2008/07/30 by David W. Hogg, Hogg, David W.
Chemistry · Computer Science · Mathematics · Physics and Astronomy · #Advanced Clustering Algorithms Research #Astrophysics (astro-ph) #Data Analysis #FOS: Physical sciences #Spectroscopy and Chemometric Analyses #Statistical Methods and Applications #Statistics and Probability (physics.data-an) #astro-ph #physics.data-an
paper · pdf · doi:10.48550/arxiv.0807.4820
not submitted anywhere but here
arxiv created 2008/07/30 · openalex publication_date 2008/07/30 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Data points are placed in bins when a histogram is created, but there is always a decision to be made about the number or width of the bins. This decision is often made arbitrarily or subjectively, but it need not be. A jackknife or leave-one-out cross-validation likelihood is defined and employed as a scalar objective function for optimization of the locations and widths of the bins. The objective is justified as being related to the histogram's usefulness for predicting future data. The method works for data or histograms of any dimensionality.