization techniques
C Jentsch, M Pauly
Bernoulli 21 (2), 697-739, 2015
A note on using periodogram-based distances for comparing spectral densities
C Jentsch, M Pauly
Statistics & probability letters 82 (1), 158-164, 2012
Baxter’s inequality and sieve bootstrap for random fields
M Meyer, C Jentsch, JP Kreiss
Bernoulli 23 (4B), 2988-3020, 2017
Bootstrapping sample quantiles of discrete data
C Jentsch, A Leucht
Annals of the Institute of Statistical Mathematics 68 (3), 491-539, 2016
A new frequency domain approach of testing for covariance stationarity and for periodic stationarity in multivariate linear processes
C Jentsch
Journal of Time Series Analysis 33 (2), 177-192, 2012
A Spectral Domain Test for Stationarity of Spatio‐Temporal Data
S Bandyopadhyay, C Jentsch, S Subba Rao
Journal of Time Series Analysis 38 (2), 326-351, 2017
Block bootstrap theory for multivariate integrated and cointegrated processes
C Jentsch, DN Politis, E Paparoditis
Journal of Time Series Analysis 36 (3), 416-441, 2015
Valid resampling of higher-order statistics using the linear process bootstrap and autoregressive sieve bootstrap
C Jentsch, DN Politis
Communications in Statistics-Theory and Methods 42 (7), 1277-1293, 2013
Asymptotically valid bootstrap inference for Proxy SVARs
C Jentsch, KG Lunsford
FRB of Cleveland Working Paper, 2019
Empirical Characteristic Functions‐Based Estimation and Distance Correlation for Locally Stationary Processes
C Jentsch, A Leucht, M Meyer, C Beering
Journal of Time Series Analysis 41 (1), 110-133, 2020
Bootstrapping INAR models
C Jentsch, CH Weiß
Bernoulli 25 (3), 2359-2408, 2019
Guaranteed conditional ARL performance in the presence of autocorrelation
CH Weiß, D Steuer, C Jentsch, MC Testik
Computational Statistics & Data Analysis 128, 367-379, 2018
Improving Reliability of Latent Dirichlet Allocation by Assessing Its Stability Using Clustering Techniques on Replicated Runs
J Rieger, L Koppers, C Jentsch, J Rahnenführer
arXiv preprint arXiv:2003.04980, 2020
Asymptotik eines nicht-parametrischen Kernschatzers f ur zeitvariable autoregressive Prozesse
C Jentsch
Diploma thesis, University of Braunschweig, 2006
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