# HG changeset patch
# User Shlomi Fish
# Date 1342259325 -10800
# Node ID cdf2baa8c0c15979346db79632b9718fd6d94a83
# Parent a0205d94916c222547590465427d532562dfeb1c
Correct a misspelling and wrapped long lines.
Thanks to Wilhelm for the report.
diff --git a/Statistics-Descriptive/Changes b/Statistics-Descriptive/Changes
--- a/Statistics-Descriptive/Changes
+++ b/Statistics-Descriptive/Changes
@@ -1,5 +1,9 @@
Revision history for Perl extension Statistics::Descriptive.
+ - Correct a misspelling of "weight" in
+ lib/Statistics/Descriptive/Smoother/Weightedexponential.pm
+ - Thanks to Wilhelm for the report.
+
3.0603 May 15, 2012
- Use in_between to compare decimal numbers
- Smoothing tests were failing because of rounding problems
diff --git a/Statistics-Descriptive/lib/Statistics/Descriptive/Smoother/Weightedexponential.pm b/Statistics-Descriptive/lib/Statistics/Descriptive/Smoother/Weightedexponential.pm
--- a/Statistics-Descriptive/lib/Statistics/Descriptive/Smoother/Weightedexponential.pm
+++ b/Statistics-Descriptive/lib/Statistics/Descriptive/Smoother/Weightedexponential.pm
@@ -76,13 +76,14 @@
=head1 NAME
-Statistics::Descriptive::Smoother::Weigthedexponential - Implement weigthed exponential smoothing
+Statistics::Descriptive::Smoother::Weigthedexponential - Implement weighted
+exponential smoothing
=head1 SYNOPSIS
use Statistics::Descriptive::Smoother;
my $smoother = Statistics::Descriptive::Smoother->instantiate({
- method => 'weigthedexponential',
+ method => 'weightedexponential',
coeff => 0.5,
data => [1, 2, 3, 4, 5],
samples => [110, 120, 130, 140, 150],
@@ -91,10 +92,11 @@
=head1 DESCRIPTION
-This module implement the weigthed exponential smoothing algorithm to smooth the trend of a series of statistical data.
+This module implement the weighted exponential smoothing algorithm to smooth
+the trend of a series of statistical data.
-This algorithm can help to control large swings in the unsmoothed data that arise from small samples for
-those data points.
+This algorithm can help to control large swings in the unsmoothed data that
+arise from small samples for those data points.
The algorithm implements the following formula: