Affiner les résultats

MissForest—non-parametric missing value imputation for mixed-type data

Stekhoven, Daniel J. ; Bühlmann, Peter

In: Bioinformatics, 2012, vol. 28, no. 1, p. 112-118

Model-based boosting in high dimensions

Hothorn, Torsten ; Bühlmann, Peter

In: Bioinformatics, 2006, vol. 22, no. 22, p. 2828-2829

Low-Order Conditional Independence Graphs for Inferring Genetic Networks

Wille, Anja ; Bühlmann, Peter

In: Statistical Applications in Genetics and Molecular Biology, 2006, vol. 5, no. 1, p. -

Lower bounds for the number of false null hypotheses for multiple testing of associations under general dependence structures

Meinshausen, Nicolai ; Bühlmann, Peter

In: Biometrika, 2005, vol. 92, no. 4, p. 893-907

A systematic comparison and evaluation of biclustering methods for gene expression data

Prelić, Amela ; Bleuler, Stefan ; Zimmermann, Philip ; Wille, Anja ; Bühlmann, Peter ; Gruissem, Wilhelm ; Hennig, Lars ; Thiele, Lothar ; Zitzler, Eckart

In: Bioinformatics, 2006, vol. 22, no. 9, p. 1122-1129

Selection of Credibility Regression Models

Bühlmann, Peter ; Bühlmann, Hans

In: ASTIN Bulletin, 1999, vol. 29, no. 2, p. 245-270

Boosting for tumor classification with gene expression data

Dettling, Marcel ; Bühlmann, Peter

In: Bioinformatics, 2003, vol. 19, no. 9, p. 1061-1069

Causal stability ranking

Stekhoven, Daniel J. ; Moraes, Izabel ; Sveinbjörnsson, Gardar ; Hennig, Lars ; Maathuis, Marloes H. ; Bühlmann, Peter

In: Bioinformatics, 2012, vol. 28, no. 21, p. 2819-2823

Volatility estimation with functional gradient descent for very high-dimensional financial time series

Bühlmann, Peter

We propose a functional gradient descent algorithm (FGD) for estimating volatility and conditional covariances (given the past) for very high-dimensional financial time series of asset price returns. FGD is a kind of hybrid of nonparametric statistical function estimation and numerical optimization. Our FGD algorithm is computationally feasible in multivariate problems with dozens up to thousands...

Synchronizing multivariate financial time series

Audrino, Francesco ; Bühlmann, Peter

Prices or returns of financial assets are most often collected in local times of the trading markets. The need to synchronize multivariate time series of financial prices or returns is motivated by the fact that information continues to flow for closed markets while others are still open. We propose here a synchronization technique which takes this into account. Besides the nice interpretation...