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Tim O'Brien 57b9151881 An implementation of ordinary least squares regression with one independent

variable. The implementation uses running sums and does not require the data
to be stored in memory.  Since I could not conceive of any significantly
different implementation strategies that did not amount to just improving
efficiency or numerical accuracy of what I am submitting, I did not abstract
the interface.

The test cases validate the computations against NIST reference data and
verified computations. The slope, intercept, their standard errors and
r-square estimates are accurate to within 10E-12 against the reference data
set.  MSE and other ANOVA stats are good at least to within 10E-8. -- Phil S.

PR: Issue #20224
Obtained from: Bugzilla
Submitted by: Phil Steitz
Reviewed by: Tim O'Brien


git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140858 13f79535-47bb-0310-9956-ffa450edef68

2003-05-26 02:11:50 +00:00

src

An implementation of ordinary least squares regression with one independent

2003-05-26 02:11:50 +00:00

xdocs

Added mdiggory patch for developer resources

2003-05-22 16:55:22 +00:00

.cvsignore

Mavenization phase one - moving documentation build to maven, will complete by generating build.xml etc later.

2003-05-20 10:24:32 +00:00

build.properties.sample

added new commons math component