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- W1528422915 abstract "The probability density function is useful for summarizing and exploring a set of data. When the parametric form is unknown, then a nonparametric estimator such as the histogram is appropriate. This article illustrates the presentation of data by the histogram compared to the empirical distribution function. The steps required to construct a histogram are described, and data-based methods to accomplish this task are presented. Finally, the more efficient kernel density estimator is introduced and illustrated with real data." @default.
- W1528422915 created "2016-06-24" @default.
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- W1528422915 date "2015-01-01" @default.
- W1528422915 modified "2023-09-26" @default.
- W1528422915 title "Probability Density Estimation" @default.
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- W1528422915 doi "https://doi.org/10.1016/b978-0-08-097086-8.42066-0" @default.
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