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package Statistics::TheilSenEstimator; |
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31390
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use 5.006; |
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use strict; |
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use Carp; |
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use warnings FATAL => 'all'; |
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require Exporter; |
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our @ISA = qw/Exporter/; |
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use Statistics::QuickMedian qw/qmedian/; |
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1296
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our @EXPORT_OK = qw/theilsen/; |
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=head1 NAME |
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Statistics::TheilSen - Perl implementation of Theil Sen Estimator |
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=head1 VERSION |
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Version 0.06 |
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=cut |
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our $VERSION = '0.06'; |
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=head1 SYNOPSIS |
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29
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This is a perl implementation of the Theil Sen Estimator, which is a method of |
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linear regression that uses medians. All of the gradients of the lines between |
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all points are calculated, and hte median is the one reported. Sounds trivial. |
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If you have 1000s of points, then you have millions of lines, and sort-based |
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median methods can take ages, so Statistics::TheilSen uses the partition-based |
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Statistics::QuickMedian. |
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36
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# OOP... |
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38
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use Statistics::TheilSenEstimator; |
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40
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my $tse = Statistics::TheilSenEstimator->new(\$y_values, \$x_values); |
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# which is really a shortcut for: |
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my $tse = Statistics::TheilSenEstimator->new(); |
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$tse->addData(\@y_values, \@x_values); # listrefs of numeric scalars |
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45
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my $status_line = $tse->run(); # might tell if you had bad values, etc |
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print "y = ", $tse->m(), "x + ", $tse->c(); # y = mx + c |
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48
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# or procedural... |
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49
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50
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use Statistics::TheilSenEstimator qw/theilsen/; |
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51
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52
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my ($m,$c) = theilsen(\@y_values, \@x_values); |
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53
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54
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=head1 EXPORT/SUBROUTINES |
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56
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=head2 theilsen |
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57
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58
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Accepts two list refs, the lists should be the same length. They represent y and x series |
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59
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which will be the subject of the regression. Returns a list of two |
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60
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61
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use Statistics::TheilSenEstimator qw/theilsen/; |
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62
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63
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my ($m,$b) = theilsen(\$y_values, \$x_values); |
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65
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=cut |
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66
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67
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sub theilsen { |
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68
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0
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0
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1
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my ($y,$x) = @_; |
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69
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0
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my $n = @$y; |
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0
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0
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carp "y and x series are different lengths" |
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71
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unless $n == @$x; |
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72
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# all the gradients! |
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0
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my @M = (); |
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# each item from start to penultimate |
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0
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my ($x1,$x2,$y1,$y2); |
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foreach my $i(0 .. $n-2){ |
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$y1 = $y->[$i]; |
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$x1 = $x->[$i]; |
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0
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next unless defined $y1 && $y1 =~ /\d/ && defined $x1 && $x1 =~ /\d/; |
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0
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0
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80
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# each item from next to last |
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foreach my $j($i+1 .. $n-1){ |
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$y2 = $y->[$j]; |
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next unless defined $y2 && $y2 =~ /\d/; |
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# short cut for zero (even if dx is zero ;-) |
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0
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if($y2 == $y1){ |
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push @M, 0; |
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0
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next; |
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} |
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$x2 = $x->[$j]; |
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next unless defined $x2 && $x2 =~ /\d/; |
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# skip any divisions by zero! (don't add to the list, if it's infinite then it's both pos and neg anyway!) |
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0
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next if $x2 == $x1; |
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# otherwise, calculate the gradient and push it... |
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push @M, ($y2-$y1)/($x2-$x1); |
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} |
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} |
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# now we have @M, so what's the median? |
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0
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my $m = qmedian(\@M); # warning... this modifies the order of M! |
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100
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# y-intercept b to be the median of the values yi - mxi |
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0
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my @C = (); |
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foreach my $i(0 .. $n-1){ |
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$y1 = $y->[$i]; |
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$x1 = $x->[$i]; |
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next unless defined $y1 && $y1 =~ /\d/ && defined $x1 && $x1 =~ /\d/; |
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106
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push @C, $y1 - $m * $x1; |
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} |
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# now we have @C, so what's the median? |
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my $c = qmedian(\@C); # warning... this modifies the order of C! |
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return ($m,$c); |
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} |
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113
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=head1 METHODS |
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115
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=head2 new |
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116
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117
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use Statistics::TheilSenEstimator; |
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118
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my $tse = Statistics::TheilSenEstimator->new(); |
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119
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#or |
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120
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my $tse = Statistics::TheilSenEstimator->new(\@y_values, \@x_values); |
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122
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returns a new Statistics::TheilSenEstimator estimator object with the optional data added. |
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124
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=cut |
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125
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126
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sub new { |
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1
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my $p = shift; |
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128
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my $c = ref $p || $p; |
