Publications
Publications
Referenzen
20.
Dominik Liebl
Inference for sparse and dense functional data with covariate adjustments
J. Multivariate Anal., 170:315--335
2019
19.
Dominik Liebl
Nonparametric testing for differences in electricity prices: the case of the Fukushima nuclear accident
Ann. Appl. Stat., 13(2):1128--1146
2019
18.
Dominik Liebl und Fabian Walders
Parameter regimes in partial functional panel regression
Econom. Stat., 11:105--115
2019
17.
Dominik Liebl und Stefan Rameseder
Partially observed functional data: the case of systematically missing parts
Comput. Statist. Data Anal., 131:104--115
2019
16.
Dominik Liebl
Finite sample correction for two-sample inference with sparse covariate adjusted functional data
Working Paper arXiv:1711.03367 (Revise and Resubmit at the Annals of Applied Statistics), :1--27
2017
15.
Dominik Liebl, Stefan Rameseder und Christoph Rust
Functional insights into Google AdWords
Working Paper arXiv:1709.02166, :1--21
2017
14.
Dominik Liebl
Inference for functional data with covariate adjustments: From sparse to dense and everything in-between
Working Paper arXiv:1601.07780 (Revise and Resubmit at the Journal of Multivariate Statistics), :1--30
2017
13.
Alois Kneip und Dominik Liebl
On the optimal reconstruction of partially observed functional data
Working Paper arXiv:1710.10099, :1--53
2017
12.
Dominik Liebl und Fabian Walders
Parameter regimes in partial functional panel regression
Working Paper arXiv:1709.05786, :1--51
2017
11.
Fabian Walders und Dominik Liebl
Parameter regimes in partially functional linear regression for panel data
Functional Statistics and Related Fields, :261--270
2017
10.
Fabian Walders und Dominik Liebl
Parameter regimes in partially functional linear regression for panel data
Functional statistics and related fields aus Contrib. Stat.
Seite 261--270.
Herausgeber: Springer, Cham,
2017
9.
Dominik Liebl, Steffen Willwacher, Joseph Hamill und Gert-Peter Brüggemann
Ankle plantarflexion strength in rearfoot and forefoot runners: A novel clusteranalytic approach
Human Movement Science, 35:104--120
2014
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