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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 computationWed, 04 Dec 2013 06:42:32 -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/2013/Dec/04/t1386157475rr5c64nojn2weoq.htm/, Retrieved Thu, 28 Mar 2024 22:18:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230530, Retrieved Thu, 28 Mar 2024 22:18:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Spectral Analysis] [Unemployment] [2010-11-29 09:27:34] [b98453cac15ba1066b407e146608df68]
- RMPD      [(Partial) Autocorrelation Function] [WS 9 ACF 1] [2013-12-04 11:42:32] [048684812ca01f747ec4932e1d7a1787] [Current]
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Dataseries X:
46
62
66
59
58
61
41
27
58
70
49
59
44
36
72
45
56
54
53
35
61
52
47
51
52
63
74
45
51
64
36
30
55
64
39
40
63
45
59
55
40
64
27
28
45
57
45
69
60
56
58
50
51
53
37
22
55
70
62
58
39
49
58
47
42
62
39
40
72
70
54
65




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230530&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230530&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230530&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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0703190.59670.276298
2-0.233976-1.98540.025457
30.0681120.57790.282551
4-0.142495-1.20910.115287
5-0.211961-1.79850.038141
60.0689130.58470.280274
7-0.1007-0.85450.19784
8-0.052042-0.44160.330054
90.1182471.00340.159524
10-0.112644-0.95580.171181
110.1140180.96750.168272
120.463813.93569.5e-05
13-0.037397-0.31730.375959
14-0.269423-2.28610.012595
150.0568020.4820.31564
16-0.133191-1.13020.131079
17-0.178608-1.51550.067008
180.0454740.38590.35037

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.070319 & 0.5967 & 0.276298 \tabularnewline
2 & -0.233976 & -1.9854 & 0.025457 \tabularnewline
3 & 0.068112 & 0.5779 & 0.282551 \tabularnewline
4 & -0.142495 & -1.2091 & 0.115287 \tabularnewline
5 & -0.211961 & -1.7985 & 0.038141 \tabularnewline
6 & 0.068913 & 0.5847 & 0.280274 \tabularnewline
7 & -0.1007 & -0.8545 & 0.19784 \tabularnewline
8 & -0.052042 & -0.4416 & 0.330054 \tabularnewline
9 & 0.118247 & 1.0034 & 0.159524 \tabularnewline
10 & -0.112644 & -0.9558 & 0.171181 \tabularnewline
11 & 0.114018 & 0.9675 & 0.168272 \tabularnewline
12 & 0.46381 & 3.9356 & 9.5e-05 \tabularnewline
13 & -0.037397 & -0.3173 & 0.375959 \tabularnewline
14 & -0.269423 & -2.2861 & 0.012595 \tabularnewline
15 & 0.056802 & 0.482 & 0.31564 \tabularnewline
16 & -0.133191 & -1.1302 & 0.131079 \tabularnewline
17 & -0.178608 & -1.5155 & 0.067008 \tabularnewline
18 & 0.045474 & 0.3859 & 0.35037 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230530&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]0.070319[/C][C]0.5967[/C][C]0.276298[/C][/ROW]
[ROW][C]2[/C][C]-0.233976[/C][C]-1.9854[/C][C]0.025457[/C][/ROW]
[ROW][C]3[/C][C]0.068112[/C][C]0.5779[/C][C]0.282551[/C][/ROW]
[ROW][C]4[/C][C]-0.142495[/C][C]-1.2091[/C][C]0.115287[/C][/ROW]
[ROW][C]5[/C][C]-0.211961[/C][C]-1.7985[/C][C]0.038141[/C][/ROW]
[ROW][C]6[/C][C]0.068913[/C][C]0.5847[/C][C]0.280274[/C][/ROW]
[ROW][C]7[/C][C]-0.1007[/C][C]-0.8545[/C][C]0.19784[/C][/ROW]
[ROW][C]8[/C][C]-0.052042[/C][C]-0.4416[/C][C]0.330054[/C][/ROW]
[ROW][C]9[/C][C]0.118247[/C][C]1.0034[/C][C]0.159524[/C][/ROW]
[ROW][C]10[/C][C]-0.112644[/C][C]-0.9558[/C][C]0.171181[/C][/ROW]
[ROW][C]11[/C][C]0.114018[/C][C]0.9675[/C][C]0.168272[/C][/ROW]
[ROW][C]12[/C][C]0.46381[/C][C]3.9356[/C][C]9.5e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.037397[/C][C]-0.3173[/C][C]0.375959[/C][/ROW]
[ROW][C]14[/C][C]-0.269423[/C][C]-2.2861[/C][C]0.012595[/C][/ROW]
[ROW][C]15[/C][C]0.056802[/C][C]0.482[/C][C]0.31564[/C][/ROW]
[ROW][C]16[/C][C]-0.133191[/C][C]-1.1302[/C][C]0.131079[/C][/ROW]
[ROW][C]17[/C][C]-0.178608[/C][C]-1.5155[/C][C]0.067008[/C][/ROW]
[ROW][C]18[/C][C]0.045474[/C][C]0.3859[/C][C]0.35037[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230530&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230530&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
10.0703190.59670.276298
2-0.233976-1.98540.025457
30.0681120.57790.282551
4-0.142495-1.20910.115287
5-0.211961-1.79850.038141
60.0689130.58470.280274
7-0.1007-0.85450.19784
8-0.052042-0.44160.330054
90.1182471.00340.159524
10-0.112644-0.95580.171181
110.1140180.96750.168272
120.463813.93569.5e-05
13-0.037397-0.31730.375959
14-0.269423-2.28610.012595
150.0568020.4820.31564
16-0.133191-1.13020.131079
17-0.178608-1.51550.067008
180.0454740.38590.35037







