Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 15 Dec 2009 15:13:46 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/15/t1260915335qoo2smkpzm4xi1x.htm/, Retrieved Wed, 08 May 2024 13:30:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68190, Retrieved Wed, 08 May 2024 13:30:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W32
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [Bootstrap Plot Ma...] [2009-12-15 21:42:58] [ccfbf9d81e657cac862fa2c4f4dea5e7]
-   P   [Bootstrap Plot - Central Tendency] [Bootstrap Plot Ma...] [2009-12-15 21:49:13] [ccfbf9d81e657cac862fa2c4f4dea5e7]
- RMPD      [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2009-12-15 22:13:46] [8d07284ecb3aa8be600f3c4907b7b611] [Current]
-   PD        [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2009-12-15 22:18:05] [ccfbf9d81e657cac862fa2c4f4dea5e7]
-   P           [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2009-12-15 22:21:42] [ccfbf9d81e657cac862fa2c4f4dea5e7]
Feedback Forum

Post a new message
Dataseries X:
100,34
115,78
114,6
114,2
115,88
125,22
161,71
165,01
135,78
153,67
125,52
135,29
103,05
120,79
120,17
119,62
121,17
129,86
167,8
167,14
140,55
158,44
131,07
140,55
106,15
123,65
122,8
122,25
123,88
132,96
171,82
173,69
149,5
164,44
133,37
143,77
69,49
84,5
82,3
78,8
79,47
88,93
138,13
139,69
114,43
128,65
95,92
98,22
56,65
69,6
66,91
63,76
64
35,24
45,3
43,02
43,08
43,17
46,38
70,85
72,81
59,51
67,54
56,51
53,82
112,55
127,65
126,51
126,08
127,34




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68190&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68190&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68190&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean102.775107142857108.975714285714117.93182142857110.999168327728615.1567142857143
median114.38625119.895123.027514.00979402898898.64125000000001
midrange102.0225104.465108.37756.619322981596676.35499999999999

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 102.775107142857 & 108.975714285714 & 117.931821428571 & 10.9991683277286 & 15.1567142857143 \tabularnewline
median & 114.38625 & 119.895 & 123.0275 & 14.0097940289889 & 8.64125000000001 \tabularnewline
midrange & 102.0225 & 104.465 & 108.3775 & 6.61932298159667 & 6.35499999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68190&T=1

[TABLE]
[ROW][C]Estimation Results of Blocked Bootstrap[/C][/ROW]
[ROW][C]statistic[/C][C]Q1[/C][C]Estimate[/C][C]Q3[/C][C]S.D.[/C][C]IQR[/C][/ROW]
[ROW][C]mean[/C][C]102.775107142857[/C][C]108.975714285714[/C][C]117.931821428571[/C][C]10.9991683277286[/C][C]15.1567142857143[/C][/ROW]
[ROW][C]median[/C][C]114.38625[/C][C]119.895[/C][C]123.0275[/C][C]14.0097940289889[/C][C]8.64125000000001[/C][/ROW]
[ROW][C]midrange[/C][C]102.0225[/C][C]104.465[/C][C]108.3775[/C][C]6.61932298159667[/C][C]6.35499999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68190&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68190&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean102.775107142857108.975714285714117.93182142857110.999168327728615.1567142857143
median114.38625119.895123.027514.00979402898898.64125000000001
midrange102.0225104.465108.37756.619322981596676.35499999999999



Parameters (Session):
par1 = 50 ; par2 = 12 ;
Parameters (R input):
par1 = 50 ; par2 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1 < 10) par1 = 10
if (par1 > 5000) par1 = 5000
if (par2 < 3) par2 = 3
if (par2 > length(x)) par2 = length(x)
library(lattice)
library(boot)
boot.stat <- function(s)
{
s.mean <- mean(s)
s.median <- median(s)
s.midrange <- (max(s) + min(s)) / 2
c(s.mean, s.median, s.midrange)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
bitmap(file='plot1.png')
plot(r$t[,1],type='p',ylab='simulated values',main='Simulation of Mean')
grid()
dev.off()
bitmap(file='plot2.png')
plot(r$t[,2],type='p',ylab='simulated values',main='Simulation of Median')
grid()
dev.off()
bitmap(file='plot3.png')
plot(r$t[,3],type='p',ylab='simulated values',main='Simulation of Midrange')
grid()
dev.off()
bitmap(file='plot4.png')
densityplot(~r$t[,1],col='black',main='Density Plot',xlab='mean')
dev.off()
bitmap(file='plot5.png')
densityplot(~r$t[,2],col='black',main='Density Plot',xlab='median')
dev.off()
bitmap(file='plot6.png')
densityplot(~r$t[,3],col='black',main='Density Plot',xlab='midrange')
dev.off()
z <- data.frame(cbind(r$t[,1],r$t[,2],r$t[,3]))
colnames(z) <- list('mean','median','midrange')
bitmap(file='plot7.png')
boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimation Results of Blocked Bootstrap',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'statistic',header=TRUE)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,'Estimate',header=TRUE)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'IQR',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
q1 <- quantile(r$t[,1],0.25)[[1]]
q3 <- quantile(r$t[,1],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[1])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,1])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
q1 <- quantile(r$t[,2],0.25)[[1]]
q3 <- quantile(r$t[,2],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[2])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,2])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'midrange',header=TRUE)
q1 <- quantile(r$t[,3],0.25)[[1]]
q3 <- quantile(r$t[,3],0.75)[[1]]
a<-table.element(a,q1)
a<-table.element(a,r$t0[3])
a<-table.element(a,q3)
a<-table.element(a,sqrt(var(r$t[,3])))
a<-table.element(a,q3-q1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')