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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 computationTue, 08 Dec 2009 12:39:48 -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/08/t1260301261rrutmfanoz4h6do.htm/, Retrieved Sat, 27 Apr 2024 16:45:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64815, Retrieved Sat, 27 Apr 2024 16:45:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJSSHWWS9Rev6
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [WS 9 Arima backwa...] [2009-12-04 14:47:12] [2f17fb7f9ce5412e0690130b6ae01587]
- RMP   [(Partial) Autocorrelation Function] [review] [2009-12-08 19:25:53] [214e6e00abbde49700521a7ef1d30da2]
-   PD      [(Partial) Autocorrelation Function] [Review] [2009-12-08 19:39:48] [c8fd62404619100d8e91184019148412] [Current]
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Dataseries X:
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3
91
93.2
103.1
94.1
91.8
102.7
82.6




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=64815&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=64815&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64815&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
1-0.631799-4.33143.9e-05
20.0390680.26780.394999
30.3540862.42750.009544
4-0.320734-2.19880.016423
50.0726560.49810.310366
60.1662951.14010.130018
7-0.279062-1.91320.030916
80.2385151.63520.054346
9-0.13946-0.95610.171959
10-0.028579-0.19590.422756
110.1865451.27890.103607
12-0.217599-1.49180.071219
130.0872670.59830.276266
140.0355530.24370.404248
15-0.009644-0.06610.473783
16-0.092439-0.63370.264665
170.1289130.88380.190656

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.631799 & -4.3314 & 3.9e-05 \tabularnewline
2 & 0.039068 & 0.2678 & 0.394999 \tabularnewline
3 & 0.354086 & 2.4275 & 0.009544 \tabularnewline
4 & -0.320734 & -2.1988 & 0.016423 \tabularnewline
5 & 0.072656 & 0.4981 & 0.310366 \tabularnewline
6 & 0.166295 & 1.1401 & 0.130018 \tabularnewline
7 & -0.279062 & -1.9132 & 0.030916 \tabularnewline
8 & 0.238515 & 1.6352 & 0.054346 \tabularnewline
9 & -0.13946 & -0.9561 & 0.171959 \tabularnewline
10 & -0.028579 & -0.1959 & 0.422756 \tabularnewline
11 & 0.186545 & 1.2789 & 0.103607 \tabularnewline
12 & -0.217599 & -1.4918 & 0.071219 \tabularnewline
13 & 0.087267 & 0.5983 & 0.276266 \tabularnewline
14 & 0.035553 & 0.2437 & 0.404248 \tabularnewline
15 & -0.009644 & -0.0661 & 0.473783 \tabularnewline
16 & -0.092439 & -0.6337 & 0.264665 \tabularnewline
17 & 0.128913 & 0.8838 & 0.190656 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64815&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]-0.631799[/C][C]-4.3314[/C][C]3.9e-05[/C][/ROW]
[ROW][C]2[/C][C]0.039068[/C][C]0.2678[/C][C]0.394999[/C][/ROW]
[ROW][C]3[/C][C]0.354086[/C][C]2.4275[/C][C]0.009544[/C][/ROW]
[ROW][C]4[/C][C]-0.320734[/C][C]-2.1988[/C][C]0.016423[/C][/ROW]
[ROW][C]5[/C][C]0.072656[/C][C]0.4981[/C][C]0.310366[/C][/ROW]
[ROW][C]6[/C][C]0.166295[/C][C]1.1401[/C][C]0.130018[/C][/ROW]
[ROW][C]7[/C][C]-0.279062[/C][C]-1.9132[/C][C]0.030916[/C][/ROW]
[ROW][C]8[/C][C]0.238515[/C][C]1.6352[/C][C]0.054346[/C][/ROW]
[ROW][C]9[/C][C]-0.13946[/C][C]-0.9561[/C][C]0.171959[/C][/ROW]
[ROW][C]10[/C][C]-0.028579[/C][C]-0.1959[/C][C]0.422756[/C][/ROW]
[ROW][C]11[/C][C]0.186545[/C][C]1.2789[/C][C]0.103607[/C][/ROW]
[ROW][C]12[/C][C]-0.217599[/C][C]-1.4918[/C][C]0.071219[/C][/ROW]
[ROW][C]13[/C][C]0.087267[/C][C]0.5983[/C][C]0.276266[/C][/ROW]
[ROW][C]14[/C][C]0.035553[/C][C]0.2437[/C][C]0.404248[/C][/ROW]
[ROW][C]15[/C][C]-0.009644[/C][C]-0.0661[/C][C]0.473783[/C][/ROW]
[ROW][C]16[/C][C]-0.092439[/C][C]-0.6337[/C][C]0.264665[/C][/ROW]
[ROW][C]17[/C][C]0.128913[/C][C]0.8838[/C][C]0.190656[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64815&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64815&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
1-0.631799-4.33143.9e-05
20.0390680.26780.394999
30.3540862.42750.009544
4-0.320734-2.19880.016423
50.0726560.49810.310366
60.1662951.14010.130018
7-0.279062-1.91320.030916
80.2385151.63520.054346
9-0.13946-0.95610.171959
10-0.028579-0.19590.422756
110.1865451.27890.103607
12-0.217599-1.49180.071219
130.0872670.59830.276266
140.0355530.24370.404248
15-0.009644-0.06610.473783
16-0.092439-0.63370.264665
170.1289130.88380.190656







