Tests: R, Perl

라벨: Informatics
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•  using chi-square test
• http://www.r-tutor.com/elementary-statistics/goodness-fit/chi-squared-test-independence
• d-separation
• http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=pcalg:dsepTest 

T-test with Perl

#! /usr/bin/perl
use Statistics::TTest;
use Statistics::Basic qw(:all);

my @Data1 = qw(1 2 3 4);
my @Data2 = qw(11 12 13 11 16); 

my $mean = mean( @Data1 ) ;
print $mean;

my $ttest = new Statistics::TTest;
$ttest->set_significance(95);
$ttest->load_data(\@Data1,\@Data2);
#$ttest->output_t_test();

my $t = $ttest->t_statistic;
my $df   = $ttest->df;
my $prob = $ttest->{t_prob};
my $test = $ttest->null_hypothesis();
print "t=$t (df = $df) - p-value = $prob\nNull hypothesis is $test\n";

T-test with R (paired)

args <- commandArgs(TRUE)

data1 <- args[1]   # data file / numeric vector
data2 <- args[2]   # data file / numeric vector

v1 <- read.table( file=data1, header=F ) 
v1 <- as.vector( v1 ) 

v2 <- read.table( file=data2, header=F ) 
v2 <- as.vector( v2 ) 

t.test( v1, v2, paired=F )

One-way ANOVA

Tuekey TEst

require(graphics)

#summary(fm1 = aov(breaks ~ wool + tension, data = warpbreaks))
#TukeyHSD(fm1, "tension", ordered = TRUE)


c2 = read.table(file="c2.txt", header=T)

fm2 = aov( score ~ group, data=c2) 

TukeyHSD(fm2, "group", ordered = TRUE)
plot(TukeyHSD(fm2, "group"))




c4 = read.table(file="c4.txt", header=T)

fm4 = aov( score ~ group, data=c4) 

TukeyHSD(fm4, "group", ordered = TRUE)
plot(TukeyHSD(fm4, "group"))


g1   g2  g3   g4
-------------------
1    2    3   2
2    3    1   2
-------------------

g = read.csv( "g-ratio.csv", sep="\t" )
d = read.csv( "diameter.csv", sep="\t" )

g1 = as.vector( g[,1] )
g1 = g1[ g1 != "" ][-1]

g2 = as.vector( g[,2] )
g2 = g2[ g2 != "" ][-1]

g3 = as.vector( g[,3] )
g3 = g3[ g3 != "" ][-1]

g4 = as.vector( g[,4] )
g4 = g4[ g4 != "" ][-1]

group = c( rep("g1", length(g1)), rep("g2", length(g2)), rep("g3", length(g3)), rep("g4", length(g4)) )
score = as.numeric( c( g1, g2, g3, g4 ) )

t = data.frame( group )
t$score = score

fm = aov( score ~ group, data=t)
 
TukeyHSD(fm, "group", ordered = TRUE)
plot(TukeyHSD(fm, "group"))