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Abstract Histogram is one of the most important graphical objects in statistical practice. In addition, the histogram provides a consistent estimate of any density function with very few assumptions. Construction of a density histogram with arbitrary mesh is described. Asymptotic theory of optimal histograms is used to provide practical rules for choosing a bin width with real data. Cross‐validation is shown to provide useful estimates of both the bin width and the bin origin. Examples are displayed using data from Sammy Sosa's best year for hitting home runs. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Density Estimation

Histogram of the distance of Sammy Sosa's 66 home runs in 1998 using an oversmoothing rule for the number of bins. The bin width is 32 ft and bin origin is 340 ft.

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Undersmoothed histogram of the Sosa home run data.

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Cross‐validated histogram of the Sosa home run data.

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Cross‐validation scores for thousands of combinations of bin width and bin origin for the blurred Sosa data.

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Statistical and Graphical Methods of Data Analysis > Density Estimation

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