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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 25 Nov 2011 10:10:22 -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/25/t1322234081mdajsipv0zndvjf.htm/, Retrieved Mon, 24 Jun 2024 12:54:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147334, Retrieved Mon, 24 Jun 2024 12:54:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMPD          [(Partial) Autocorrelation Function] [] [2011-11-25 15:10:22] [f8ac047da1b1db86cbd9837decfb2b34] [Current]
- R  D            [(Partial) Autocorrelation Function] [Paper] [2011-12-23 08:01:40] [ec29c78521a0445a37e4526edb78f709]
- RMPD            [Kernel Density Estimation] [Paper 1] [2011-12-23 09:00:56] [ec29c78521a0445a37e4526edb78f709]
- RMPD            [Histogram] [Paper 2] [2011-12-23 09:02:43] [ec29c78521a0445a37e4526edb78f709]
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Dataseries X:
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556

















































Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=147334&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=147334&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147334&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'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3058192.64850.004926
20.3998733.4630.000443
30.3767363.26260.000832
40.1227261.06280.145632
50.2117041.83340.035354
60.1514121.31130.096884
70.137031.18670.119543
80.0394290.34150.366853
90.2922972.53140.006728
100.1622331.4050.082079
110.1626121.40830.081593
120.5787335.0122e-06
130.123171.06670.144768
140.2738482.37160.010139
150.1853481.60520.05633
16-0.025095-0.21730.41427
170.0564830.48920.313079
180.0435050.37680.353705

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.305819 & 2.6485 & 0.004926 \tabularnewline
2 & 0.399873 & 3.463 & 0.000443 \tabularnewline
3 & 0.376736 & 3.2626 & 0.000832 \tabularnewline
4 & 0.122726 & 1.0628 & 0.145632 \tabularnewline
5 & 0.211704 & 1.8334 & 0.035354 \tabularnewline
6 & 0.151412 & 1.3113 & 0.096884 \tabularnewline
7 & 0.13703 & 1.1867 & 0.119543 \tabularnewline
8 & 0.039429 & 0.3415 & 0.366853 \tabularnewline
9 & 0.292297 & 2.5314 & 0.006728 \tabularnewline
10 & 0.162233 & 1.405 & 0.082079 \tabularnewline
11 & 0.162612 & 1.4083 & 0.081593 \tabularnewline
12 & 0.578733 & 5.012 & 2e-06 \tabularnewline
13 & 0.12317 & 1.0667 & 0.144768 \tabularnewline
14 & 0.273848 & 2.3716 & 0.010139 \tabularnewline
15 & 0.185348 & 1.6052 & 0.05633 \tabularnewline
16 & -0.025095 & -0.2173 & 0.41427 \tabularnewline
17 & 0.056483 & 0.4892 & 0.313079 \tabularnewline
18 & 0.043505 & 0.3768 & 0.353705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147334&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.305819[/C][C]2.6485[/C][C]0.004926[/C][/ROW]
[ROW][C]2[/C][C]0.399873[/C][C]3.463[/C][C]0.000443[/C][/ROW]
[ROW][C]3[/C][C]0.376736[/C][C]3.2626[/C][C]0.000832[/C][/ROW]
[ROW][C]4[/C][C]0.122726[/C][C]1.0628[/C][C]0.145632[/C][/ROW]
[ROW][C]5[/C][C]0.211704[/C][C]1.8334[/C][C]0.035354[/C][/ROW]
[ROW][C]6[/C][C]0.151412[/C][C]1.3113[/C][C]0.096884[/C][/ROW]
[ROW][C]7[/C][C]0.13703[/C][C]1.1867[/C][C]0.119543[/C][/ROW]
[ROW][C]8[/C][C]0.039429[/C][C]0.3415[/C][C]0.366853[/C][/ROW]
[ROW][C]9[/C][C]0.292297[/C][C]2.5314[/C][C]0.006728[/C][/ROW]
[ROW][C]10[/C][C]0.162233[/C][C]1.405[/C][C]0.082079[/C][/ROW]
[ROW][C]11[/C][C]0.162612[/C][C]1.4083[/C][C]0.081593[/C][/ROW]
[ROW][C]12[/C][C]0.578733[/C][C]5.012[/C][C]2e-06[/C][/ROW]
[ROW][C]13[/C][C]0.12317[/C][C]1.0667[/C][C]0.144768[/C][/ROW]
[ROW][C]14[/C][C]0.273848[/C][C]2.3716[/C][C]0.010139[/C][/ROW]
[ROW][C]15[/C][C]0.185348[/C][C]1.6052[/C][C]0.05633[/C][/ROW]
[ROW][C]16[/C][C]-0.025095[/C][C]-0.2173[/C][C]0.41427[/C][/ROW]
[ROW][C]17[/C][C]0.056483[/C][C]0.4892[/C][C]0.313079[/C][/ROW]
[ROW][C]18[/C][C]0.043505[/C][C]0.3768[/C][C]0.353705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147334&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147334&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3058192.64850.004926
20.3998733.4630.000443
30.3767363.26260.000832
40.1227261.06280.145632
50.2117041.83340.035354
60.1514121.31130.096884
70.137031.18670.119543
80.0394290.34150.366853
90.2922972.53140.006728
100.1622331.4050.082079
110.1626121.40830.081593
120.5787335.0122e-06
130.123171.06670.144768
140.2738482.37160.010139
150.1853481.60520.05633
16-0.025095-0.21730.41427
170.0564830.48920.313079
180.0435050.37680.353705







