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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationTue, 15 Nov 2011 06:48:53 -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/Nov/15/t1321357746quh625mlyw2oc6l.htm/, Retrieved Fri, 29 Mar 2024 11:14:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=142771, Retrieved Fri, 29 Mar 2024 11:14:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
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] [] [2011-11-14 13:57:35] [e32f7fcc4522d286f7101d32ccf9e2fd]
-    D        [Blocked Bootstrap Plot - Central Tendency] [mini tutorial] [2011-11-15 11:48:53] [05d3841c0e91f0207133db830e88168b] [Current]
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Dataseries X:
1.324
1.310
1.310
1.310
1.310
1.338
1.338
1.338
1.358
1.358
1.358
1.358
1.351
1.351
1.351
1.351
1.351
1.372
1.372
1.372
1.372
1.386
1.386
1.386
1.386
1.414
1.414
1.414
1.414
1.443
1.443
1.443
1.443
1.443
1.443
1.443
1.443
1.443
1.448
1.448
1.448
1.463
1.463
1.463
1.456
1.456
1.456
1.456
1.456
1.440
1.440
1.440
1.440
1.429
1.429
1.429
1.419
1.419
1.435
1.435
1.435
1.435
1.435
1.465
1.465
1.438
1.438
1.394
1.394
1.394
1.423
1.423
1.423
1.460
1.460
1.460
1.460
1.472
1.472
1.472
1.451
1.451
1.451
1.400
1.421
1.421
1.421
1.421
1.421
1.421
1.450
1.450
1.450
1.450
1.463
1.463
1.463
1.463
1.463
1.463
1.463
1.463
1.459
1.459
1.459
1.459
1.480
1.480
1.480
1.480
1.498
1.498
1.498
1.498
1.498
1.498
1.498
1.498
1.498
1.511
1.511




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=142771&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=142771&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142771&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
mean1.421962809917361.430322314049591.436369834710740.01148587853975620.0144070247933885
median1.4351.4431.4480.01183066546271090.0129999999999999

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 1.42196280991736 & 1.43032231404959 & 1.43636983471074 & 0.0114858785397562 & 0.0144070247933885 \tabularnewline
median & 1.435 & 1.443 & 1.448 & 0.0118306654627109 & 0.0129999999999999 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142771&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]1.42196280991736[/C][C]1.43032231404959[/C][C]1.43636983471074[/C][C]0.0114858785397562[/C][C]0.0144070247933885[/C][/ROW]
[ROW][C]median[/C][C]1.435[/C][C]1.443[/C][C]1.448[/C][C]0.0118306654627109[/C][C]0.0129999999999999[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142771&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142771&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
mean1.421962809917361.430322314049591.436369834710740.01148587853975620.0144070247933885
median1.4351.4431.4480.01183066546271090.0129999999999999







95% Confidence Intervals
MeanMedian
Lower Bound1.428148942894331.44208142327484
Upper Bound1.430189900080871.44391857672516

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 1.42814894289433 & 1.44208142327484 \tabularnewline
Upper Bound & 1.43018990008087 & 1.44391857672516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=142771&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]1.42814894289433[/C][C]1.44208142327484[/C][/ROW]
[ROW][C]Upper Bound[/C][C]1.43018990008087[/C][C]1.44391857672516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=142771&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=142771&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 Bound1.428148942894331.44208142327484
Upper Bound1.430189900080871.44391857672516



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')