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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, 16 Dec 2016 15:32:54 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/16/t1481898905r4sauyurhv4momo.htm/, Retrieved Thu, 02 May 2024 17:10:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300315, Retrieved Thu, 02 May 2024 17:10:42 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact53
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelation f...] [2016-12-16 14:32:54] [31f526a885cd288e1bc58dc4a6a7fb1f] [Current]
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Dataseries X:
2647.36
2711.22
2733.02
2831
2823.6
2833.46
2885.1
2929.78
3108.46
2921.92
2988.78
3038.84
3005.08
2816.94
3016.28
3242.68
3097.38
3057.18
3014.1
3063.66
3100.36
2964.4
3155.4
3217
3091.1
3192.64
3219.66
3478.26
3284.9
3382.2
3341.9
3402.18
3394.04
3374.1
3383.36
3626.54
3579.84
3530.72
3532.4
3636.68
3639.84
3676.98
3668.92
3718.74
3815.02
3799.9
3925.86
4226.32
4049.72
3883.56
3928.18
4377.66
4146.08
4246.12
4163.4
4144.76
4238.82
4352.28
4379.2
4451.02
4368.22
4337.82
4349.92
4079.42
4463.84
4552.72
4489
4455.9
4583.62
4512.76
4654.04
4768.44
4658.66
4589.98
4572.86
4643
4470.7
4635.34
4373.52
4348.18
4421.02
4363.52
4462.84
4567.34
4367.84
4382.64
4386.44
4489.36
4549.1
4627.66
4646.26
4728.68
4687.46
4755.26
4899.7
5042.06
4983.88
5028.08
4819.3
4889.86
4962.22
4968.92
5019.56
5099.18
5171.08
5353.5
5304.26
5636.62
5322.96
5308.46
5352.02
5358.9
5421.04
5537.66
5519.38
5643.06




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300315&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=300315&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300315&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.323043-3.46420.000374
2-0.091757-0.9840.163595
3-0.045297-0.48580.314033
40.0736310.78960.215693
5-0.064016-0.68650.24689
60.0680860.73010.233394
7-0.023766-0.25490.399641
80.0857710.91980.179802
9-0.107675-1.15470.125307
10-0.064162-0.68810.246401
110.0166020.1780.429503
120.1555791.66840.048979
130.0287380.30820.379252
14-0.105556-1.1320.130003
15-0.00935-0.10030.460153
16-0.071939-0.77150.221009
170.0207930.2230.411973
180.0587360.62990.265014
19-0.056784-0.60890.271881
200.0853250.9150.18105

