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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, 04 Dec 2009 08:15:19 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t1259939756b13zt5jju1pvifl.htm/, Retrieved Sun, 28 Apr 2024 17:31:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63738, Retrieved Sun, 28 Apr 2024 17:31:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:19:56] [b98453cac15ba1066b407e146608df68]
-    D        [(Partial) Autocorrelation Function] [] [2009-11-23 15:21:31] [5d885a68c2332cc44f6191ec94766bfa]
- R PD            [(Partial) Autocorrelation Function] [AutoCF d=0,D=1] [2009-12-04 15:15:19] [18c0746232b29e9668aa6bedcb8dd698] [Current]
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Dataseries X:
12.6
15.7
13.2
20.3
12.8
8
0.9
3.6
14.1
21.7
24.5
18.9
13.9
11
5.8
15.5
22.4
31.7
30.3
31.4
20.2
19.7
10.8
13.2
15.1
15.6
15.5
12.7
10.9
10
9.1
10.3
16.9
22
27.6
28.9
31
32.9
38.1
28.8
29
21.8
28.8
25.6
28.2
20.2
17.9
16.3
13.2
8.1
4.5
-0.1
0
2.3
2.8
2.9
0.1
3.5
8.6
13.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63738&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63738&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63738&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8823936.11340
20.6921144.79518e-06
30.4413983.05810.001818
40.283791.96620.027539
50.1807471.25230.108273
60.1312670.90940.18383
70.065020.45050.3272
8-0.029151-0.2020.420398
9-0.163522-1.13290.131439
10-0.319137-2.2110.015915
11-0.445069-3.08350.001693
12-0.51712-3.58270.000396
13-0.485822-3.36590.000754
14-0.393309-2.72490.004474
15-0.260426-1.80430.038732
16-0.14468-1.00240.160595
17-0.044025-0.3050.380837

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.882393 & 6.1134 & 0 \tabularnewline
2 & 0.692114 & 4.7951 & 8e-06 \tabularnewline
3 & 0.441398 & 3.0581 & 0.001818 \tabularnewline
4 & 0.28379 & 1.9662 & 0.027539 \tabularnewline
5 & 0.180747 & 1.2523 & 0.108273 \tabularnewline
6 & 0.131267 & 0.9094 & 0.18383 \tabularnewline
7 & 0.06502 & 0.4505 & 0.3272 \tabularnewline
8 & -0.029151 & -0.202 & 0.420398 \tabularnewline
9 & -0.163522 & -1.1329 & 0.131439 \tabularnewline
10 & -0.319137 & -2.211 & 0.015915 \tabularnewline
11 & -0.445069 & -3.0835 & 0.001693 \tabularnewline
12 & -0.51712 & -3.5827 & 0.000396 \tabularnewline
13 & -0.485822 & -3.3659 & 0.000754 \tabularnewline
14 & -0.393309 & -2.7249 & 0.004474 \tabularnewline
15 & -0.260426 & -1.8043 & 0.038732 \tabularnewline
16 & -0.14468 & -1.0024 & 0.160595 \tabularnewline
17 & -0.044025 & -0.305 & 0.380837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63738&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]0.882393[/C][C]6.1134[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.692114[/C][C]4.7951[/C][C]8e-06[/C][/ROW]
[ROW][C]3[/C][C]0.441398[/C][C]3.0581[/C][C]0.001818[/C][/ROW]
[ROW][C]4[/C][C]0.28379[/C][C]1.9662[/C][C]0.027539[/C][/ROW]
[ROW][C]5[/C][C]0.180747[/C][C]1.2523[/C][C]0.108273[/C][/ROW]
[ROW][C]6[/C][C]0.131267[/C][C]0.9094[/C][C]0.18383[/C][/ROW]
[ROW][C]7[/C][C]0.06502[/C][C]0.4505[/C][C]0.3272[/C][/ROW]
[ROW][C]8[/C][C]-0.029151[/C][C]-0.202[/C][C]0.420398[/C][/ROW]
[ROW][C]9[/C][C]-0.163522[/C][C]-1.1329[/C][C]0.131439[/C][/ROW]
[ROW][C]10[/C][C]-0.319137[/C][C]-2.211[/C][C]0.015915[/C][/ROW]
[ROW][C]11[/C][C]-0.445069[/C][C]-3.0835[/C][C]0.001693[/C][/ROW]
[ROW][C]12[/C][C]-0.51712[/C][C]-3.5827[/C][C]0.000396[/C][/ROW]
[ROW][C]13[/C][C]-0.485822[/C][C]-3.3659[/C][C]0.000754[/C][/ROW]
[ROW][C]14[/C][C]-0.393309[/C][C]-2.7249[/C][C]0.004474[/C][/ROW]
[ROW][C]15[/C][C]-0.260426[/C][C]-1.8043[/C][C]0.038732[/C][/ROW]
[ROW][C]16[/C][C]-0.14468[/C][C]-1.0024[/C][C]0.160595[/C][/ROW]
[ROW][C]17[/C][C]-0.044025[/C][C]-0.305[/C][C]0.380837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63738&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63738&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
10.8823936.11340
20.6921144.79518e-06
30.4413983.05810.001818
40.283791.96620.027539
50.1807471.25230.108273
60.1312670.90940.18383
70.065020.45050.3272
8-0.029151-0.2020.420398
9-0.163522-1.13290.131439
10-0.319137-2.2110.015915
11-0.445069-3.08350.001693
12-0.51712-3.58270.000396
13-0.485822-3.36590.000754
14-0.393309-2.72490.004474
15-0.260426-1.80430.038732
16-0.14468-1.00240.160595
17-0.044025-0.3050.380837







