https://muon-stat.com/blog Articles on statistics, supply chain optimization, and high-performance computing. en-us https://muon-stat.com/blog/mint-hierarchical-forecast-reconciliation https://muon-stat.com/blog/mint-hierarchical-forecast-reconciliation Wed, 06 May 2026 00:00:00 GMT Forecasts at the SKU-store level rarely add up to your category total. That gap is where money goes missing. We benchmarked four hierarchical reconciliation methods on the full M5 retail dataset (30,490 series, 12 levels, 28-day horizon). Here's what each does and which one to pick. Forecasting Supply Chain Retail Hierarchical Reconciliation https://muon-stat.com/blog/magpie-rs-semantic-search https://muon-stat.com/blog/magpie-rs-semantic-search Tue, 05 May 2026 00:00:00 GMT Vector search libraries are easy to write and hard to ship. Magpie-RS is a Rust vector database designed for production from the start: bounded memory, atomic checkpoints, and durable resume — proven by indexing the entire CRAN. Rust Semantic Search RAG R CRAN https://muon-stat.com/blog/occams-razor-retail-forecasting https://muon-stat.com/blog/occams-razor-retail-forecasting Mon, 30 Mar 2026 00:00:00 GMT A landmark study proves that reducing your forecasting model pool from 19 to 8 models improves accuracy while cutting compute costs by 41%. For large retailers, that's over $1M in annual savings — and 108,000 tonnes less CO₂. Forecasting Supply Chain Retail Cost Optimization https://muon-stat.com/blog/inventory-death-spiral https://muon-stat.com/blog/inventory-death-spiral Sun, 28 Dec 2025 00:00:00 GMT Traditional demand classification systems rely on rigid, decades-old mathematical thresholds that create inventory bloat and revenue loss. Replace them with probabilistic model-based classification. Supply Chain Statistics DuckDB Forecasting