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Author*The author of this computation has been verified*
R Software Modulerwasp_bootstrapplot.wasp
Title produced by softwareBlocked Bootstrap Plot - Central Tendency
Date of computationThu, 25 Nov 2010 16:48:57 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/25/t1290703642xvo8j1tod1arcnq.htm/, Retrieved Thu, 28 Mar 2024 21:56:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=101213, Retrieved Thu, 28 Mar 2024 21:56:16 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
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] [] [2010-11-25 16:48:57] [288f03f47c5783dcaccb816dacc66894] [Current]
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Dataseries X:
61.712
62.084
61.406
60.724
58.904
58.722
59.704
60.674
59.813
60.568
61.401
61.427
61.080
61.999
63.888
66.284
67.309
66.685
65.404
65.045
63.867
64.156
62.224
63.193
64.256
66.153
68.072
68.245
68.741
67.795
67.315
67.245
66.448
69.112
71.787
74.366
76.337
77.618
77.090
76.925
78.384
80.462
82.765
85.033
83.608
81.813
81.467
80.708
80.631
79.133
77.396
75.491
74.267
72.882
71.286
70.737
67.425
67.530
67.157
67.215
66.268
66.053
54.905
54.459
51.159
44.725
40.184
44.094
46.904
47.141
45.052
42.758
41.388
41.154
40.019
39.928
38.598
36.584
32.566
30.140
27.713
25.380
23.823
21.376
18.696
16.304
14.203
11.807
7.551
4.215
3.346
3.010
2.849
2.485
1.744
1.221
803
553
314
204
125
55
53
27
10
6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101213&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101213&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101213&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132







Estimation Results of Blocked Bootstrap
statisticQ1EstimateQ3S.D.IQR
mean59.799285377358569.726132075471777.386165094339612.980109663875617.5868797169811
median60.190562.15466.11557.426451128554315.92500000000001

\begin{tabular}{lllllllll}
\hline
Estimation Results of Blocked Bootstrap \tabularnewline
statistic & Q1 & Estimate & Q3 & S.D. & IQR \tabularnewline
mean & 59.7992853773585 & 69.7261320754717 & 77.3861650943396 & 12.9801096638756 & 17.5868797169811 \tabularnewline
median & 60.1905 & 62.154 & 66.1155 & 7.42645112855431 & 5.92500000000001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101213&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]59.7992853773585[/C][C]69.7261320754717[/C][C]77.3861650943396[/C][C]12.9801096638756[/C][C]17.5868797169811[/C][/ROW]
[ROW][C]median[/C][C]60.1905[/C][C]62.154[/C][C]66.1155[/C][C]7.42645112855431[/C][C]5.92500000000001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101213&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101213&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
mean59.799285377358569.726132075471777.386165094339612.980109663875617.5868797169811
median60.190562.15466.11557.426451128554315.92500000000001







95% Confidence Intervals
MeanMedian
Lower Bound67.02686635158961.7344577457216
Upper Bound69.51331289369462.5735422542784

\begin{tabular}{lllllllll}
\hline
95% Confidence Intervals \tabularnewline
 & Mean & Median \tabularnewline
Lower Bound & 67.026866351589 & 61.7344577457216 \tabularnewline
Upper Bound & 69.513312893694 & 62.5735422542784 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=101213&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]67.026866351589[/C][C]61.7344577457216[/C][/ROW]
[ROW][C]Upper Bound[/C][C]69.513312893694[/C][C]62.5735422542784[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=101213&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=101213&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 Bound67.02686635158961.7344577457216
Upper Bound69.51331289369462.5735422542784



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')