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8823936.11340
2-0.390739-2.70710.004686
3-0.336725-2.33290.011946
40.4915653.40570.000671
5-0.080464-0.55750.289898
6-0.323928-2.24420.014732
7-0.011186-0.07750.469274
8-0.069624-0.48240.315868
9-0.255056-1.76710.041786
10-0.249474-1.72840.045172
110.1522031.05450.148469
120.0196740.13630.446074
130.091660.6350.264209
140.0649370.44990.327405
150.0023720.01640.493478
160.1596081.10580.137162
170.1554881.07730.143376

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.882393 & 6.1134 & 0 \tabularnewline
2 & -0.390739 & -2.7071 & 0.004686 \tabularnewline
3 & -0.336725 & -2.3329 & 0.011946 \tabularnewline
4 & 0.491565 & 3.4057 & 0.000671 \tabularnewline
5 & -0.080464 & -0.5575 & 0.289898 \tabularnewline
6 & -0.323928 & -2.2442 & 0.014732 \tabularnewline
7 & -0.011186 & -0.0775 & 0.469274 \tabularnewline
8 & -0.069624 & -0.4824 & 0.315868 \tabularnewline
9 & -0.255056 & -1.7671 & 0.041786 \tabularnewline
10 & -0.249474 & -1.7284 & 0.045172 \tabularnewline
11 & 0.152203 & 1.0545 & 0.148469 \tabularnewline
12 & 0.019674 & 0.1363 & 0.446074 \tabularnewline
13 & 0.09166 & 0.635 & 0.264209 \tabularnewline
14 & 0.064937 & 0.4499 & 0.327405 \tabularnewline
15 & 0.002372 & 0.0164 & 0.493478 \tabularnewline
16 & 0.159608 & 1.1058 & 0.137162 \tabularnewline
17 & 0.155488 & 1.0773 & 0.143376 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63738&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]0.882393[/C][C]6.1134[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.390739[/C][C]-2.7071[/C][C]0.004686[/C][/ROW]
[ROW][C]3[/C][C]-0.336725[/C][C]-2.3329[/C][C]0.011946[/C][/ROW]
[ROW][C]4[/C][C]0.491565[/C][C]3.4057[/C][C]0.000671[/C][/ROW]
[ROW][C]5[/C][C]-0.080464[/C][C]-0.5575[/C][C]0.289898[/C][/ROW]
[ROW][C]6[/C][C]-0.323928[/C][C]-2.2442[/C][C]0.014732[/C][/ROW]
[ROW][C]7[/C][C]-0.011186[/C][C]-0.0775[/C][C]0.469274[/C][/ROW]
[ROW][C]8[/C][C]-0.069624[/C][C]-0.4824[/C][C]0.315868[/C][/ROW]
[ROW][C]9[/C][C]-0.255056[/C][C]-1.7671[/C][C]0.041786[/C][/ROW]
[ROW][C]10[/C][C]-0.249474[/C][C]-1.7284[/C][C]0.045172[/C][/ROW]
[ROW][C]11[/C][C]0.152203[/C][C]1.0545[/C][C]0.148469[/C][/ROW]
[ROW][C]12[/C][C]0.019674[/C][C]0.1363[/C][C]0.446074[/C][/ROW]
[ROW][C]13[/C][C]0.09166[/C][C]0.635[/C][C]0.264209[/C][/ROW]
[ROW][C]14[/C][C]0.064937[/C][C]0.4499[/C][C]0.327405[/C][/ROW]
[ROW][C]15[/C][C]0.002372[/C][C]0.0164[/C][C]0.493478[/C][/ROW]
[ROW][C]16[/C][C]0.159608[/C][C]1.1058[/C][C]0.137162[/C][/ROW]
[ROW][C]17[/C][C]0.155488[/C][C]1.0773[/C][C]0.143376[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63738&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63738&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
10.8823936.11340
2-0.390739-2.70710.004686
3-0.336725-2.33290.011946
40.4915653.40570.000671
5-0.080464-0.55750.289898
6-0.323928-2.24420.014732
7-0.011186-0.07750.469274
8-0.069624-0.48240.315868
9-0.255056-1.76710.041786
10-0.249474-1.72840.045172
110.1522031.05450.148469
120.0196740.13630.446074
130.091660.6350.264209
140.0649370.44990.327405
150.0023720.01640.493478
160.1596081.10580.137162
170.1554881.07730.143376



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')