Jochen Einbeck
Cited by
Cited by
Software for calculating blood lactate endurance markers
J Newell, D Higgins, N Madden, J Cruickshank, J Einbeck, K McMillan, ...
Journal of sports sciences 25 (12), 1403-1409, 2007
Local principal curves
J Einbeck, G Tutz, L Evers
Statistics and Computing 15, 301-313, 2005
Modelling beyond regression functions: an application of multimodal regression to speed–flow data
J Einbeck, G Tutz
Journal of the Royal Statistical Society Series C: Applied Statistics 55 (4 …, 2006
Weighted repeated median smoothing and filtering
R Fried, J Einbeck, U Gather
Journal of the American Statistical Association 102 (480), 1300-1308, 2007
Zero‐inflated regression models for radiation‐induced chromosome aberration data: A comparative study
M Oliveira, J Einbeck, M Higueras, E Ainsbury, P Puig, K Rothkamm
Biometrical Journal 58 (2), 259-279, 2016
Bandwidth selection for mean-shift based unsupervised learning techniques: a unified approach via self-coverage
J Einbeck
Journal of pattern recognition research. 6 (2), 2011
hdrcde: highest density regions and conditional density estimation. R package version 3.3
RJ Hyndman, J Einbeck, M Wand
Uncertainty of fast biological radiation dose assessment for emergency response scenarios
EA Ainsbury, M Higueras, P Puig, J Einbeck, D Samaga, JF Barquinero, ...
International Journal of Radiation Biology 93 (1), 127-135, 2017
Representing complex data using localized principal components with application to astronomical data
J Einbeck, L Evers, C Bailer-Jones
Principal manifolds for data visualization and dimension reduction, 178-201, 2008
npmlreg: Nonparametric maximum likelihood estimation for random effect models.[Online] http://CRAN
J Einbeck, R Darnell, J Hinde
R-project. org/package= npmlreg, 2009
Using principal curves to analyse traffic patterns on freeways
J Einbeck, J Dwyer
Transportmetrica 7 (3), 229-246, 2011
A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay
J Einbeck, EA Ainsbury, R Sales, S Barnard, F Kaestle, M Higueras
PLoS One 13 (11), e0207464, 2018
Data compression and regression through local principal curves and surfaces
J Einbeck, L Evers, B Powell
International journal of neural systems 20 (03), 177-192, 2010
A note on NPML estimation for exponential family regression models with unspecified dispersion parameter
J Einbeck, J Hinde
Austrian journal of statistics 35 (2&3), 233-243, 2006
A comparative study of nonparametric derivative estimators
J Newell, J Einbeck
Proc. of the 22nd International Workshop on Statistical Modelling, 2007
Exploring multivariate data structures with local principal curves
J Einbeck, G Tutz, L Evers
Classification—the Ubiquitous Challenge: Proceedings of the 28 th Annual …, 2005
A new and intuitive test for zero modification
P Wilson, J Einbeck
Statistical Modelling 19 (4), 341-361, 2019
Intrinsic dimensionality estimation for high-dimensional data sets: New approaches for the computation of correlation dimension
J Einbeck, Z Kalantan
Challenging the curse of dimensionality in multivariate local linear regression
J Taylor, J Einbeck
Computational Statistics 28, 955-976, 2013
Data compression and regression based on local principal curves
J Einbeck, L Evers, K Hinchliff
Advances in Data Analysis, Data Handling and Business Intelligence …, 2010
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