statistics-0.10.0.0: A library of statistical types, data, and functions

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Statistics.Sample.Histogram

Contents

Description

Functions for computing histograms of sample data.

Synopsis

# Documentation

Arguments

 :: (Vector v0 Double, Vector v1 Double, Num b, Vector v1 b) => Int Number of bins (must be positive). -> v0 Double Sample data (cannot be empty). -> (v1 Double, v1 b)

O(n) Compute a histogram over a data set.

The result consists of a pair of vectors:

• The lower bound of each interval. * The number of samples within the interval.

Interval (bin) sizes are uniform, and the upper and lower bounds are chosen automatically using the `range` function. To specify these parameters directly, use the `histogram_` function.

# Building blocks

Arguments

 :: (Num b, RealFrac a, Vector v0 a, Vector v1 b) => Int Number of bins. This value must be positive. A zero or negative value will cause an error. -> a Lower bound on interval range. Sample data less than this will cause an error. -> a Upper bound on interval range. This value must not be less than the lower bound. Sample data that falls above the upper bound will cause an error. -> v0 a Sample data. -> v1 b

O(n) Compute a histogram over a data set.

Interval (bin) sizes are uniform, based on the supplied upper and lower bounds.

Arguments

 :: Vector v Double => Int Number of bins (must be positive). -> v Double Sample data (cannot be empty). -> (Double, Double)

O(n) Compute decent defaults for the lower and upper bounds of a histogram, based on the desired number of bins and the range of the sample data.

The upper and lower bounds used are `(lo-d, hi+d)`, where

`d = (maximum sample - minimum sample) / ((bins - 1) * 2)`