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Statistics::Cook - Statistics::Cook - calculate cook distance of Least squares line fit
use Statistics::Cook; my @x = qw/1 2 3 4 5 6/; my @y = qw/1 2.1 3.2 4 7 6/; my $sc = Statistics::Cook->new(x => \@x, y => \@y); ($intercept, $slope) = $sc->coefficients; my @predictedYs = $sc->fitted; my @residuals = $sc->residuals; my @cooks = $sc->cooks_distance;
The Statistics::Cook module is used to calculate cook distance of Least squares line fit to two-dimensional data (y = a + b * x). (This is also called linear regression.) In addition to the slope and y-intercept, the module, the predicted y values and the residuals of the y values. (See the METHODS section for a description of these statistics.)
The module accepts input data in separate x and y arrays. The optional weights are input in a separate array The module is state-oriented and caches its results. you can call the other methods in any order or call a method several times without invoking redundant calculations.
The purpose of I write this module is that I could not find a module to calculate cook distance in CPAN, Therefore I just realized this module with a minimized function consists of least squares and cook distance
x coordinate that used to linear regression and cook distance, is a ArrayRef
y coordinate that used to linear regression and cook distance, is a ArrayRef
weights that used to linear regression and cook distance, is a ArrayRef
slope value of linear model
intercept of y in linear model
the status whether has done linear regress
The module is state-oriented and caches its results. Once you have done regress, you can call the other methods in any order or call a method several times without invoking redundant calculations.
The regression fails if the x values are all the same. In this case, the module issues an error message
Do the least squares line fit, but you don't need to call this method because it is invoked by the other methods as needed, you can call regress() at any time to get the status of the regression for the current data.
Computing some value that used by regress, that you usually need not use it.
Return the slope and y intercept
Return the fitted y values
Return residuals of y values
Calculate cook distance of linear model
default is get N50 of a ArrayRef $self->N([1,2,3,4], 90), you will get N90 $self->N([1,2,3,4], 80), you will get N80
mean value of an array
The variance of a set of samples
The standard deviation of a set of samples
Yan Xueqing <email@example.com>
This software is copyright (c) 2015 by Yan Xueqing.
This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.