pca: A Python Package for Principal Component Analysis.
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Apr 24, 2025 - Jupyter Notebook
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hotelling-t2
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Python implementation of the control charts used for process monitoring and anomaly detection
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Jun 18, 2023 - Python
The HotellingEllipse package helps draw the Hotelling's T-squared ellipse on a PCA or PLS score scatterplot by computing the Hotelling's T-squared statistic and providing the ellipse's coordinates, semi-minor, and semi-major axes lengths.
pca outliers rstats principal-component-analysis partial-least-squares-regression pls confidence-ellipse hotelling-t2 hotelling-s-t-square hotelling-ellipse multivariate-distribution hotellings-t2-distribution
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Jan 4, 2025 - R
A collection of simple parameter estimation and significance tests for the comparison of multivariate means and variation, covered in Chapters 4 and 5 of the book Multivariate Statistical Methods. A Primer. 5th edition.
statistical-inference hypothesis-testing multivariate-analysis levene-test covariance-matrices two-sample-t-test multivariate-analysis-in-r statistical-estimation hotelling-t2 one-way-manova van-valen-test box-m-test penrose-distance
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May 21, 2025 - R
Hotellings T^2 Statistics Two sample Problem
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Nov 21, 2019
Analyze a dataset on muscular dystrophy and make statistical inferences
data-science statistical-analysis logistic-regression k-means-clustering linear-discriminant-analysis-lda hotelling-t2
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Jan 28, 2023 - Jupyter Notebook
In this repository you find a python program and the prints and 3D-visualization of it. After the KNN-Classification I wanted to know which variables have the most relevance for the results. One approach for this is the Principal-Component-Analysis (PCA). More details in the python program as comments.
python statistics decentralized neuroscience outliers dimensionality-reduction data-analysis hacktoberfest time-warp 3d-plot explained-variance fault-diagnosis supervised-pca hotelling-t2
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Jun 16, 2025
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