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introduction to Bayesian methods for the social sciences (18-22 Aug, Università della Svizzera italiana, Lugano)
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Tidyverse with GitHub Copilot for Healthcare Analytics – Part 1
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Understanding Basis Spline (B-spline) By Working Through Cox-deBoor Algorithm
I finally understood B-splines by working through the Cox-deBoor algorithm step-by-step, discovering they’re just weighted combinations of basis functions that make non-linear regression linear. What surprised me is going through Bayesian statistics…
Correlation vs Causation: Understanding the Difference
Introduction “Correlation is not causation” – it’s a refrain we hear often, yet the distinction between these concepts is deceptively easy to overlook. Correlation refers to a statistical association: when one variable…
Repost: The Modern R Stack for Production AI
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Targeted Advertising vs Personalization: What’s the Difference and Why It Matters
When we think about digital advertising today, targeting and personalization are often spoken about and it makes sense because these two strategies have formed the way brands connect with audiences online but…
Beyond ARMA-GARCH: leveraging model-agnostic Machine Learning and conformal prediction for nonparametric probabilistic stock forecasting (ML-ARCH)
Probabilistic (not point forecasting) stock forecasting is notably useful for testing trading strategies or risk capital valuation. Because stock prices exhibit a latent stochastic volatility, this type of forecasting methods relies on…
Containerizing Shiny Apps with {shiny2docker}: A Step-by-Step Guide
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Benchmarks vs. Baselines: When ‘Above Average’ Isn’t Good Enough
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