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20 lines
779 B
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20 lines
779 B
Plaintext
This Haskell library provides a number of common functions and types
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useful in statistics. Our focus is on high performance, numerical
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robustness, and use of good algorithms. Where possible, we provide
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references to the statistical literature.
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The library's facilities can be divided into three broad categories:
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Working with widely used discrete and continuous probability
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distributions. (There are dozens of exotic distributions in use; we
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focus on the most common.)
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Computing with sample data: quantile estimation, kernel density
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estimation, bootstrap methods, and autocorrelation analysis.
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Random variate generation under several different distributions.
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Common statistical tests for significant differences between samples.
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WWW: http://darcs.serpentine.com/statistics
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