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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 computationThu, 22 Dec 2016 20:42:28 +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/22/t1482436458d2dg8b2i55n30x5.htm/, Retrieved Fri, 01 Nov 2024 03:31:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302660, Retrieved Fri, 01 Nov 2024 03:31:38 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [ACF1] [2016-12-22 17:08:50] [267314984f6394bb93cd815224aa34ba]
- R  D    [(Partial) Autocorrelation Function] [ACF3] [2016-12-22 19:42:28] [636d0f72197ac5e1dae4a755427db02a] [Current]
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Dataseries X:
3120
3360
3540
2700
2580
3480
3240
4440
3000
3720
1620
3360
3180
2100
3000
2520
2160
1980
4020
3480
2750
2640
3420
2640
2520
2040
2820
1860
3780
2520
2580
2880
2100
3060
2100
3720
2940
2820
4980
2400
2940
2640
2340
1680
4140
2640
3600
3240
3120
2460
2940

































































































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
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 Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \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=302660&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] [ROW]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=302660&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302660&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
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
1-0.170199-1.21550.114893
20.1319150.94210.175301
3-0.048957-0.34960.364031
4-0.074218-0.530.299199
5-0.145204-1.0370.152322
60.0152930.10920.45673
70.1249480.89230.188209
8-0.141372-1.00960.158727
90.0571570.40820.342423
100.1028860.73480.232928
11-0.019759-0.14110.44417
12-0.03579-0.25560.399648
130.0078020.05570.477892
14-0.083952-0.59950.275735
15-0.071606-0.51140.305649
160.1076190.76860.222851
170.0985840.7040.242308

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.170199 & -1.2155 & 0.114893 \tabularnewline
2 & 0.131915 & 0.9421 & 0.175301 \tabularnewline
3 & -0.048957 & -0.3496 & 0.364031 \tabularnewline
4 & -0.074218 & -0.53 & 0.299199 \tabularnewline
5 & -0.145204 & -1.037 & 0.152322 \tabularnewline
6 & 0.015293 & 0.1092 & 0.45673 \tabularnewline
7 & 0.124948 & 0.8923 & 0.188209 \tabularnewline
8 & -0.141372 & -1.0096 & 0.158727 \tabularnewline
9 & 0.057157 & 0.4082 & 0.342423 \tabularnewline
10 & 0.102886 & 0.7348 & 0.232928 \tabularnewline
11 & -0.019759 & -0.1411 & 0.44417 \tabularnewline
12 & -0.03579 & -0.2556 & 0.399648 \tabularnewline
13 & 0.007802 & 0.0557 & 0.477892 \tabularnewline
14 & -0.083952 & -0.5995 & 0.275735 \tabularnewline
15 & -0.071606 & -0.5114 & 0.305649 \tabularnewline
16 & 0.107619 & 0.7686 & 0.222851 \tabularnewline
17 & 0.098584 & 0.704 & 0.242308 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302660&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]-0.170199[/C][C]-1.2155[/C][C]0.114893[/C][/ROW]
[ROW][C]2[/C][C]0.131915[/C][C]0.9421[/C][C]0.175301[/C][/ROW]
[ROW][C]3[/C][C]-0.048957[/C][C]-0.3496[/C][C]0.364031[/C][/ROW]
[ROW][C]4[/C][C]-0.074218[/C][C]-0.53[/C][C]0.299199[/C][/ROW]
[ROW][C]5[/C][C]-0.145204[/C][C]-1.037[/C][C]0.152322[/C][/ROW]
[ROW][C]6[/C][C]0.015293[/C][C]0.1092[/C][C]0.45673[/C][/ROW]
[ROW][C]7[/C][C]0.124948[/C][C]0.8923[/C][C]0.188209[/C][/ROW]
[ROW][C]8[/C][C]-0.141372[/C][C]-1.0096[/C][C]0.158727[/C][/ROW]
[ROW][C]9[/C][C]0.057157[/C][C]0.4082[/C][C]0.342423[/C][/ROW]
[ROW][C]10[/C][C]0.102886[/C][C]0.7348[/C][C]0.232928[/C][/ROW]
[ROW][C]11[/C][C]-0.019759[/C][C]-0.1411[/C][C]0.44417[/C][/ROW]
[ROW][C]12[/C][C]-0.03579[/C][C]-0.2556[/C][C]0.399648[/C][/ROW]
[ROW][C]13[/C][C]0.007802[/C][C]0.0557[/C][C]0.477892[/C][/ROW]
[ROW][C]14[/C][C]-0.083952[/C][C]-0.5995[/C][C]0.275735[/C][/ROW]
[ROW][C]15[/C][C]-0.071606[/C][C]-0.5114[/C][C]0.305649[/C][/ROW]
[ROW][C]16[/C][C]0.107619[/C][C]0.7686[/C][C]0.222851[/C][/ROW]
[ROW][C]17[/C][C]0.098584[/C][C]0.704[/C][C]0.242308[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302660&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302660&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
1-0.170199-1.21550.114893
20.1319150.94210.175301
3-0.048957-0.34960.364031
4-0.074218-0.530.299199
5-0.145204-1.0370.152322
60.0152930.10920.45673
70.1249480.89230.188209
8-0.141372-1.00960.158727
90.0571570.40820.342423
100.1028860.73480.232928
11-0.019759-0.14110.44417
12-0.03579-0.25560.399648
130.0078020.05570.477892
14-0.083952-0.59950.275735
15-0.071606-0.51140.305649
160.1076190.76860.222851
170.0985840.7040.242308







