An R package for testing high-dimensional covariance matrices
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Oct 5, 2017 - R
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sparse-pca
Here are 7 public repositories matching this topic...
Gradient-based Fantope projection and selection algorithm for sparse PCA
constrained-optimization eigenvalue convex-optimization sparse-pca sparse-principal-component-analysis eigenvector
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Jul 17, 2022 - C
An R Package for Sparse PCA with Multiple Principal Components
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Jun 29, 2026 - C++
machine-learning clustering cancer-genomics kmeans-clustering sparse-pca rna-seq-data elbow-method liver-cancer one-hot-encoding
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Jan 20, 2020 - Jupyter Notebook
TopoSPCA: Topology-Dependent Robustness in Graph-Regularized Sparse PCA
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Apr 2, 2026 - Python
Subspace projection methods (PCA, SPCA, SSPCA, KernelPCA, Isomap) for visual classification. Structured Sparse PCA with co-clustering outperforms baselines on VOC and Caltech benchmarks. Published at BigMM 2017.
python computer-vision scikit-learn pca dimensionality-reduction bag-of-words manifold-learning sparse-pca visual-classification structured-sparse-pca
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Mar 5, 2026 - Python
Out-of-sample volatility forecasting and Value-at-Risk backtesting for 14 currencies (2000–2026): GARCH/EGARCH/GJR vs. RiskMetrics, with QLIKE and Diebold-Mariano model comparison, Kupiec/Christoffersen VaR coverage tests, and sparse PCA on FX returns. Python.
python time-series forex econometrics quantitative-finance garch sparse-pca value-at-risk risk-management backtesting egarch volatility-forecasting
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Jul 10, 2026 - Python
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