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 evelinag.com
Christmas Carol and other eigenvectors
| | sebastianraschka.com
Predictive modeling, supervised machine learning, and pattern classification
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| | I'm Sebastian: a machine learning & AI researcher, programmer, and author. As Staff Research Engineer Lightning AI, I focus on the intersection of AI research, software development, and large language models (LLMs).
| | dm13450.github.io
Currency Hedging and Principal Component Analysis | Dean Markwick
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| | Principal component analysis (PCA) reduces a dataset to its main components. When we apply it to a dataset of different currencies it helps us understand how each currency drives the overall portfolio and what currency might be a common factor.
| | alexhwilliams.info
Everything you did and didn't know about PCA ยท Its Neuronal
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| | [AI summary] A technical blog post explaining the mathematical foundations of Principal Component Analysis (PCA), its various generalizations like Sparse and Non-negative Matrix Factorization, and practical considerations for choosing components and handling missing data.
| | fharrell.com
Incorporating Historical Control Data Into an RCT - Statistical Thinking
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| Historical data (HD) are being used increasingly in Bayesian analyses when it is difficult to randomize enough patients to study effectiveness of a treatment. Such analyses summarize observational studies' posterior effectiveness distribution (for two-arm HD) or standard-of-care outcome distribution (for one-arm HD) then turn that into a prior distribution for an RCT. The prior distribution is then flattened somewhat to discount the HD. Since Bayesian modeling makes it easy to fit multiple models at once...