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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 computationSun, 18 Dec 2016 09:40:42 +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/18/t1482050542hhk0dabu960osr8.htm/, Retrieved Fri, 01 Nov 2024 03:47:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300980, Retrieved Fri, 01 Nov 2024 03:47:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelation N...] [2016-12-18 08:40:42] [08c254f01fc4fb8b56d19f4878327019] [Current]
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Dataseries X:
5884.5
5879.1
5897.2
5920.7
5944.6
5982.4
6017.4
5980
6087.4
6114.5
6143.2
6173.1
6195.7
6236
6255.2
6282.5
6301.7
6330.9
6350.8
6363
6388.6
6411.5
6436.4
6449.2
6473.3
6479.5
6507.3
6516.1
6534.2
6540.6
6542.9
6562.6
6577
6596.6
6612.1
6626.3
6640.1
6642.4
6648.7
6660.8
6668.2
6657.7
6682.8
6696.8
6714.4
6728.2
6741.8
6758.4
6774
6792.3
6809.1
6832.2
6850.3
6861.1
6882.6
6900.7
6915.1
6947.8
6965.9
6991.7
6993.9
7031.7
7048.7
7067.4
7077.1
7107.4
7127.1
7137.3
7147.9
7170.6
7193
7220.1
7251
7268.1
7282.2
7290.2
7292.5
7299.6
7305.1
7306.9
7313.3
7325.6
7348.1
7354.7
7375.3
7396.3
7401.9
7390.4
7393.6
7398.5
7392.4
7390.8
7380.6
7365.8
7346.9
7334.1
7314.8
7287.8
7274.3
7252.7
7257.5
7256.5
7253.9
7262.6
7263.6
7261.3
7250.4
7249.3
7245.6
7244.4
7253.8
7271.6
7282.7
7283
7293.3
7291.2
7298.5




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=300980&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=300980&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300980&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
1-0.629098-6.74630
20.1567421.68090.047752
30.0180790.19390.423306
4-0.030579-0.32790.371784
50.0444470.47660.317263
6-0.073905-0.79250.214838
70.0774420.83050.203996
8-0.07832-0.83990.201357
90.0738890.79240.214889
10-0.05963-0.63950.261898
110.0185240.19860.421446
120.0326480.35010.363448
13-0.033635-0.36070.359493
140.0241930.25940.397879
15-0.065941-0.70710.240456
160.1112421.19290.117675
17-0.154318-1.65490.050338
180.1323091.41890.079322
19-0.058765-0.63020.264912
200.0409620.43930.330644

