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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, 23 Dec 2016 10:57:02 +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/23/t1482487077u7m9qzyom4kw64s.htm/, Retrieved Tue, 07 May 2024 05:49:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=302829, Retrieved Tue, 07 May 2024 05:49:13 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelation f...] [2016-12-23 09:57:02] [bd7223969ac5b08f41438741a34686d6] [Current]
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Dataseries X:
99
102
100
98
98
99
100
99
100
99
101
104
100
101
99
100
102
99
99
100
99
105
100
101
100
101
99
100
100
100
100
101
101
100
99
101
101
101
100
100
100
101
98
99
100
101
100
100
99
100
99
101
98
100
99
103
105
100
101
100
99
100
99
105
99
102
100
100
99
102
99
101
100
100
99
101
100
100
98
99
99
98
105
98
100
101
101
100
101
102
100
100
99
102
102
98
100
101
98
99
99
101
100
99
99
101
99




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=302829&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=302829&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302829&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
1-0.110017-1.1380.128826
20.0442890.45810.323896
3-0.084472-0.87380.192096
4-0.003808-0.03940.484327
50.0023220.0240.490443
6-0.047749-0.49390.311189
7-0.041561-0.42990.334063
80.0455480.47120.319245
9-0.072468-0.74960.227566
100.0903330.93440.176099
11-0.031487-0.32570.372641
120.0198010.20480.419049
13-0.154522-1.59840.056452
14-0.008433-0.08720.465327
15-0.048212-0.49870.309504
16-0.062571-0.64720.259432
17-0.056914-0.58870.278645
18-0.116457-1.20460.1155
190.1354061.40070.082105
200.091630.94780.172676

