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Almond Stöcker
Almond Stöcker
PostDoc, École Polytechnic Fédéral de Lausanne (EPFL)
Bestätigte E-Mail-Adresse bei epfl.ch
Titel
Zitiert von
Zitiert von
Jahr
Quantifying alternative splicing from paired-end RNA-sequencing data
D Rossell, CSO Attolini, M Kroiss, A Stöcker
The annals of applied statistics 8 (1), 309, 2014
522014
The effect of rapid relative humidity changes on fast filter-based aerosol-particle light-absorption measurements: uncertainties and correction schemes
S Düsing, B Wehner, T Müller, A Stöcker, A Wiedensohler
Atmospheric Measurement Techniques 12 (11), 5879-5895, 2019
192019
Multivariate functional additive mixed models
A Volkmann, A Stöcker, F Scheipl, S Greven
Statistical Modelling 23 (4), 303-326, 2023
162023
Elastic analysis of irregularly or sparsely sampled curves
L Steyer, A Stöcker, S Greven
Biometrics 79 (3), 2103-2115, 2023
132023
Boosting functional response models for location, scale and shape with an application to bacterial competition
A Stöcker, S Brockhaus, SA Schaffer, B Bronk, M Opitz, S Greven
Statistical Modelling 21 (5), 385-404, 2021
112021
Pedestrian exposure to black carbon and PM2.5 emissions in urban hot spots: new findings using mobile measurement techniques and flexible Bayesian …
HD Alas, A Stöcker, N Umlauf, O Senaweera, S Pfeifer, S Greven, ...
Journal of exposure science & environmental epidemiology 32 (4), 604-614, 2022
102022
Additive density-on-scalar regression in Bayes Hilbert spaces with an application to gender economics
EM Maier, A Stöcker, B Fitzenberger, S Greven
arXiv preprint arXiv:2110.11771, 2021
82021
Functional additive regression on shape and form manifolds of planar curves
A Stöcker, S Greven
arXiv preprint arXiv:2109.02624, 2021
8*2021
sparseFLMM: Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data
J Cederbaum, A Volkmann, A Stöcker
R package version 0.3. 0, URL https://CRAN. R-project. org/package= sparseFLMM, 2019
62019
Elastic full Procrustes analysis of plane curves via Hermitian covariance smoothing
A Stöcker, M Pfeuffer, L Steyer, S Greven
arXiv preprint arXiv:2203.10522, 2022
42022
Package ‘FDboost’
S Brockhaus, D Ruegamer, A Stoecker, T Hothorn
32023
A Bayesian Time-Varying Autoregressive Model for Improved Short-and Long-Term Prediction
C Berninger, A Stöcker, D Rügamer
arXiv preprint arXiv:2006.05750, 2020
22020
A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction
C Berninger, A Stöcker, D Rügamer
Journal of Forecasting 41 (1), 181-200, 2022
12022
Comments on: shape-based functional data analysis
A Stöcker, L Steyer, S Greven
TEST, 1-11, 2023
2023
4. Paper III: Regression in Quotient Metric Spaces with a Focus On Elastic Curves
L Steyer, A Stöcker, S Greven
Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2023
2023
Elastic regression for irregularly sampled curves in
L Steyer, A Stöcker, S Greven
arXiv preprint arXiv:2305.02075, 2023
2023
5. Paper IV: Functional Additive Models on Manifolds of Planar Shapes and Forms
A Stöcker, L Steyer, S Greven
Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2023
2023
Flexible regression for functional object data: curves, shapes and densities
A Stöcker
lmu, 2022
2022
3. Paper II: Elastic Full Procrustes Analysis of Plane Curves via Hermitian Covariance Smoothing
A Stöcker, M Pfeuffer, L Steyer, S Greven
Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2022
2022
2. Paper I: Elastic Analysis of Irregularly or Sparsely Sampled Curves
L Steyer, A Stöcker, S Greven
Statistical Methods for Sparse Functional Object Data: Elastic Curves …, 2022
2022
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