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629098 & -6.7463 & 0 \tabularnewline
2 & 0.156742 & 1.6809 & 0.047752 \tabularnewline
3 & 0.018079 & 0.1939 & 0.423306 \tabularnewline
4 & -0.030579 & -0.3279 & 0.371784 \tabularnewline
5 & 0.044447 & 0.4766 & 0.317263 \tabularnewline
6 & -0.073905 & -0.7925 & 0.214838 \tabularnewline
7 & 0.077442 & 0.8305 & 0.203996 \tabularnewline
8 & -0.07832 & -0.8399 & 0.201357 \tabularnewline
9 & 0.073889 & 0.7924 & 0.214889 \tabularnewline
10 & -0.05963 & -0.6395 & 0.261898 \tabularnewline
11 & 0.018524 & 0.1986 & 0.421446 \tabularnewline
12 & 0.032648 & 0.3501 & 0.363448 \tabularnewline
13 & -0.033635 & -0.3607 & 0.359493 \tabularnewline
14 & 0.024193 & 0.2594 & 0.397879 \tabularnewline
15 & -0.065941 & -0.7071 & 0.240456 \tabularnewline
16 & 0.111242 & 1.1929 & 0.117675 \tabularnewline
17 & -0.154318 & -1.6549 & 0.050338 \tabularnewline
18 & 0.132309 & 1.4189 & 0.079322 \tabularnewline
19 & -0.058765 & -0.6302 & 0.264912 \tabularnewline
20 & 0.040962 & 0.4393 & 0.330644 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300980&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]-0.629098[/C][C]-6.7463[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.156742[/C][C]1.6809[/C][C]0.047752[/C][/ROW]
[ROW][C]3[/C][C]0.018079[/C][C]0.1939[/C][C]0.423306[/C][/ROW]
[ROW][C]4[/C][C]-0.030579[/C][C]-0.3279[/C][C]0.371784[/C][/ROW]
[ROW][C]5[/C][C]0.044447[/C][C]0.4766[/C][C]0.317263[/C][/ROW]
[ROW][C]6[/C][C]-0.073905[/C][C]-0.7925[/C][C]0.214838[/C][/ROW]
[ROW][C]7[/C][C]0.077442[/C][C]0.8305[/C][C]0.203996[/C][/ROW]
[ROW][C]8[/C][C]-0.07832[/C][C]-0.8399[/C][C]0.201357[/C][/ROW]
[ROW][C]9[/C][C]0.073889[/C][C]0.7924[/C][C]0.214889[/C][/ROW]
[ROW][C]10[/C][C]-0.05963[/C][C]-0.6395[/C][C]0.261898[/C][/ROW]
[ROW][C]11[/C][C]0.018524[/C][C]0.1986[/C][C]0.421446[/C][/ROW]
[ROW][C]12[/C][C]0.032648[/C][C]0.3501[/C][C]0.363448[/C][/ROW]
[ROW][C]13[/C][C]-0.033635[/C][C]-0.3607[/C][C]0.359493[/C][/ROW]
[ROW][C]14[/C][C]0.024193[/C][C]0.2594[/C][C]0.397879[/C][/ROW]
[ROW][C]15[/C][C]-0.065941[/C][C]-0.7071[/C][C]0.240456[/C][/ROW]
[ROW][C]16[/C][C]0.111242[/C][C]1.1929[/C][C]0.117675[/C][/ROW]
[ROW][C]17[/C][C]-0.154318[/C][C]-1.6549[/C][C]0.050338[/C][/ROW]
[ROW][C]18[/C][C]0.132309[/C][C]1.4189[/C][C]0.079322[/C][/ROW]
[ROW][C]19[/C][C]-0.058765[/C][C]-0.6302[/C][C]0.264912[/C][/ROW]
[ROW][C]20[/C][C]0.040962[/C][C]0.4393[/C][C]0.330644[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300980&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300980&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
1-0.629098-6.74630
20.1567421.68090.047752
30.0180790.19390.423306
4-0.030579-0.32790.371784
50.0444470.47660.317263
6-0.073905-0.79250.214838
70.0774420.83050.203996
8-0.07832-0.83990.201357
90.0738890.79240.214889
10-0.05963-0.63950.261898
110.0185240.19860.421446
120.0326480.35010.363448
13-0.033635-0.36070.359493
140.0241930.25940.397879
15-0.065941-0.70710.240456
160.1112421.19290.117675
17-0.154318-1.65490.050338
180.1323091.41890.079322
19-0.058765-0.63020.264912
200.0409620.43930.330644







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.629098-6.74630
2-0.395578-4.24212.3e-05
3-0.182791-1.96020.026195
4-0.083698-0.89760.185647
50.0291870.3130.377423
6-0.036422-0.39060.348416
70.0092680.09940.460502
8-0.059118-0.6340.263679
90.001490.0160.493642
10-0.025026-0.26840.394445
11-0.03888-0.41690.338748
120.0202950.21760.414048
130.0373710.40080.344669
140.0429880.4610.322835
15-0.072327-0.77560.219783
160.0227660.24410.403779
17-0.120999-1.29760.098517
18-0.047544-0.50990.305565
19-0.011239-0.12050.45214
200.0843230.90430.183873

