Category Archives: statistical series

Stream flow and P-splines: Using built-in estimates for smoothing

Mother Brook in Dedham Massachusetts was the first man-made canal in the United States. Dug in 1639, it connects the Charles River at Dedham, to the Neponset River in the Hyde Park section of Boston. It was originally an important … Continue reading

Posted in American Statistical Association, citizen data, citizen science, Clausius-Clapeyron equation, Commonwealth of Massachusetts, cross-validation, data science, dependent data, descriptive statistics, dynamic linear models, empirical likelihood, environment, flooding, floods, Grant Foster, hydrology, likelihood-free, meteorological models, model-free forecasting, non-mechanistic modeling, non-parametric, non-parametric model, non-parametric statistics, numerical algorithms, precipitation, quantitative ecology, statistical dependence, statistical series, stream flow, Tamino, the bootstrap, time series, water vapor | Leave a comment

A look at an electricity consumption series using SNCDs for clustering

(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading

Posted in American Statistical Association, consumption, data streams, decentralized electric power generation, dendrogram, divergence measures, efficiency, electricity, electricity markets, energy efficiency, energy utilities, ensembles, evidence, forecasting, grid defection, hierarchical clustering, hydrology, ILSR, information theoretic statistics, local self reliance, Massachusetts, microgrids, NCD, normalized compression divergence, numerical software, open data, prediction, rate of return regulation, Sankey diagram, SNCD, statistical dependence, statistical series, statistics, sustainability, symmetric normalized compression divergence, time series | Leave a comment