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0703190.59670.276298
2-0.240108-2.03740.022644
30.1124030.95380.171694
4-0.234004-1.98560.025444
5-0.139325-1.18220.120506
60.0042840.03630.485553
7-0.202861-1.72130.044743
8-0.002173-0.01840.492671
9-0.036368-0.30860.379261
10-0.176649-1.49890.069134
110.1792881.52130.066281
120.3495422.9660.002046
13-0.013446-0.11410.45474
14-0.12453-1.05670.147096
150.0442190.37520.354303
16-0.059446-0.50440.307754
17-0.030484-0.25870.398315
18-0.083966-0.71250.239237

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.070319 & 0.5967 & 0.276298 \tabularnewline
2 & -0.240108 & -2.0374 & 0.022644 \tabularnewline
3 & 0.112403 & 0.9538 & 0.171694 \tabularnewline
4 & -0.234004 & -1.9856 & 0.025444 \tabularnewline
5 & -0.139325 & -1.1822 & 0.120506 \tabularnewline
6 & 0.004284 & 0.0363 & 0.485553 \tabularnewline
7 & -0.202861 & -1.7213 & 0.044743 \tabularnewline
8 & -0.002173 & -0.0184 & 0.492671 \tabularnewline
9 & -0.036368 & -0.3086 & 0.379261 \tabularnewline
10 & -0.176649 & -1.4989 & 0.069134 \tabularnewline
11 & 0.179288 & 1.5213 & 0.066281 \tabularnewline
12 & 0.349542 & 2.966 & 0.002046 \tabularnewline
13 & -0.013446 & -0.1141 & 0.45474 \tabularnewline
14 & -0.12453 & -1.0567 & 0.147096 \tabularnewline
15 & 0.044219 & 0.3752 & 0.354303 \tabularnewline
16 & -0.059446 & -0.5044 & 0.307754 \tabularnewline
17 & -0.030484 & -0.2587 & 0.398315 \tabularnewline
18 & -0.083966 & -0.7125 & 0.239237 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230530&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]0.070319[/C][C]0.5967[/C][C]0.276298[/C][/ROW]
[ROW][C]2[/C][C]-0.240108[/C][C]-2.0374[/C][C]0.022644[/C][/ROW]
[ROW][C]3[/C][C]0.112403[/C][C]0.9538[/C][C]0.171694[/C][/ROW]
[ROW][C]4[/C][C]-0.234004[/C][C]-1.9856[/C][C]0.025444[/C][/ROW]
[ROW][C]5[/C][C]-0.139325[/C][C]-1.1822[/C][C]0.120506[/C][/ROW]
[ROW][C]6[/C][C]0.004284[/C][C]0.0363[/C][C]0.485553[/C][/ROW]
[ROW][C]7[/C][C]-0.202861[/C][C]-1.7213[/C][C]0.044743[/C][/ROW]
[ROW][C]8[/C][C]-0.002173[/C][C]-0.0184[/C][C]0.492671[/C][/ROW]
[ROW][C]9[/C][C]-0.036368[/C][C]-0.3086[/C][C]0.379261[/C][/ROW]
[ROW][C]10[/C][C]-0.176649[/C][C]-1.4989[/C][C]0.069134[/C][/ROW]
[ROW][C]11[/C][C]0.179288[/C][C]1.5213[/C][C]0.066281[/C][/ROW]
[ROW][C]12[/C][C]0.349542[/C][C]2.966[/C][C]0.002046[/C][/ROW]
[ROW][C]13[/C][C]-0.013446[/C][C]-0.1141[/C][C]0.45474[/C][/ROW]
[ROW][C]14[/C][C]-0.12453[/C][C]-1.0567[/C][C]0.147096[/C][/ROW]
[ROW][C]15[/C][C]0.044219[/C][C]0.3752[/C][C]0.354303[/C][/ROW]
[ROW][C]16[/C][C]-0.059446[/C][C]-0.5044[/C][C]0.307754[/C][/ROW]
[ROW][C]17[/C][C]-0.030484[/C][C]-0.2587[/C][C]0.398315[/C][/ROW]
[ROW][C]18[/C][C]-0.083966[/C][C]-0.7125[/C][C]0.239237[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230530&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230530&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
10.0703190.59670.276298
2-0.240108-2.03740.022644
30.1124030.95380.171694
4-0.234004-1.98560.025444
5-0.139325-1.18220.120506
60.0042840.03630.485553
7-0.202861-1.72130.044743
8-0.002173-0.01840.492671
9-0.036368-0.30860.379261
10-0.176649-1.49890.069134
110.1792881.52130.066281
120.3495422.9660.002046
13-0.013446-0.11410.45474
14-0.12453-1.05670.147096
150.0442190.37520.354303
16-0.059446-0.50440.307754
17-0.030484-0.25870.398315
18-0.083966-0.71250.239237



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')