Package: binsmooth 0.2.2

binsmooth: Generate PDFs and CDFs from Binned Data

Provides several methods for generating density functions based on binned data. Methods include step function, recursive subdivision, and optimized spline. Data are assumed to be nonnegative, the top bin is assumed to have no upper bound, but the bin widths need be equal. All PDF smoothing methods maintain the areas specified by the binned data. (Equivalently, all CDF smoothing methods interpolate the points specified by the binned data.) In practice, an estimate for the mean of the distribution should be supplied as an optional argument. Doing so greatly improves the reliability of statistics computed from the smoothed density functions. Includes methods for estimating the Gini coefficient, the Theil index, percentiles, and random deviates from a smoothed distribution. Among the three methods, the optimized spline (splinebins) is recommended for most purposes. The percentile and random-draw methods should be regarded as experimental, and these methods only support splinebins.

Authors:David J. Hunter and McKalie Drown

binsmooth_0.2.2.tar.gz
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binsmooth.pdf |binsmooth.html
binsmooth/json (API)
NEWS

# Install 'binsmooth' in R:
install.packages('binsmooth', repos = c('https://djhunter.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 8 scripts 227 downloads 13 exports 4 dependencies

Last updated 5 years agofrom:b51b3ed85b. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 22 2024
R-4.5-winOKOct 22 2024
R-4.5-linuxOKOct 22 2024
R-4.4-winOKOct 22 2024
R-4.4-macOKOct 22 2024
R-4.3-winOKOct 22 2024
R-4.3-macOKOct 22 2024

Exports:ginirsubbinsrsubbinsNotailrsubbinsTailsb_percentilessb_samplesimcountysplinebinsstats_from_distributionstepbinsstepbinsNotailstepbinsTailtheil

Dependencies:assertthatineqpracmatriangle