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my $o = { |
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Y=>[], # we store y series here |
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X=>[], # and x here |
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runSinceAddData=>0, # check whether a run is needed |
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m=>'', |
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c=>'', |
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}; |
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bless $o, $c; |
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if(@_==2){ |
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0
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138
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0
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$o->addData(@_); |
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139
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} |
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140
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elsif(@_){ |
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0
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croak "wrong number of args to Statistics::TheilSen->new, should be 0 or 2."; |
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142
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} |
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143
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0
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return $o; |
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144
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} |
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145
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146
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=head2 addData |
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147
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148
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$tse->addData(\@y_values, \@x_values); |
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149
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150
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Adds data to the y and x series. Data series should be the same length. |
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151
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152
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=cut |
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153
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154
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sub addData { |
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155
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1
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my $o = shift; |
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156
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0
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0
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croak "wrong number of args to Statistics::TheilSen->new, should be 0 or 2." |
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157
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unless @_ == 2; |
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158
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0
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my ($Y,$X) = @_; |
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159
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0
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croak "Y and X are not equal lengths" |
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160
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unless @$Y == @$X; |
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161
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0
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push @{$o->{Y}}, @$Y; |
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0
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162
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0
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push @{$o->{X}}, @$X; |
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0
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163
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0
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$o->{runSinceAddData} = 0; |
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164
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} |
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165
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166
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=head2 run |
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167
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168
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my $status_line = $tse->run(); |
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169
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170
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Runs the estimator on the data currently in the object. Returns any messages |
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171
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about whether errors or weird things were found in the data. Sets m and c in |
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172
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the object |
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174
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=cut |
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175
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176
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sub run { |
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0
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0
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1
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my $o = shift; |
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178
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# fatal: |
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179
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0
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my $n = @{$o->{Y}}; |
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0
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180
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0
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return "Y and X are different lengths (fatal)" |
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181
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0
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0
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if $n != @{$o->{X}}; |
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182
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183
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# "warnings" about data |
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184
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0
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my $message; |
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185
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# count up how many of x2-x1 == 0... |
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186
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0
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my %X = (); |
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187
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0
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my $divZeroCounts = 0; |
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188
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0
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foreach (@{$o->{X}}){ |
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0
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189
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0
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0
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if(exists $X{$_}){ |
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190
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0
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$X{$_}++; |
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191
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0
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$divZeroCounts += $X{$_}; |
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192
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} |
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193
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else { |
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0
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$X{$_} = 0; |
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} |
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} |
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0
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undef %X; |
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0
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0
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if($divZeroCounts){ |
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0
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$message .= "Denominator (x2-x1) is zero in $divZeroCounts cases. "; |
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} |
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# check missing values, etc. |
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0
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my ($y,$x); |
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my $missing = 0; |
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0
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foreach my $i(0..$n-1){ |
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($y,$x) = ($o->{Y}->[$i],$o->{X}->[$i]); |
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0
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0
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0
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if(! defined $y || $y !~ /\d/ || $y != $y+0 |
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0
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0
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0
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0
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|| ! defined $x || $x !~ /\d/ || $x != $x+0){ |
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# looks like x or y is NaN |
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0
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$missing ++; |
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} |
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} |
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0
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0
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if($missing){ |
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0
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$message .= "Missing values on $missing rows. "; |
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} |
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# end of checks |
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0
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($o->{m}, $o->{c}) |
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= theilsen( |
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$o->{Y}, |
