The following pages link to Inge Koch (Q262371):
Displaying 27 items.
- Feature extraction for proteomics imaging mass spectrometry data (Q262375) (← links)
- Robustifying principal component analysis with spatial sign vectors (Q434715) (← links)
- Pattern recognition based on canonical correlations in a high dimension low sample size context (Q444992) (← links)
- Proteomics profiles from mass spectrometry (Q470433) (← links)
- Analysis of proteomics data: impact of alignment on classification (Q470443) (← links)
- Rejoinder: Analysis of proteomics data (Q470447) (← links)
- Penalized spline support vector classifiers computational issues (Q626242) (← links)
- An application of comonotonicity and convex ordering to present values with truncated stochastic interest rates (Q882461) (← links)
- Feature significance for multivariate kernel density estimation (Q1023768) (← links)
- On the asymptotic performance of median smoothers in image analysis and nonparametric regression (Q1354398) (← links)
- Prediction of multivariate responses with a selected number of principal components (Q2445634) (← links)
- Polynomial histograms for multivariate density and mode estimation (Q2911705) (← links)
- Measuring Comonotonicity in M-Dimensional Vectors (Q3008261) (← links)
- A New Method for the Construction of Bivariate Archimedean Copulas Based on the λ Function (Q3017874) (← links)
- On continuous image models and image analysis in the presence of correlated noise (Q3488956) (← links)
- DESIGNING RELEVANT FEATURES FOR CONTINUOUS DATA SETS USING ICA (Q3629854) (← links)
- On the Feasibility of Cross-Validation in Image Analysis (Q3989038) (← links)
- Asymptotic bias and variance of a kernel-based estimator for the location of a discontinuity (Q4352133) (← links)
- Tests for monotonicity of a regression mean with guaranteed level (Q4520228) (← links)
- (Q4981589) (← links)
- Kernel naive Bayes discrimination for high‐dimensional pattern recognition (Q5117650) (← links)
- Highest Density Difference Region Estimation with Application to Flow Cytometric Data (Q5123228) (← links)
- Sparse Principal Component Analysis With Preserved Sparsity Pattern (Q5238331) (← links)
- Evaluating the Contributions of Individual Variables to a Quadratic Form (Q5361193) (← links)
- Analysis of Multivariate and High-Dimensional Data (Q5401636) (← links)
- Dimension Selection for Feature Selection and Dimension Reduction with Principal and Independent Component Analysis (Q5423024) (← links)
- Robustness of principal component analysis with Spearman's rank matrix (Q6537386) (← links)
