NAME
Math::LOESS - Perl wrapper of the Locally-Weighted Regression package originally written by Cleveland, et al.
VERSION
version 0.0000_03
SYNOPSIS
use Math::LOESS;
my $loess = Math::LOESS->new(x => $x, y => $y);
$loess->fit();
my $fitted_values = $loess->outputs->fitted_values;
print $loess->summary();
my $prediction = $loess->predict($new_data, 1);
my $confidence_intervals = $prediction->confidence(0.05);
print $confidence_internals->{fit};
print $confidence_internals->{upper};
print $confidence_internals->{lower};
CONSTRUCTION
new(Piddle1D :$x, Piddle1D :$y, Piddle1D :$weights=undef,
Num :$span=0.75, Str :$family='gaussian')
Arguments:
$x
A PDL piddle for x data.
In case of multiple predictors,
$x
is a glued piddle containing all predictors' data. It's possible to have at most 8 predictors.$y
A PDL piddle for y data.
$weights
Optional weights.
$span
POD INCLUDE ERROR: Can't load template 'span' from 'Math::LOESS::Model'.
When provided as a construction parameter, it is like a shortcut for,
$loess->model->span($span);
$family
POD INCLUDE ERROR: Can't load template 'family' from 'Math::LOESS::Model'.
When provided as a construction parameter, it is like a shortcut for,
$loess->model->family($family);
NAME
Math::LOESS - Perl wrapper of the Locally-Weighted Regression package originally written by Cleveland, et al.
ATTRIBUTES
model
Get an Math::LOESS::Model object.
outputs
Get an Math::LOESS::Outputs object.
x
Get input x data as a piddle.
y
Get input y data as a piddle.
weights
Get input weights data as a piddle.
activated
Returns a true value if the object's fit()
method has been called.
METHODS
fit
fit()
predict
predict(Piddle1D $newdata, Bool $stderr=false)
Returns a Math::LOESS::Prediction object.
summary
summary()
Returns a summary string.
SEE ALSO
https://en.wikipedia.org/wiki/Local_regression
AUTHOR
Stephan Loyd <sloyd@cpan.org>
COPYRIGHT AND LICENSE
This software is copyright (c) 2019 by Stephan Loyd.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.