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.110017 & -1.138 & 0.128826 \tabularnewline
2 & 0.044289 & 0.4581 & 0.323896 \tabularnewline
3 & -0.084472 & -0.8738 & 0.192096 \tabularnewline
4 & -0.003808 & -0.0394 & 0.484327 \tabularnewline
5 & 0.002322 & 0.024 & 0.490443 \tabularnewline
6 & -0.047749 & -0.4939 & 0.311189 \tabularnewline
7 & -0.041561 & -0.4299 & 0.334063 \tabularnewline
8 & 0.045548 & 0.4712 & 0.319245 \tabularnewline
9 & -0.072468 & -0.7496 & 0.227566 \tabularnewline
10 & 0.090333 & 0.9344 & 0.176099 \tabularnewline
11 & -0.031487 & -0.3257 & 0.372641 \tabularnewline
12 & 0.019801 & 0.2048 & 0.419049 \tabularnewline
13 & -0.154522 & -1.5984 & 0.056452 \tabularnewline
14 & -0.008433 & -0.0872 & 0.465327 \tabularnewline
15 & -0.048212 & -0.4987 & 0.309504 \tabularnewline
16 & -0.062571 & -0.6472 & 0.259432 \tabularnewline
17 & -0.056914 & -0.5887 & 0.278645 \tabularnewline
18 & -0.116457 & -1.2046 & 0.1155 \tabularnewline
19 & 0.135406 & 1.4007 & 0.082105 \tabularnewline
20 & 0.09163 & 0.9478 & 0.172676 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302829&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]-0.110017[/C][C]-1.138[/C][C]0.128826[/C][/ROW]
[ROW][C]2[/C][C]0.044289[/C][C]0.4581[/C][C]0.323896[/C][/ROW]
[ROW][C]3[/C][C]-0.084472[/C][C]-0.8738[/C][C]0.192096[/C][/ROW]
[ROW][C]4[/C][C]-0.003808[/C][C]-0.0394[/C][C]0.484327[/C][/ROW]
[ROW][C]5[/C][C]0.002322[/C][C]0.024[/C][C]0.490443[/C][/ROW]
[ROW][C]6[/C][C]-0.047749[/C][C]-0.4939[/C][C]0.311189[/C][/ROW]
[ROW][C]7[/C][C]-0.041561[/C][C]-0.4299[/C][C]0.334063[/C][/ROW]
[ROW][C]8[/C][C]0.045548[/C][C]0.4712[/C][C]0.319245[/C][/ROW]
[ROW][C]9[/C][C]-0.072468[/C][C]-0.7496[/C][C]0.227566[/C][/ROW]
[ROW][C]10[/C][C]0.090333[/C][C]0.9344[/C][C]0.176099[/C][/ROW]
[ROW][C]11[/C][C]-0.031487[/C][C]-0.3257[/C][C]0.372641[/C][/ROW]
[ROW][C]12[/C][C]0.019801[/C][C]0.2048[/C][C]0.419049[/C][/ROW]
[ROW][C]13[/C][C]-0.154522[/C][C]-1.5984[/C][C]0.056452[/C][/ROW]
[ROW][C]14[/C][C]-0.008433[/C][C]-0.0872[/C][C]0.465327[/C][/ROW]
[ROW][C]15[/C][C]-0.048212[/C][C]-0.4987[/C][C]0.309504[/C][/ROW]
[ROW][C]16[/C][C]-0.062571[/C][C]-0.6472[/C][C]0.259432[/C][/ROW]
[ROW][C]17[/C][C]-0.056914[/C][C]-0.5887[/C][C]0.278645[/C][/ROW]
[ROW][C]18[/C][C]-0.116457[/C][C]-1.2046[/C][C]0.1155[/C][/ROW]
[ROW][C]19[/C][C]0.135406[/C][C]1.4007[/C][C]0.082105[/C][/ROW]
[ROW][C]20[/C][C]0.09163[/C][C]0.9478[/C][C]0.172676[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302829&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302829&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
1-0.110017-1.1380.128826
20.0442890.45810.323896
3-0.084472-0.87380.192096
4-0.003808-0.03940.484327
50.0023220.0240.490443
6-0.047749-0.49390.311189
7-0.041561-0.42990.334063
80.0455480.47120.319245
9-0.072468-0.74960.227566
100.0903330.93440.176099
11-0.031487-0.32570.372641
120.0198010.20480.419049
13-0.154522-1.59840.056452
14-0.008433-0.08720.465327
15-0.048212-0.49870.309504
16-0.062571-0.64720.259432
17-0.056914-0.58870.278645
18-0.116457-1.20460.1155
190.1354061.40070.082105
200.091630.94780.172676







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.110017-1.1380.128826
20.0325790.3370.368388
3-0.077189-0.79840.213189
4-0.022587-0.23360.407855
50.0051620.05340.478757
6-0.053642-0.55490.290069
7-0.055839-0.57760.282373
80.0398790.41250.340393
9-0.070881-0.73320.23252
100.0653460.67590.250266
11-0.005437-0.05620.477627
12-0.002212-0.02290.490895
13-0.150739-1.55930.060944
14-0.03876-0.40090.344633
15-0.052514-0.54320.294057
16-0.100788-1.04260.149752
17-0.076745-0.79390.214518
18-0.159614-1.65110.050829
190.0895770.92660.178113
200.0886990.91750.180469