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.323043 & -3.4642 & 0.000374 \tabularnewline
2 & -0.091757 & -0.984 & 0.163595 \tabularnewline
3 & -0.045297 & -0.4858 & 0.314033 \tabularnewline
4 & 0.073631 & 0.7896 & 0.215693 \tabularnewline
5 & -0.064016 & -0.6865 & 0.24689 \tabularnewline
6 & 0.068086 & 0.7301 & 0.233394 \tabularnewline
7 & -0.023766 & -0.2549 & 0.399641 \tabularnewline
8 & 0.085771 & 0.9198 & 0.179802 \tabularnewline
9 & -0.107675 & -1.1547 & 0.125307 \tabularnewline
10 & -0.064162 & -0.6881 & 0.246401 \tabularnewline
11 & 0.016602 & 0.178 & 0.429503 \tabularnewline
12 & 0.155579 & 1.6684 & 0.048979 \tabularnewline
13 & 0.028738 & 0.3082 & 0.379252 \tabularnewline
14 & -0.105556 & -1.132 & 0.130003 \tabularnewline
15 & -0.00935 & -0.1003 & 0.460153 \tabularnewline
16 & -0.071939 & -0.7715 & 0.221009 \tabularnewline
17 & 0.020793 & 0.223 & 0.411973 \tabularnewline
18 & 0.058736 & 0.6299 & 0.265014 \tabularnewline
19 & -0.056784 & -0.6089 & 0.271881 \tabularnewline
20 & 0.085325 & 0.915 & 0.18105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300315&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]-0.323043[/C][C]-3.4642[/C][C]0.000374[/C][/ROW]
[ROW][C]2[/C][C]-0.091757[/C][C]-0.984[/C][C]0.163595[/C][/ROW]
[ROW][C]3[/C][C]-0.045297[/C][C]-0.4858[/C][C]0.314033[/C][/ROW]
[ROW][C]4[/C][C]0.073631[/C][C]0.7896[/C][C]0.215693[/C][/ROW]
[ROW][C]5[/C][C]-0.064016[/C][C]-0.6865[/C][C]0.24689[/C][/ROW]
[ROW][C]6[/C][C]0.068086[/C][C]0.7301[/C][C]0.233394[/C][/ROW]
[ROW][C]7[/C][C]-0.023766[/C][C]-0.2549[/C][C]0.399641[/C][/ROW]
[ROW][C]8[/C][C]0.085771[/C][C]0.9198[/C][C]0.179802[/C][/ROW]
[ROW][C]9[/C][C]-0.107675[/C][C]-1.1547[/C][C]0.125307[/C][/ROW]
[ROW][C]10[/C][C]-0.064162[/C][C]-0.6881[/C][C]0.246401[/C][/ROW]
[ROW][C]11[/C][C]0.016602[/C][C]0.178[/C][C]0.429503[/C][/ROW]
[ROW][C]12[/C][C]0.155579[/C][C]1.6684[/C][C]0.048979[/C][/ROW]
[ROW][C]13[/C][C]0.028738[/C][C]0.3082[/C][C]0.379252[/C][/ROW]
[ROW][C]14[/C][C]-0.105556[/C][C]-1.132[/C][C]0.130003[/C][/ROW]
[ROW][C]15[/C][C]-0.00935[/C][C]-0.1003[/C][C]0.460153[/C][/ROW]
[ROW][C]16[/C][C]-0.071939[/C][C]-0.7715[/C][C]0.221009[/C][/ROW]
[ROW][C]17[/C][C]0.020793[/C][C]0.223[/C][C]0.411973[/C][/ROW]
[ROW][C]18[/C][C]0.058736[/C][C]0.6299[/C][C]0.265014[/C][/ROW]
[ROW][C]19[/C][C]-0.056784[/C][C]-0.6089[/C][C]0.271881[/C][/ROW]
[ROW][C]20[/C][C]0.085325[/C][C]0.915[/C][C]0.18105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300315&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300315&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
1-0.323043-3.46420.000374
2-0.091757-0.9840.163595
3-0.045297-0.48580.314033
40.0736310.78960.215693
5-0.064016-0.68650.24689
60.0680860.73010.233394
7-0.023766-0.25490.399641
80.0857710.91980.179802
9-0.107675-1.15470.125307
10-0.064162-0.68810.246401
110.0166020.1780.429503
120.1555791.66840.048979
130.0287380.30820.379252
14-0.105556-1.1320.130003
15-0.00935-0.10030.460153
16-0.071939-0.77150.221009
170.0207930.2230.411973
180.0587360.62990.265014
19-0.056784-0.60890.271881
200.0853250.9150.18105







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.323043-3.46420.000374
2-0.218963-2.34810.010288
3-0.178448-1.91360.029076
4-0.036535-0.39180.347968
5-0.090815-0.97390.166079
60.0204690.21950.413321
7-0.002515-0.0270.489264
80.1044061.11960.132601
9-0.028199-0.30240.381448
10-0.112758-1.20920.114533
11-0.079387-0.85130.198178
120.0964281.03410.151636
130.1537141.64840.051
140.0076490.0820.467386
158.7e-059e-040.499629
16-0.123993-1.32970.093128
17-0.072752-0.78020.218444
180.0080960.08680.465485
19-0.090486-0.97040.166954
200.0422320.45290.325741

