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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationSun, 13 Dec 2009 07:39:24 -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/13/t1260715290ucbtdisko1vuja5.htm/, Retrieved Sun, 28 Apr 2024 17:54:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67308, Retrieved Sun, 28 Apr 2024 17:54:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [Paper Bivariate E...] [2009-12-13 14:39:24] [5ed0eef5d4509bbfdac0ae6d87f3b4bf] [Current]
- RMPD    [(Partial) Autocorrelation Function] [Paper-ACF-Yt] [2009-12-15 17:52:27] [f15cfb7053d35072d573abca87df96a0]
- RMPD    [(Partial) Autocorrelation Function] [Paper-ACF2-Yt] [2009-12-15 17:59:21] [f15cfb7053d35072d573abca87df96a0]
-   P       [(Partial) Autocorrelation Function] [Paper-ACF3-Yt] [2009-12-15 18:09:38] [f15cfb7053d35072d573abca87df96a0]
- R  D        [(Partial) Autocorrelation Function] [Paper-ACF2-Xt] [2009-12-16 20:41:59] [143cbdcaf7333bdd9926a1dde50d1082]
- R  D      [(Partial) Autocorrelation Function] [Paper-ACF1-Xt] [2009-12-16 20:22:54] [143cbdcaf7333bdd9926a1dde50d1082]
- RMPD    [Variance Reduction Matrix] [Paper-VRM-Yt] [2009-12-15 18:02:12] [f15cfb7053d35072d573abca87df96a0]
- R  D      [Variance Reduction Matrix] [Paper-VRM-Xt] [2009-12-16 20:29:46] [143cbdcaf7333bdd9926a1dde50d1082]
- RMPD    [Spectral Analysis] [Paper-Spectrum1-Yt] [2009-12-15 18:16:48] [f15cfb7053d35072d573abca87df96a0]
-   P       [Spectral Analysis] [Paper-Spectrum2-Yt] [2009-12-15 18:21:23] [f15cfb7053d35072d573abca87df96a0]
- R  D      [Spectral Analysis] [Paper-Spectrum1-Xt] [2009-12-16 20:46:25] [143cbdcaf7333bdd9926a1dde50d1082]
- R PD      [Spectral Analysis] [Paper-Spectrum2-Xt] [2009-12-16 20:52:27] [143cbdcaf7333bdd9926a1dde50d1082]
- RMPD    [Standard Deviation-Mean Plot] [Paper-SMP-Yt] [2009-12-15 18:23:34] [f15cfb7053d35072d573abca87df96a0]
- R PD      [Standard Deviation-Mean Plot] [Paper-SMP-Xt] [2009-12-16 21:01:03] [143cbdcaf7333bdd9926a1dde50d1082]
- RMPD    [ARIMA Backward Selection] [Paper-ARIMAbackw-Yt] [2009-12-15 18:35:49] [f15cfb7053d35072d573abca87df96a0]
- R PD      [ARIMA Backward Selection] [Paper-ARIMAbackw-Xt] [2009-12-18 10:42:00] [143cbdcaf7333bdd9926a1dde50d1082]
- RMPD    [ARIMA Forecasting] [Paper-ARIMAforeca...] [2009-12-15 18:44:14] [f15cfb7053d35072d573abca87df96a0]
- R PD      [ARIMA Forecasting] [Paper-ARIMAforeca...] [2009-12-18 10:49:22] [143cbdcaf7333bdd9926a1dde50d1082]
- R PD        [ARIMA Forecasting] [Forecasting] [2010-12-29 19:27:15] [17d39bb3ec485d4ce196f61215d11ba1]
-               [ARIMA Forecasting] [forecast] [2010-12-29 22:40:36] [442b6d00ecbe55ac6a674160c9c5510a]
- RMPD        [Cross Correlation Function] [Cross correlation] [2010-12-29 19:42:55] [17d39bb3ec485d4ce196f61215d11ba1]
-               [Cross Correlation Function] [cross correlation] [2010-12-29 22:35:31] [442b6d00ecbe55ac6a674160c9c5510a]
- RMPD        [ARIMA Backward Selection] [Arima bw - NWWZ- ...] [2010-12-29 19:51:03] [17d39bb3ec485d4ce196f61215d11ba1]
- R PD        [ARIMA Forecasting] [Arima forcasting ...] [2010-12-29 20:07:50] [87d09f1da78d94c90b11e34ec961a75e]
- R PD        [ARIMA Forecasting] [forcastingmodel f...] [2010-12-29 20:13:09] [17d39bb3ec485d4ce196f61215d11ba1]
- RMPD        [ARIMA Backward Selection] [Arima- backward f...] [2010-12-29 20:17:01] [17d39bb3ec485d4ce196f61215d11ba1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.8
100.5
110.4
96.4
101.9
106.2
81
94.7
101
109.4
102.3
90.7
96.2
96.1
106
103.1
102
104.7
86
92.1
106.9
112.6
101.7
92
97.4
97
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3
91
Dataseries Y:
Download CSV
Histogram 
128
502
629.7
595.9
823.7
498.7
766.9
1611.3
329.7
1378.9
1159.4
790.1
-189.6
862.4
426.6
852
834.7
1026.7
1052.8
1280.9
-243.6
976
908.2
416
610.7
728
520.8
905.8
768.9
479.3
1054.2
1411.9
-131
1526.2
1049.5
550.8
168.5
458.2
297
616.3
762.7
693.1
512.7
1169.2
-915.1
1384.2
1368.9
-275.1
-408.9
-37.5
171.5
671.8
-18.5
231.6
747.5
1505.7
-83.6
1173.2
1452.1
777
-52.8
861.2
735.2
1073.6
966.9
1189.8
1093.5
1782.7
-70.4
1471.6
1273.8
900.8
-910.2
299.8
460.2
677.2
937.1
1265.4
1275.6
1582.6
-154.2
1667.7
1083.1
891.7
-26.5
423.4
662.8
711.4
993.3
1133.2
343.9
1415.8
-531.8
1193.6
1201.3
805.6
-164.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67308&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67308&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67308&T=0

