Pages that link to "Item:Q2514169"
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The following pages link to High-dimensional principal projections (Q2514169):
Displaying 15 items.
- Estimation of eigenvalues, eigenvectors and scores in FDA models with dependent errors (Q272079) (← links)
- Optimal eigen expansions and uniform bounds (Q343789) (← links)
- Non-asymptotic adaptive prediction in functional linear models (Q900804) (← links)
- High-dimensional sufficient dimension reduction through principal projections (Q2136660) (← links)
- Lower bounds for invariant statistical models with applications to principal component analysis (Q2157446) (← links)
- Nonasymptotic upper bounds for the reconstruction error of PCA (Q2196210) (← links)
- High-probability bounds for the reconstruction error of PCA (Q2307416) (← links)
- Asymptotic properties of principal component projections with repeated eigenvalues (Q2407519) (← links)
- Theory for high-order bounds in functional principal components analysis (Q3598127) (← links)
- Nonparametric density estimation for intentionally corrupted functional data (Q5037795) (← links)
- Perturbation bounds for eigenspaces under a relative gap condition (Q5210923) (← links)
- On the number of principal components in high dimensions (Q5384592) (← links)
- Wald Statistics in high-dimensional PCA (Q5881043) (← links)
- Lasso in Infinite dimension: application to variable selection in functional multivariate linear regression (Q6144429) (← links)
- New perspectives in smoothing: minimax estimation of the mean and principal components of discretized functional data (Q6168063) (← links)