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.110017 & -1.138 & 0.128826 \tabularnewline
2 & 0.032579 & 0.337 & 0.368388 \tabularnewline
3 & -0.077189 & -0.7984 & 0.213189 \tabularnewline
4 & -0.022587 & -0.2336 & 0.407855 \tabularnewline
5 & 0.005162 & 0.0534 & 0.478757 \tabularnewline
6 & -0.053642 & -0.5549 & 0.290069 \tabularnewline
7 & -0.055839 & -0.5776 & 0.282373 \tabularnewline
8 & 0.039879 & 0.4125 & 0.340393 \tabularnewline
9 & -0.070881 & -0.7332 & 0.23252 \tabularnewline
10 & 0.065346 & 0.6759 & 0.250266 \tabularnewline
11 & -0.005437 & -0.0562 & 0.477627 \tabularnewline
12 & -0.002212 & -0.0229 & 0.490895 \tabularnewline
13 & -0.150739 & -1.5593 & 0.060944 \tabularnewline
14 & -0.03876 & -0.4009 & 0.344633 \tabularnewline
15 & -0.052514 & -0.5432 & 0.294057 \tabularnewline
16 & -0.100788 & -1.0426 & 0.149752 \tabularnewline
17 & -0.076745 & -0.7939 & 0.214518 \tabularnewline
18 & -0.159614 & -1.6511 & 0.050829 \tabularnewline
19 & 0.089577 & 0.9266 & 0.178113 \tabularnewline
20 & 0.088699 & 0.9175 & 0.180469 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=302829&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]-0.110017[/C][C]-1.138[/C][C]0.128826[/C][/ROW]
[ROW][C]2[/C][C]0.032579[/C][C]0.337[/C][C]0.368388[/C][/ROW]
[ROW][C]3[/C][C]-0.077189[/C][C]-0.7984[/C][C]0.213189[/C][/ROW]
[ROW][C]4[/C][C]-0.022587[/C][C]-0.2336[/C][C]0.407855[/C][/ROW]
[ROW][C]5[/C][C]0.005162[/C][C]0.0534[/C][C]0.478757[/C][/ROW]
[ROW][C]6[/C][C]-0.053642[/C][C]-0.5549[/C][C]0.290069[/C][/ROW]
[ROW][C]7[/C][C]-0.055839[/C][C]-0.5776[/C][C]0.282373[/C][/ROW]
[ROW][C]8[/C][C]0.039879[/C][C]0.4125[/C][C]0.340393[/C][/ROW]
[ROW][C]9[/C][C]-0.070881[/C][C]-0.7332[/C][C]0.23252[/C][/ROW]
[ROW][C]10[/C][C]0.065346[/C][C]0.6759[/C][C]0.250266[/C][/ROW]
[ROW][C]11[/C][C]-0.005437[/C][C]-0.0562[/C][C]0.477627[/C][/ROW]
[ROW][C]12[/C][C]-0.002212[/C][C]-0.0229[/C][C]0.490895[/C][/ROW]
[ROW][C]13[/C][C]-0.150739[/C][C]-1.5593[/C][C]0.060944[/C][/ROW]
[ROW][C]14[/C][C]-0.03876[/C][C]-0.4009[/C][C]0.344633[/C][/ROW]
[ROW][C]15[/C][C]-0.052514[/C][C]-0.5432[/C][C]0.294057[/C][/ROW]
[ROW][C]16[/C][C]-0.100788[/C][C]-1.0426[/C][C]0.149752[/C][/ROW]
[ROW][C]17[/C][C]-0.076745[/C][C]-0.7939[/C][C]0.214518[/C][/ROW]
[ROW][C]18[/C][C]-0.159614[/C][C]-1.6511[/C][C]0.050829[/C][/ROW]
[ROW][C]19[/C][C]0.089577[/C][C]0.9266[/C][C]0.178113[/C][/ROW]
[ROW][C]20[/C][C]0.088699[/C][C]0.9175[/C][C]0.180469[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=302829&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=302829&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
1-0.110017-1.1380.128826
20.0325790.3370.368388
3-0.077189-0.79840.213189
4-0.022587-0.23360.407855
50.0051620.05340.478757
6-0.053642-0.55490.290069
7-0.055839-0.57760.282373
80.0398790.41250.340393
9-0.070881-0.73320.23252
100.0653460.67590.250266
11-0.005437-0.05620.477627
12-0.002212-0.02290.490895
13-0.150739-1.55930.060944
14-0.03876-0.40090.344633
15-0.052514-0.54320.294057
16-0.100788-1.04260.149752
17-0.076745-0.79390.214518
18-0.159614-1.65110.050829
190.0895770.92660.178113
200.0886990.91750.180469



Parameters (Session):
par1 = Default ; par2 = -1.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = -1.0 ; 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')