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$o->{X}, |
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); |
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0
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$o->{runSinceAddData} = 1; |
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0
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return $message; |
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} |
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225
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=head2 m |
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227
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my $gradient = $tse->m(); |
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Returns "m", the gradient of the model generated by run(). If run() was not |
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called since addData(), then run() will be called here! |
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232
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=cut |
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234
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sub m { |
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235
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0
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0
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1
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my $o = shift; |
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236
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0
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0
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|
$o->{runSinceAddData} || $o->run(); |
|
237
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0
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return $o->{m}; |
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238
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} |
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239
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240
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=head2 c |
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241
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242
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|
my $intersect = $tse->c(); |
|
243
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244
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|
Returns "c", the intersect of the model generated by run(). If run() was not |
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245
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|
called since addData(), then run() will be called here! |
|
246
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247
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=cut |
|
248
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249
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sub c { |
|
250
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0
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0
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1
|
|
my $o = shift; |
|
251
|
0
|
0
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|
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|
|
$o->{runSinceAddData} || $o->run(); |
|
252
|
0
|
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|
|
return $o->{c}; |
|
253
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|
} |
|
254
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255
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|
=head1 AUTHOR |
|
256
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|
257
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|
|
Jimi Wills, C<< >> |
|
258
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259
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|
=head1 BUGS |
|
260
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|
261
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|
Please report any bugs or feature requests to C, or through |
|
262
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|
|
the web interface at L. I will be notified, and then you'll |
|
263
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|
automatically be notified of progress on your bug as I make changes. |
|
264
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|
265
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|
266
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|
267
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|
268
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|
=head1 SUPPORT |
|
269
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|
270
|
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|
|
You can find documentation for this module with the perldoc command. |
|
271
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|
272
|
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|
|
|
|
perldoc Statistics::TheilSenEstimator |
|
273
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|
274
|
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|
275
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|
|
You can also look for information at: |
|
276
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|
277
|
|
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|
|
|
|
=over 4 |
|
278
|
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|
279
|
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|
|
=item * RT: CPAN's request tracker (report bugs here) |
|
280
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|
281
|
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|
L |
|
282
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|
283
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|
|
=item * AnnoCPAN: Annotated CPAN documentation |
|
284
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|
285
|
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|
L |
|
286
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|
287
|
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|
|
=item * CPAN Ratings |
|
288
|
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|
289
|
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|
|
L |
|
290
|
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|
291
|
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|
|
=item * Search CPAN |
|
292
|
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|
293
|
|
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|
|
L |
|
294
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|
295
|
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|
|
=back |
|
296
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|
297
|
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|
298
|
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|
|
|
|
=head1 ACKNOWLEDGEMENTS |
|
299
|
|
|
|
|
|
|
|
|
300
|
|
|
|
|
|
|
http://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator |
|
301
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|
302
|
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|
|
=head1 LICENSE AND COPYRIGHT |
|
303
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|
304
|
|
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|
|
Copyright 2013 Jimi Wills. |
|
305
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|
306
|
|
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|
|
|
|
This program is free software; you can redistribute it and/or modify it |
|
307
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|
|
under the terms of the the Artistic License (2.0). You may obtain a |
|
308
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|
|
copy of the full license at: |
|
309
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|
310
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|
L |
|
311
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|
312
|
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|
|
Any use, modification, and distribution of the Standard or Modified |
|
313
|
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|
|
|
|
Versions is governed by this Artistic License. By using, modifying or |
|
314
|
|
|
|
|
|
|
distributing the Package, you accept this license. Do not use, modify, |
|
315
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|
|
or distribute the Package, if you do not accept this license. |
|
316
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|
317
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|
|
If your Modified Version has been derived from a Modified Version made |
|
318
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|
|
by someone other than you, you are nevertheless required to ensure that |
|
319
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|
|
your Modified Version complies with the requirements of this license. |
|
320
|
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|
321
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|
|
This license does not grant you the right to use any trademark, service |
|
322
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|
|
mark, tradename, or logo of the Copyright Holder. |
|
323
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|
324
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|
|
This license includes the non-exclusive, worldwide, free-of-charge |
|
325
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|
|
patent license to make, have made, use, offer to sell, sell, import and |
|
326
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|
|
otherwise transfer the Package with respect to any patent claims |
|
327
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|
|
licensable by the Copyright Holder that are necessarily infringed by the |
|
328
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|
|
Package. If you institute patent litigation (including a cross-claim or |
|
329
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|
|
|
counterclaim) against any party alleging that the Package constitutes |
|
330
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|
|
direct or contributory patent infringement, then this Artistic License |
|
331
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|
|
to you shall terminate on the date that such litigation is filed. |
|
332
|
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|
333
|
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|
|
Disclaimer of Warranty: THE PACKAGE IS PROVIDED BY THE COPYRIGHT HOLDER |
|
334
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|
|
AND CONTRIBUTORS "AS IS' AND WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES. |
|
335
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|
|
THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR |
|
336
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|
|
PURPOSE, OR NON-INFRINGEMENT ARE DISCLAIMED TO THE EXTENT PERMITTED BY |
|
337
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|
|
YOUR LOCAL LAW. UNLESS REQUIRED BY LAW, NO COPYRIGHT HOLDER OR |
|
338
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|
|
CONTRIBUTOR WILL BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, OR |
|
339
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|
|
CONSEQUENTIAL DAMAGES ARISING IN ANY WAY OUT OF THE USE OF THE PACKAGE, |
|
340
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|
|
EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
|
341
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|
342
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|
343
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|
=cut |
|
344
|
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|
345
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|
|
1; # End of Statistics::TheilSen |