Articles, newest first
Missing Data and Irregular Sampling in Time Series
A missing row in a table is a nuisance. A missing interval in a time series changes the meaning of every lag, window and seasonal index computed from it.
Read articleConformal Prediction for Operational Risk Decisions
Conformal prediction helps teams express model uncertainty as calibrated intervals or prediction sets that can be used in operational risk decisions.
Read articleHierarchical Forecasting: Making Forecasts Add Up
Forecast every store separately and the total will not match the forecast you made for the company. Reconciliation is how you make a hierarchy of forecasts c...
Read articleFeature Engineering for Time Series Without Leaking the Future
Turning a time series into a tabular problem unlocks powerful models and introduces a specific failure: features that quietly contain information from the fu...
Read articleWeak Supervision for Better Machine Learning Labels
Weak supervision helps teams scale labeling by combining imperfect rules, heuristics, and external signals instead of hand-labeling every example.
Read articleMultiple Seasonality: MSTL, TBATS, and Fourier Terms
Hourly and daily data rarely has one season. Electricity demand cycles daily, weekly and annually at the same time, and a single seasonal period cannot repre...
Read articleForecasting Baselines That Are Hard to Beat
An RMSE of 4.2 means nothing on its own. Without a baseline you cannot tell whether a model is skilful or merely arithmetic.
Read articleMultilevel Models for Operational Analytics
Multilevel models help analysts estimate group-level performance without overreacting to small samples or ignoring real differences between sites.
Read articleLLM Distillation Is Function Approximation, Not Model Copying
A smaller student model cannot inherit a larger teacher by osmosis. Distillation trains the student to approximate selected aspects of the teacher's behaviou...
Read articleIntermittent Demand Forecasting: Croston's Method and Its Successors
Spare parts and slow-moving stock produce series that are mostly zeros. Standard forecasters quietly fail on them; Croston's method and its successors are bu...
Read article