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.631799-4.33143.9e-05
2-0.599342-4.10897.9e-05
30.0386980.26530.39597
40.1955671.34070.093225
50.0748130.51290.305214
60.08770.60120.275284
7-0.158428-1.08610.141481
8-0.000779-0.00530.49788
9-0.126595-0.86790.194931
10-0.150284-1.03030.154073
110.0903920.61970.269226
120.0914070.62670.26696
130.023060.15810.43753
14-0.192093-1.31690.097125
150.1355330.92920.178776
16-0.001671-0.01150.495455
17-0.026549-0.1820.428178

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.631799 & -4.3314 & 3.9e-05 \tabularnewline
2 & -0.599342 & -4.1089 & 7.9e-05 \tabularnewline
3 & 0.038698 & 0.2653 & 0.39597 \tabularnewline
4 & 0.195567 & 1.3407 & 0.093225 \tabularnewline
5 & 0.074813 & 0.5129 & 0.305214 \tabularnewline
6 & 0.0877 & 0.6012 & 0.275284 \tabularnewline
7 & -0.158428 & -1.0861 & 0.141481 \tabularnewline
8 & -0.000779 & -0.0053 & 0.49788 \tabularnewline
9 & -0.126595 & -0.8679 & 0.194931 \tabularnewline
10 & -0.150284 & -1.0303 & 0.154073 \tabularnewline
11 & 0.090392 & 0.6197 & 0.269226 \tabularnewline
12 & 0.091407 & 0.6267 & 0.26696 \tabularnewline
13 & 0.02306 & 0.1581 & 0.43753 \tabularnewline
14 & -0.192093 & -1.3169 & 0.097125 \tabularnewline
15 & 0.135533 & 0.9292 & 0.178776 \tabularnewline
16 & -0.001671 & -0.0115 & 0.495455 \tabularnewline
17 & -0.026549 & -0.182 & 0.428178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64815&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]-0.631799[/C][C]-4.3314[/C][C]3.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.599342[/C][C]-4.1089[/C][C]7.9e-05[/C][/ROW]
[ROW][C]3[/C][C]0.038698[/C][C]0.2653[/C][C]0.39597[/C][/ROW]
[ROW][C]4[/C][C]0.195567[/C][C]1.3407[/C][C]0.093225[/C][/ROW]
[ROW][C]5[/C][C]0.074813[/C][C]0.5129[/C][C]0.305214[/C][/ROW]
[ROW][C]6[/C][C]0.0877[/C][C]0.6012[/C][C]0.275284[/C][/ROW]
[ROW][C]7[/C][C]-0.158428[/C][C]-1.0861[/C][C]0.141481[/C][/ROW]
[ROW][C]8[/C][C]-0.000779[/C][C]-0.0053[/C][C]0.49788[/C][/ROW]
[ROW][C]9[/C][C]-0.126595[/C][C]-0.8679[/C][C]0.194931[/C][/ROW]
[ROW][C]10[/C][C]-0.150284[/C][C]-1.0303[/C][C]0.154073[/C][/ROW]
[ROW][C]11[/C][C]0.090392[/C][C]0.6197[/C][C]0.269226[/C][/ROW]
[ROW][C]12[/C][C]0.091407[/C][C]0.6267[/C][C]0.26696[/C][/ROW]
[ROW][C]13[/C][C]0.02306[/C][C]0.1581[/C][C]0.43753[/C][/ROW]
[ROW][C]14[/C][C]-0.192093[/C][C]-1.3169[/C][C]0.097125[/C][/ROW]
[ROW][C]15[/C][C]0.135533[/C][C]0.9292[/C][C]0.178776[/C][/ROW]
[ROW][C]16[/C][C]-0.001671[/C][C]-0.0115[/C][C]0.495455[/C][/ROW]
[ROW][C]17[/C][C]-0.026549[/C][C]-0.182[/C][C]0.428178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64815&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64815&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
1-0.631799-4.33143.9e-05
2-0.599342-4.10897.9e-05
30.0386980.26530.39597
40.1955671.34070.093225
50.0748130.51290.305214
60.08770.60120.275284
7-0.158428-1.08610.141481
8-0.000779-0.00530.49788
9-0.126595-0.86790.194931
10-0.150284-1.03030.154073
110.0903920.61970.269226
120.0914070.62670.26696
130.023060.15810.43753
14-0.192093-1.31690.097125
150.1355330.92920.178776
16-0.001671-0.01150.495455
17-0.026549-0.1820.428178



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; 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')