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Author*Unverified author*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationMon, 12 Dec 2011 05:38:37 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/12/t1323686420zkrcn6u560mnxzu.htm/, Retrieved Fri, 03 May 2024 11:48:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=153905, Retrieved Fri, 03 May 2024 11:48:35 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [Colombia Coffee] [2008-01-07 10:26:26] [74be16979710d4c4e7c6647856088456]
-  M D    [Blocked Bootstrap Plot - Central Tendency] [Paper] [2011-11-21 11:21:19] [74be16979710d4c4e7c6647856088456]
-    D      [Blocked Bootstrap Plot - Central Tendency] [Paper] [2011-12-12 10:21:34] [aa6b3f8e5b050429abaad141c7204e84]
-    D          [Blocked Bootstrap Plot - Central Tendency] [paper] [2011-12-12 10:38:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
374.92
375.63
376.51
377.75
378.54
378.21
376.65
374.28
373.12
373.1
374.67
375.97
377.03
377.87
378.88
380.42
380.62
379.66
377.48
376.07
374.1
374.47
376.15
377.51
378.43
379.7
380.91
382.2
382.45
382.14
380.6
378.6
376.72
376.98
378.29
380.07
381.36
382.19
382.65
384.65
384.94
384.01
382.15
380.33
378.81
379.06
380.17
381.85
382.88
383.77
384.42
386.36
386.53
386.01
384.45
381.96
380.81
381.09
382.37
383.84
385.42
385.72
385.96
387.18
388.5
387.88
386.38
384.15
383.07
382.98
384.11
385.54
386.92
387.41
388.77
389.46
390.18
389.43
387.74
385.91
384.77
384.38
385.99
387.26




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153905&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153905&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153905&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean380.818958333333381.648452380952382.5899107142861.26413223595181.77095238095228
median380.6382.05382.881.654911141836542.27999999999997

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 380.818958333333 & 381.648452380952 & 382.589910714286 & 1.2641322359518 & 1.77095238095228 \tabularnewline
median & 380.6 & 382.05 & 382.88 & 1.65491114183654 & 2.27999999999997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153905&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]380.818958333333[/C][C]381.648452380952[/C][C]382.589910714286[/C][C]1.2641322359518[/C][C]1.77095238095228[/C][/ROW]
[ROW][C]median[/C][C]380.6[/C][C]382.05[/C][C]382.88[/C][C]1.65491114183654[/C][C]2.27999999999997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153905&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153905&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
mean380.818958333333381.648452380952382.5899107142861.26413223595181.77095238095228
median380.6382.05382.881.654911141836542.27999999999997







95% Confidence Intervals
MeanMedian
Lower Bound381.594901161128381.978895774357
Upper Bound381.845575029348382.301104225643

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 381.594901161128 & 381.978895774357 \tabularnewline
Upper Bound & 381.845575029348 & 382.301104225643 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=153905&T=2

[TABLE]
[ROW][C]95% Confidence Intervals[/C][/ROW]
[ROW][C][/C][C]Mean[/C][C]Median[/C][/ROW]
[ROW][C]Lower Bound[/C][C]381.594901161128[/C][C]381.978895774357[/C][/ROW]
[ROW][C]Upper Bound[/C][C]381.845575029348[/C][C]382.301104225643[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=153905&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=153905&T=2

As an alternative you can also use a QR Code:  

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

95% Confidence Intervals
MeanMedian
Lower Bound381.594901161128381.978895774357
Upper Bound381.845575029348382.301104225643



Parameters (Session):
par1 = 500 ; par2 = 12 ;
Parameters (R input):
par1 = 500 ; 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)
c(s.mean, s.median)
}
(r <- tsboot(x, boot.stat, R=par1, l=12, sim='fixed'))
z <- data.frame(cbind(r$t[,1],r$t[,2]))
colnames(z) <- list('mean','median')
bitmap(file='plot7.png')
b <- boxplot(z,notch=TRUE,ylab='simulated values',main='Bootstrap Simulation - Central Tendency')
grid()
dev.off()
b
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.end(a)
table.save(a,file='mytable.tab')

a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'95% Confidence Intervals',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Mean',1,TRUE)
a<-table.element(a,'Median',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lower Bound',1,TRUE)
a<-table.element(a,b$conf[1,1])
a<-table.element(a,b$conf[1,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Upper Bound',1,TRUE)
a<-table.element(a,b$conf[2,1])
a<-table.element(a,b$conf[2,2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')