The following pages link to J. S. Marron (Q1070701):
Displaying 50 items.
- Best possibility constant for bandwidth selection (Q1208659) (← links)
- Runze Li (Q1274829) (← links)
- Assessing bandwidth selectors with visual error criteria (Q1297878) (← links)
- Robust principal component analysis for functional data. (With comments) (Q1302060) (← links)
- Curve estimation when the design density is low (Q1359422) (← links)
- On the role of the shrinkage parameter in local linear smoothing (Q1368746) (← links)
- On automatic boundary corrections (Q1372853) (← links)
- Semi-parametric multivariate modelling when the marginals are the same (Q1403420) (← links)
- SiZer for length biased, censored density and hazard estimation. (Q1427804) (← links)
- A general projection framework for constrained smoothing. (Q1431205) (← links)
- Choosing a kernel regression estimator. With comments and a rejoinder by the authors (Q1596033) (← links)
- An assessment of finite sample performance of adaptive methods in density estimation (Q1606486) (← links)
- Nested nonnegative cone analysis (Q1663282) (← links)
- Significance analysis for pairwise variable selection in classification (Q1748876) (← links)
- Functional data analysis of amplitude and phase variation (Q1790299) (← links)
- Progress in data-based bandwidth selection for kernel density estimation (Q1815673) (← links)
- Convergence properties of an empirical error criterion for multivariate density estimation (Q1821451) (← links)
- Scale space view of curve estimation. (Q1848781) (← links)
- Improved variable window kernel estimates of probability densities (Q1895340) (← links)
- A curious property of the derivatives of the Cauchy density (Q1916196) (← links)
- Comparison of binary discrimination methods for high dimension low sample size data (Q1941430) (← links)
- Consistency of sparse PCA in high dimension, low sample size contexts (Q1941448) (← links)
- Deconvolution estimation of mixture distributions with boundaries (Q1951116) (← links)
- Varying coefficient model for modeling diffusion tensors along white matter tracts (Q1951522) (← links)
- Joint and individual variation explained (JIVE) for integrated analysis of multiple data types (Q1951546) (← links)
- Visualizing the structure of large trees (Q1952191) (← links)
- Geometric insights into support vector machine behavior using the KKT conditions (Q2074327) (← links)
- Joint and individual analysis of breast cancer histologic images and genomic covariates (Q2078283) (← links)
- Response to `Fitting a folded normal distribution without EM' (Q2078798) (← links)
- High dimension low sample size asymptotics of robust PCA (Q2259533) (← links)
- Bootstrap simultaneous error bars for nonparametric regression (Q2277704) (← links)
- Data science vs. statistics: two cultures? (Q2329839) (← links)
- Least squares sieve estimation of mixture distributions with boundary effects (Q2355260) (← links)
- Sizer for time series: a new approach to the analysis of trends (Q2426804) (← links)
- Analysis of nonlinear modes of variation for functional data (Q2426822) (← links)
- A scale-based approach to finding effective dimensionality in manifold learning (Q2426829) (← links)
- Visualizing genetic constraints (Q2443152) (← links)
- Object oriented data analysis: sets of trees (Q2466673) (← links)
- SiZer for smoothing splines (Q2488419) (← links)
- Backwards principal component analysis and principal nested relations (Q2513413) (← links)
- Tree-oriented analysis of brain artery structure (Q2513418) (← links)
- Mode testing via the excess mass estimate (Q2775643) (← links)
- Intuitive, localized analysis of shape variability (Q2780019) (← links)
- The statistics and mathematics of high dimension low sample size asymptotics (Q2828626) (← links)
- A general framework for consistency of principal component analysis (Q2834478) (← links)
- Analysis of principal nested spheres (Q2913850) (← links)
- Overview of object oriented data analysis (Q2922172) (← links)
- Rejoinder to the discussion of: Overview of object-oriented data analysis (Q2922185) (← links)
- Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data (Q3069864) (← links)
- Biclustering via Sparse Singular Value Decomposition (Q3076038) (← links)