As an alternative you can also use a QR Code:  
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'Gwilym Jenkins' @ 72.249.127.135






Model: Y[t] = c + b X[t] + e[t]
c951.635620322542
b-2.45104565968771

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 951.635620322542 \tabularnewline
b & -2.45104565968771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67308&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]951.635620322542[/C][/ROW]
[ROW][C]b[/C][C]-2.45104565968771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67308&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67308&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Model: Y[t] = c + b X[t] + e[t]
c951.635620322542
b-2.45104565968771






Descriptive Statistics about e[t]
# observations97
minimum-1602.02478039564
Q1-310.139419631272
median57.7119588928226
mean6.97265841857366e-15
Q3409.167852920076
maximum1077.39446847607

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 97 \tabularnewline
minimum & -1602.02478039564 \tabularnewline
Q1 & -310.139419631272 \tabularnewline
median & 57.7119588928226 \tabularnewline
mean & 6.97265841857366e-15 \tabularnewline
Q3 & 409.167852920076 \tabularnewline
maximum & 1077.39446847607 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67308&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]97[/C][/ROW]
[ROW][C]minimum[/C][C]-1602.02478039564[/C][/ROW]
[ROW][C]Q1[/C][C]-310.139419631272[/C][/ROW]
[ROW][C]median[/C][C]57.7119588928226[/C][/ROW]
[ROW][C]mean[/C][C]6.97265841857366e-15[/C][/ROW]
[ROW][C]Q3[/C][C]409.167852920076[/C][/ROW]
[ROW][C]maximum[/C][C]1077.39446847607[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67308&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67308&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Descriptive Statistics about e[t]
# observations97
minimum-1602.02478039564
Q1-310.139419631272
median57.7119588928226
mean6.97265841857366e-15
Q3409.167852920076
maximum1077.39446847607


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t]   bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
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,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')