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3058192.64850.004926
20.3379552.92680.002265
30.2396462.07540.020689
4-0.14807-1.28230.10184
50.0128570.11130.45582
60.0513960.44510.328763
70.0780590.6760.250558
8-0.12924-1.11930.133301
90.2958042.56170.006211
100.0869510.7530.226898
11-0.023225-0.20110.420569
120.4883934.22963.3e-05
13-0.178637-1.5470.063031
14-0.147488-1.27730.102721
15-0.127635-1.10540.13627
16-0.121525-1.05240.14799
17-0.05138-0.4450.328814
180.0751290.65060.258634

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.305819 & 2.6485 & 0.004926 \tabularnewline
2 & 0.337955 & 2.9268 & 0.002265 \tabularnewline
3 & 0.239646 & 2.0754 & 0.020689 \tabularnewline
4 & -0.14807 & -1.2823 & 0.10184 \tabularnewline
5 & 0.012857 & 0.1113 & 0.45582 \tabularnewline
6 & 0.051396 & 0.4451 & 0.328763 \tabularnewline
7 & 0.078059 & 0.676 & 0.250558 \tabularnewline
8 & -0.12924 & -1.1193 & 0.133301 \tabularnewline
9 & 0.295804 & 2.5617 & 0.006211 \tabularnewline
10 & 0.086951 & 0.753 & 0.226898 \tabularnewline
11 & -0.023225 & -0.2011 & 0.420569 \tabularnewline
12 & 0.488393 & 4.2296 & 3.3e-05 \tabularnewline
13 & -0.178637 & -1.547 & 0.063031 \tabularnewline
14 & -0.147488 & -1.2773 & 0.102721 \tabularnewline
15 & -0.127635 & -1.1054 & 0.13627 \tabularnewline
16 & -0.121525 & -1.0524 & 0.14799 \tabularnewline
17 & -0.05138 & -0.445 & 0.328814 \tabularnewline
18 & 0.075129 & 0.6506 & 0.258634 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147334&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]0.305819[/C][C]2.6485[/C][C]0.004926[/C][/ROW]
[ROW][C]2[/C][C]0.337955[/C][C]2.9268[/C][C]0.002265[/C][/ROW]
[ROW][C]3[/C][C]0.239646[/C][C]2.0754[/C][C]0.020689[/C][/ROW]
[ROW][C]4[/C][C]-0.14807[/C][C]-1.2823[/C][C]0.10184[/C][/ROW]
[ROW][C]5[/C][C]0.012857[/C][C]0.1113[/C][C]0.45582[/C][/ROW]
[ROW][C]6[/C][C]0.051396[/C][C]0.4451[/C][C]0.328763[/C][/ROW]
[ROW][C]7[/C][C]0.078059[/C][C]0.676[/C][C]0.250558[/C][/ROW]
[ROW][C]8[/C][C]-0.12924[/C][C]-1.1193[/C][C]0.133301[/C][/ROW]
[ROW][C]9[/C][C]0.295804[/C][C]2.5617[/C][C]0.006211[/C][/ROW]
[ROW][C]10[/C][C]0.086951[/C][C]0.753[/C][C]0.226898[/C][/ROW]
[ROW][C]11[/C][C]-0.023225[/C][C]-0.2011[/C][C]0.420569[/C][/ROW]
[ROW][C]12[/C][C]0.488393[/C][C]4.2296[/C][C]3.3e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.178637[/C][C]-1.547[/C][C]0.063031[/C][/ROW]
[ROW][C]14[/C][C]-0.147488[/C][C]-1.2773[/C][C]0.102721[/C][/ROW]
[ROW][C]15[/C][C]-0.127635[/C][C]-1.1054[/C][C]0.13627[/C][/ROW]
[ROW][C]16[/C][C]-0.121525[/C][C]-1.0524[/C][C]0.14799[/C][/ROW]
[ROW][C]17[/C][C]-0.05138[/C][C]-0.445[/C][C]0.328814[/C][/ROW]
[ROW][C]18[/C][C]0.075129[/C][C]0.6506[/C][C]0.258634[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147334&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147334&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3058192.64850.004926
20.3379552.92680.002265
30.2396462.07540.020689
4-0.14807-1.28230.10184
50.0128570.11130.45582
60.0513960.44510.328763
70.0780590.6760.250558
8-0.12924-1.11930.133301
90.2958042.56170.006211
100.0869510.7530.226898
11-0.023225-0.20110.420569
120.4883934.22963.3e-05
13-0.178637-1.5470.063031
14-0.147488-1.27730.102721
15-0.127635-1.10540.13627
16-0.121525-1.05240.14799
17-0.05138-0.4450.328814
180.0751290.65060.258634



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
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,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')