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.323043 & -3.4642 & 0.000374 \tabularnewline
2 & -0.218963 & -2.3481 & 0.010288 \tabularnewline
3 & -0.178448 & -1.9136 & 0.029076 \tabularnewline
4 & -0.036535 & -0.3918 & 0.347968 \tabularnewline
5 & -0.090815 & -0.9739 & 0.166079 \tabularnewline
6 & 0.020469 & 0.2195 & 0.413321 \tabularnewline
7 & -0.002515 & -0.027 & 0.489264 \tabularnewline
8 & 0.104406 & 1.1196 & 0.132601 \tabularnewline
9 & -0.028199 & -0.3024 & 0.381448 \tabularnewline
10 & -0.112758 & -1.2092 & 0.114533 \tabularnewline
11 & -0.079387 & -0.8513 & 0.198178 \tabularnewline
12 & 0.096428 & 1.0341 & 0.151636 \tabularnewline
13 & 0.153714 & 1.6484 & 0.051 \tabularnewline
14 & 0.007649 & 0.082 & 0.467386 \tabularnewline
15 & 8.7e-05 & 9e-04 & 0.499629 \tabularnewline
16 & -0.123993 & -1.3297 & 0.093128 \tabularnewline
17 & -0.072752 & -0.7802 & 0.218444 \tabularnewline
18 & 0.008096 & 0.0868 & 0.465485 \tabularnewline
19 & -0.090486 & -0.9704 & 0.166954 \tabularnewline
20 & 0.042232 & 0.4529 & 0.325741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300315&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]-0.323043[/C][C]-3.4642[/C][C]0.000374[/C][/ROW]
[ROW][C]2[/C][C]-0.218963[/C][C]-2.3481[/C][C]0.010288[/C][/ROW]
[ROW][C]3[/C][C]-0.178448[/C][C]-1.9136[/C][C]0.029076[/C][/ROW]
[ROW][C]4[/C][C]-0.036535[/C][C]-0.3918[/C][C]0.347968[/C][/ROW]
[ROW][C]5[/C][C]-0.090815[/C][C]-0.9739[/C][C]0.166079[/C][/ROW]
[ROW][C]6[/C][C]0.020469[/C][C]0.2195[/C][C]0.413321[/C][/ROW]
[ROW][C]7[/C][C]-0.002515[/C][C]-0.027[/C][C]0.489264[/C][/ROW]
[ROW][C]8[/C][C]0.104406[/C][C]1.1196[/C][C]0.132601[/C][/ROW]
[ROW][C]9[/C][C]-0.028199[/C][C]-0.3024[/C][C]0.381448[/C][/ROW]
[ROW][C]10[/C][C]-0.112758[/C][C]-1.2092[/C][C]0.114533[/C][/ROW]
[ROW][C]11[/C][C]-0.079387[/C][C]-0.8513[/C][C]0.198178[/C][/ROW]
[ROW][C]12[/C][C]0.096428[/C][C]1.0341[/C][C]0.151636[/C][/ROW]
[ROW][C]13[/C][C]0.153714[/C][C]1.6484[/C][C]0.051[/C][/ROW]
[ROW][C]14[/C][C]0.007649[/C][C]0.082[/C][C]0.467386[/C][/ROW]
[ROW][C]15[/C][C]8.7e-05[/C][C]9e-04[/C][C]0.499629[/C][/ROW]
[ROW][C]16[/C][C]-0.123993[/C][C]-1.3297[/C][C]0.093128[/C][/ROW]
[ROW][C]17[/C][C]-0.072752[/C][C]-0.7802[/C][C]0.218444[/C][/ROW]
[ROW][C]18[/C][C]0.008096[/C][C]0.0868[/C][C]0.465485[/C][/ROW]
[ROW][C]19[/C][C]-0.090486[/C][C]-0.9704[/C][C]0.166954[/C][/ROW]
[ROW][C]20[/C][C]0.042232[/C][C]0.4529[/C][C]0.325741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300315&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300315&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
1-0.323043-3.46420.000374
2-0.218963-2.34810.010288
3-0.178448-1.91360.029076
4-0.036535-0.39180.347968
5-0.090815-0.97390.166079
60.0204690.21950.413321
7-0.002515-0.0270.489264
80.1044061.11960.132601
9-0.028199-0.30240.381448
10-0.112758-1.20920.114533
11-0.079387-0.85130.198178
120.0964281.03410.151636
130.1537141.64840.051
140.0076490.0820.467386
158.7e-059e-040.499629
16-0.123993-1.32970.093128
17-0.072752-0.78020.218444
180.0080960.08680.465485
19-0.090486-0.97040.166954
200.0422320.45290.325741



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; 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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')