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.629098 & -6.7463 & 0 \tabularnewline
2 & -0.395578 & -4.2421 & 2.3e-05 \tabularnewline
3 & -0.182791 & -1.9602 & 0.026195 \tabularnewline
4 & -0.083698 & -0.8976 & 0.185647 \tabularnewline
5 & 0.029187 & 0.313 & 0.377423 \tabularnewline
6 & -0.036422 & -0.3906 & 0.348416 \tabularnewline
7 & 0.009268 & 0.0994 & 0.460502 \tabularnewline
8 & -0.059118 & -0.634 & 0.263679 \tabularnewline
9 & 0.00149 & 0.016 & 0.493642 \tabularnewline
10 & -0.025026 & -0.2684 & 0.394445 \tabularnewline
11 & -0.03888 & -0.4169 & 0.338748 \tabularnewline
12 & 0.020295 & 0.2176 & 0.414048 \tabularnewline
13 & 0.037371 & 0.4008 & 0.344669 \tabularnewline
14 & 0.042988 & 0.461 & 0.322835 \tabularnewline
15 & -0.072327 & -0.7756 & 0.219783 \tabularnewline
16 & 0.022766 & 0.2441 & 0.403779 \tabularnewline
17 & -0.120999 & -1.2976 & 0.098517 \tabularnewline
18 & -0.047544 & -0.5099 & 0.305565 \tabularnewline
19 & -0.011239 & -0.1205 & 0.45214 \tabularnewline
20 & 0.084323 & 0.9043 & 0.183873 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300980&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]-0.629098[/C][C]-6.7463[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.395578[/C][C]-4.2421[/C][C]2.3e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.182791[/C][C]-1.9602[/C][C]0.026195[/C][/ROW]
[ROW][C]4[/C][C]-0.083698[/C][C]-0.8976[/C][C]0.185647[/C][/ROW]
[ROW][C]5[/C][C]0.029187[/C][C]0.313[/C][C]0.377423[/C][/ROW]
[ROW][C]6[/C][C]-0.036422[/C][C]-0.3906[/C][C]0.348416[/C][/ROW]
[ROW][C]7[/C][C]0.009268[/C][C]0.0994[/C][C]0.460502[/C][/ROW]
[ROW][C]8[/C][C]-0.059118[/C][C]-0.634[/C][C]0.263679[/C][/ROW]
[ROW][C]9[/C][C]0.00149[/C][C]0.016[/C][C]0.493642[/C][/ROW]
[ROW][C]10[/C][C]-0.025026[/C][C]-0.2684[/C][C]0.394445[/C][/ROW]
[ROW][C]11[/C][C]-0.03888[/C][C]-0.4169[/C][C]0.338748[/C][/ROW]
[ROW][C]12[/C][C]0.020295[/C][C]0.2176[/C][C]0.414048[/C][/ROW]
[ROW][C]13[/C][C]0.037371[/C][C]0.4008[/C][C]0.344669[/C][/ROW]
[ROW][C]14[/C][C]0.042988[/C][C]0.461[/C][C]0.322835[/C][/ROW]
[ROW][C]15[/C][C]-0.072327[/C][C]-0.7756[/C][C]0.219783[/C][/ROW]
[ROW][C]16[/C][C]0.022766[/C][C]0.2441[/C][C]0.403779[/C][/ROW]
[ROW][C]17[/C][C]-0.120999[/C][C]-1.2976[/C][C]0.098517[/C][/ROW]
[ROW][C]18[/C][C]-0.047544[/C][C]-0.5099[/C][C]0.305565[/C][/ROW]
[ROW][C]19[/C][C]-0.011239[/C][C]-0.1205[/C][C]0.45214[/C][/ROW]
[ROW][C]20[/C][C]0.084323[/C][C]0.9043[/C][C]0.183873[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300980&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300980&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
1-0.629098-6.74630
2-0.395578-4.24212.3e-05
3-0.182791-1.96020.026195
4-0.083698-0.89760.185647
50.0291870.3130.377423
6-0.036422-0.39060.348416
70.0092680.09940.460502
8-0.059118-0.6340.263679
90.001490.0160.493642
10-0.025026-0.26840.394445
11-0.03888-0.41690.338748
120.0202950.21760.414048
130.0373710.40080.344669
140.0429880.4610.322835
15-0.072327-0.77560.219783
160.0227660.24410.403779
17-0.120999-1.29760.098517
18-0.047544-0.50990.305565
19-0.011239-0.12050.45214
200.0843230.90430.183873



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 1 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 1 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '1'
par4 <- '0'
par3 <- '1'
par2 <- '1'
par1 <- 'Default'
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')