Maryna Prus
Maryna Prus
Research scientist, OvGU Magdeburg
Verified email at ovgu.de
Title
Cited by
Cited by
Year
Optimal designs for the prediction of individual parameters in hierarchical models
M Prus, R Schwabe
Journal of the Royal Statistical Society: Series B: Statistical Methodology …, 2016
212016
Optimal designs for the prediction in hierarchical random coefficient regression models
M Prus
Universitätsbibl., 2015
72015
Computing optimal experimental designs with respect to a compound Bayes risk criterion
R Harman, M Prus
Statistics & Probability Letters 137, 135-141, 2018
52018
Optimal designs for individual prediction in random coefficient regression models
M Prus, R Schwabe
Optimal Design of Experiments-Theory and Application: Proceedings of the …, 2011
52011
Optimal designs for the prediction of individual effects in random coefficient regression
M Prus, R Schwabe
mODa 10–Advances in Model-Oriented Design and Analysis, 211-218, 2013
42013
Interpolation and extrapolation in random coefficient regression models: optimal design for prediction
M Prus, R Schwabe
mODa 11-Advances in Model-Oriented Design and Analysis, 209-216, 2016
32016
Optimal designs in multiple group random coefficient regression models
M Prus
TEST 29 (1), 233-254, 2020
22020
Optimal designs for minimax-criteria in random coefficient regression models
M Prus
Statistical Papers 60 (2), 115-128, 2019
22019
Discussion of ‘Methods for planning repeated measures accelerated degradation tests’ by Brian P. Weaver and William Q. Meeker
R Schwabe, M Prus, U Graßhoff
Applied Stochastic Models in Business and Industry 30 (6), 677-679, 2014
22014
Various optimality criteria for the prediction of individual response curves
M Prus
Statistics & Probability Letters 146, 36-41, 2019
12019
Equivalence theorems for compound design problems with application in mixed models
M Prus
arXiv preprint arXiv:2007.14971, 2020
2020
Optimal Design in Hierarchical Random Effect Models for Individual Prediction with Application in Precision Medicine
M Prus, N Benda, R Schwabe
Journal of Statistical Theory and Practice 14, 1-12, 2020
2020
Optimizing the allocation of trials to sub-regions in multi-environment crop variety testing
M Prus, HP Piepho
arXiv preprint arXiv:2004.05925, 2020
2020
Optimal designs for minimax-criteria in random coefficient regression models (vol 286, pg 1501, 2019)
M Prus
STATISTICAL PAPERS 60 (5), 1800-1800, 2019
2019
Optimal Designs for Prediction in Two Treatment Groups Random Coefficient Regression Models
M Prus
arXiv preprint arXiv:1812.09514, 2018
2018
Optimal Design in Hierarchical Models with application in Multi-center Trials
M Prus, N Benda, R Schwabe
arXiv preprint arXiv:1807.10083, 2018
2018
Optimal designs for the prediction of individual parameters in hierarchical models Series B Statistical methodology
M Prus, R Schwabe
2016
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Articles 1–17