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.170199-1.21550.114893
20.1060190.75710.22623
3-0.011291-0.08060.468023
4-0.101343-0.72370.236268
5-0.173249-1.23720.110831
6-0.01533-0.10950.456627
70.1706371.21860.114302
8-0.12491-0.8920.188281
9-0.062789-0.44840.327882
100.1414171.00990.15865
110.0523880.37410.354932
12-0.067397-0.48130.316177
13-0.061034-0.43590.332386
14-0.058397-0.4170.339201
15-0.009067-0.06470.474314
160.0870430.62160.268483
170.0977370.6980.244179

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.170199 & -1.2155 & 0.114893 \tabularnewline
2 & 0.106019 & 0.7571 & 0.22623 \tabularnewline
3 & -0.011291 & -0.0806 & 0.468023 \tabularnewline
4 & -0.101343 & -0.7237 & 0.236268 \tabularnewline
5 & -0.173249 & -1.2372 & 0.110831 \tabularnewline
6 & -0.01533 & -0.1095 & 0.456627 \tabularnewline
7 & 0.170637 & 1.2186 & 0.114302 \tabularnewline
8 & -0.12491 & -0.892 & 0.188281 \tabularnewline
9 & -0.062789 & -0.4484 & 0.327882 \tabularnewline
10 & 0.141417 & 1.0099 & 0.15865 \tabularnewline
11 & 0.052388 & 0.3741 & 0.354932 \tabularnewline
12 & -0.067397 & -0.4813 & 0.316177 \tabularnewline
13 & -0.061034 & -0.4359 & 0.332386 \tabularnewline
14 & -0.058397 & -0.417 & 0.339201 \tabularnewline
15 & -0.009067 & -0.0647 & 0.474314 \tabularnewline
16 & 0.087043 & 0.6216 & 0.268483 \tabularnewline
17 & 0.097737 & 0.698 & 0.244179 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302660&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]-0.170199[/C][C]-1.2155[/C][C]0.114893[/C][/ROW]
[ROW][C]2[/C][C]0.106019[/C][C]0.7571[/C][C]0.22623[/C][/ROW]
[ROW][C]3[/C][C]-0.011291[/C][C]-0.0806[/C][C]0.468023[/C][/ROW]
[ROW][C]4[/C][C]-0.101343[/C][C]-0.7237[/C][C]0.236268[/C][/ROW]
[ROW][C]5[/C][C]-0.173249[/C][C]-1.2372[/C][C]0.110831[/C][/ROW]
[ROW][C]6[/C][C]-0.01533[/C][C]-0.1095[/C][C]0.456627[/C][/ROW]
[ROW][C]7[/C][C]0.170637[/C][C]1.2186[/C][C]0.114302[/C][/ROW]
[ROW][C]8[/C][C]-0.12491[/C][C]-0.892[/C][C]0.188281[/C][/ROW]
[ROW][C]9[/C][C]-0.062789[/C][C]-0.4484[/C][C]0.327882[/C][/ROW]
[ROW][C]10[/C][C]0.141417[/C][C]1.0099[/C][C]0.15865[/C][/ROW]
[ROW][C]11[/C][C]0.052388[/C][C]0.3741[/C][C]0.354932[/C][/ROW]
[ROW][C]12[/C][C]-0.067397[/C][C]-0.4813[/C][C]0.316177[/C][/ROW]
[ROW][C]13[/C][C]-0.061034[/C][C]-0.4359[/C][C]0.332386[/C][/ROW]
[ROW][C]14[/C][C]-0.058397[/C][C]-0.417[/C][C]0.339201[/C][/ROW]
[ROW][C]15[/C][C]-0.009067[/C][C]-0.0647[/C][C]0.474314[/C][/ROW]
[ROW][C]16[/C][C]0.087043[/C][C]0.6216[/C][C]0.268483[/C][/ROW]
[ROW][C]17[/C][C]0.097737[/C][C]0.698[/C][C]0.244179[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302660&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302660&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
1-0.170199-1.21550.114893
20.1060190.75710.22623
3-0.011291-0.08060.468023
4-0.101343-0.72370.236268
5-0.173249-1.23720.110831
6-0.01533-0.10950.456627
70.1706371.21860.114302
8-0.12491-0.8920.188281
9-0.062789-0.44840.327882
100.1414171.00990.15865
110.0523880.37410.354932
12-0.067397-0.48130.316177
13-0.061034-0.43590.332386
14-0.058397-0.4170.339201
15-0.009067-0.06470.474314
160.0870430.62160.268483
170.0977370.6980.244179



Parameters (Session):
par1 = 12 ; par2 = -0.3 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ; par10 = FALSE ;
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)
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')