NAME

Statistics::Descriptive::PDL::Weighted - A close to drop-in replacement for Statistics::Descriptive::Weighted using PDL as the back-end

VERSION

Version 0.02

SYNOPSIS

use Statistics::Descriptive::PDL::Weighted;

my $stats = Statistics::Descriptive::PDL::Weighted->new;
$stats->add_data([1,2,3,4], [1,3,5,6]);  #  values then weights
my $mean = $stat->mean;
my $var  = $stat->variance;

#  or you can add data using a hash ref
my %data = (1 => 1, 2 => 3, 3 => 5, 4 => 6);
$stats->add_data(\%data);

#  if you want equal weights then you need to supply them yourself
my $data = [1,2,3,4];
$stats->add_data($data, [(1) x scalar @$data]);

DESCRIPTION

This module provides basic functions used in descriptive statistics using weighted values.

METHODS

new

Create a new statistics object. Takes no arguments.

add_data (\%data)
add_data ([1,2,3,4], [0.5,1,0.1,2)

Add data to the stats object. Appends to any existing data.

If a hash reference is passed then the keys are treated as the numeric data values, with the hash values the weights.

Unlike Statistics::Descriptive::PDL, you cannot pass a single flat array since odd things might happen if we convert it to a hash and the values are multidimensional.

Since the PDL::pdl function is used to process the data and weights you should be able to specify anything pdl accepts as valid.

An exception is raised the weights are <= 0, or are not the same size as the data.

sum_wts

Sum of the weights vector.

Statistical methods

Most of the methods should need no explanation here, except to note that the standard_deviation, skewness and kurtosis use the biased methods. This is because one cannot guarantee the data are sample counts. The same applies to the median and percentiles. The median uses a centre of mass calculation, and the percentiles using analogous approach. This is because the weights are not guaranteed to be integers and so there is no sense interpolating.

Use Statistics::Descriptive::PDL::SampleWeighted when your weights are counts and you need the unbiased methods.

The iqr is the inter-quartile range, calculated as the difference of the 75th and 25th percentiles.

geometric_mean
harmonic_mean
max
mean
median
min
mode
sample_range
standard_deviation
sum
variance
count
skewness
kurtosis
percentile (10)
percentile (45)
iqr

Not yet implemented, and possibly won't be.

Any of the trimmed functions, frequency functions and some others.

least_squares_fit
trimmed_mean
quantile
mindex
maxdex

AUTHOR

Shawn Laffan, <shawnlaffan at gmail.com>

BUGS

Please report any bugs or feature requests to https://github.com/shawnlaffan/Statistics-Descriptive-PDL/issues.

ACKNOWLEDGEMENTS

LICENSE AND COPYRIGHT

Copyright 2021 Shawn Laffan.

This program is free software; you can redistribute it and/or modify it under the terms of the the Artistic License (2.0). You may obtain a copy of the full license at:

http://www.perlfoundation.org/artistic_license_2_0

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This license includes the non-exclusive, worldwide, free-of-charge patent license to make, have made, use, offer to sell, sell, import and otherwise transfer the Package with respect to any patent claims licensable by the Copyright Holder that are necessarily infringed by the Package. If you institute patent litigation (including a cross-claim or counterclaim) against any party alleging that the Package constitutes direct or contributory patent infringement, then this Artistic License to you shall terminate on the date that such litigation is filed.

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