Pavel Logačev
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Technical Case Studies

Detailed explorations of data science methods and applications

In-depth data science case studies demonstrating Bayesian methods, time series analysis, changepoint detection, and LLM applications.

Detailed case studies with full code and methodology. Each project demonstrates practical applications of Bayesian statistics, time series analysis, and machine learning techniques.

A Hidden-Markov Model of Stockout Detection
Bayesian HMM for detecting unobserved inventory outages

Price Distribution Elicitation from an LLM
Using GPT-4o to estimate plausible price ranges for products

Bayesian Changepoint Detection on Price Histograms
Detecting structural changes in pricing regimes

Local-level state-space model with sparse state innovations for elasticity analysis
Bayesian decomposition of sales dynamics with NumPyro
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