NAME
Statistics::Descriptive::PDL::Weighted - A close to drop-in replacement for Statistics::Descriptive::Weighted using PDL as the back-end
VERSION
Version 0.04
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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