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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 09 Dec 2008 03:52:15 -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/2008/Dec/09/t122881995767tnzraz19irydg.htm/, Retrieved Sun, 19 May 2024 12:04:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31279, Retrieved Sun, 19 May 2024 12:04:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Spectral Analysis] [Diff Spectral] [2008-12-06 12:07:42] [74be16979710d4c4e7c6647856088456]
F RMP   [ARIMA Backward Selection] [Arima backward] [2008-12-06 14:19:09] [74be16979710d4c4e7c6647856088456]
- RMPD      [(Partial) Autocorrelation Function] [] [2008-12-09 10:52:15] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD        [(Partial) Autocorrelation Function] [] [2008-12-09 10:56:43] [74be16979710d4c4e7c6647856088456]
- RMPD        [Spectral Analysis] [] [2008-12-09 11:01:22] [74be16979710d4c4e7c6647856088456]
F   P           [Spectral Analysis] [] [2008-12-09 11:05:55] [74be16979710d4c4e7c6647856088456]
F RMP           [ARIMA Backward Selection] [] [2008-12-09 11:11:19] [74be16979710d4c4e7c6647856088456]
F   PD        [(Partial) Autocorrelation Function] [] [2008-12-09 11:16:28] [74be16979710d4c4e7c6647856088456]
F   PD        [(Partial) Autocorrelation Function] [] [2008-12-09 11:18:29] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
5,1
4,9
5,2
5,1
4,6
3,7
3,9
3,1
2,8
2,6
2,2
1,8
1,3
1,2
1,4
1,3
1,3
1,9
1,9
2,1
2,0
1,9
1,9
1,9
1,8
1,7
1,6
1,7
1,9
1,7
1,3
2,0
2,0
2,3
2,0
1,7
2,3
2,4
2,4
2,3
2,1
2,1
2,5
2,0
1,8
1,7
1,9
2,1
1,4
1,6
1,7
1,6
1,9
1,6
1,1
1,3
1,6
1,6
1,7
1,6
1,7
1,6
1,5
1,6
1,1
1,5
1,4
1,3
0,9
1,2
0,9
1,1
1,3
1,3
1,4
1,2
1,7
2,0
3,0
3,1
3,2
2,7
2,8
3,0
2,8
3,1
3,1
3,2
3,1
2,7
2,2
2,2
2,1
2,3
2,5
2,3
2,6




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=31279&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=31279&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31279&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
10.8451698.3240
20.7474517.36150
30.635776.26160
40.5348435.26760
50.4317954.25272.4e-05
60.32043.15560.001067
70.1952611.92310.0287
80.0918210.90430.184029
90.0282740.27850.390622
10-0.050345-0.49580.310564
11-0.103938-1.02370.154268
12-0.17397-1.71340.044916
13-0.121806-1.19970.116598
14-0.083764-0.8250.205704
15-0.099465-0.97960.164856
16-0.084211-0.82940.204462
17-0.098185-0.9670.167971
18-0.106677-1.05060.148015
19-0.104677-1.03090.152564

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.845169 & 8.324 & 0 \tabularnewline
2 & 0.747451 & 7.3615 & 0 \tabularnewline
3 & 0.63577 & 6.2616 & 0 \tabularnewline
4 & 0.534843 & 5.2676 & 0 \tabularnewline
5 & 0.431795 & 4.2527 & 2.4e-05 \tabularnewline
6 & 0.3204 & 3.1556 & 0.001067 \tabularnewline
7 & 0.195261 & 1.9231 & 0.0287 \tabularnewline
8 & 0.091821 & 0.9043 & 0.184029 \tabularnewline
9 & 0.028274 & 0.2785 & 0.390622 \tabularnewline
10 & -0.050345 & -0.4958 & 0.310564 \tabularnewline
11 & -0.103938 & -1.0237 & 0.154268 \tabularnewline
12 & -0.17397 & -1.7134 & 0.044916 \tabularnewline
13 & -0.121806 & -1.1997 & 0.116598 \tabularnewline
14 & -0.083764 & -0.825 & 0.205704 \tabularnewline
15 & -0.099465 & -0.9796 & 0.164856 \tabularnewline
16 & -0.084211 & -0.8294 & 0.204462 \tabularnewline
17 & -0.098185 & -0.967 & 0.167971 \tabularnewline
18 & -0.106677 & -1.0506 & 0.148015 \tabularnewline
19 & -0.104677 & -1.0309 & 0.152564 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31279&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]0.845169[/C][C]8.324[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.747451[/C][C]7.3615[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.63577[/C][C]6.2616[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.534843[/C][C]5.2676[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.431795[/C][C]4.2527[/C][C]2.4e-05[/C][/ROW]
[ROW][C]6[/C][C]0.3204[/C][C]3.1556[/C][C]0.001067[/C][/ROW]
[ROW][C]7[/C][C]0.195261[/C][C]1.9231[/C][C]0.0287[/C][/ROW]
[ROW][C]8[/C][C]0.091821[/C][C]0.9043[/C][C]0.184029[/C][/ROW]
[ROW][C]9[/C][C]0.028274[/C][C]0.2785[/C][C]0.390622[/C][/ROW]
[ROW][C]10[/C][C]-0.050345[/C][C]-0.4958[/C][C]0.310564[/C][/ROW]
[ROW][C]11[/C][C]-0.103938[/C][C]-1.0237[/C][C]0.154268[/C][/ROW]
[ROW][C]12[/C][C]-0.17397[/C][C]-1.7134[/C][C]0.044916[/C][/ROW]
[ROW][C]13[/C][C]-0.121806[/C][C]-1.1997[/C][C]0.116598[/C][/ROW]
[ROW][C]14[/C][C]-0.083764[/C][C]-0.825[/C][C]0.205704[/C][/ROW]
[ROW][C]15[/C][C]-0.099465[/C][C]-0.9796[/C][C]0.164856[/C][/ROW]
[ROW][C]16[/C][C]-0.084211[/C][C]-0.8294[/C][C]0.204462[/C][/ROW]
[ROW][C]17[/C][C]-0.098185[/C][C]-0.967[/C][C]0.167971[/C][/ROW]
[ROW][C]18[/C][C]-0.106677[/C][C]-1.0506[/C][C]0.148015[/C][/ROW]
[ROW][C]19[/C][C]-0.104677[/C][C]-1.0309[/C][C]0.152564[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31279&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31279&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
10.8451698.3240
20.7474517.36150
30.635776.26160
40.5348435.26760
50.4317954.25272.4e-05
60.32043.15560.001067
70.1952611.92310.0287
80.0918210.90430.184029
90.0282740.27850.390622
10-0.050345-0.49580.310564
11-0.103938-1.02370.154268
12-0.17397-1.71340.044916
13-0.121806-1.19970.116598
14-0.083764-0.8250.205704
15-0.099465-0.97960.164856
16-0.084211-0.82940.204462
17-0.098185-0.9670.167971
18-0.106677-1.05060.148015
19-0.104677-1.03090.152564







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8451698.3240
20.1160011.14250.128033
3-0.07349-0.72380.235467
4-0.039998-0.39390.347247
5-0.06306-0.62110.268005
6-0.104175-1.0260.153721
7-0.143417-1.41250.080502
8-0.041019-0.4040.343555
90.073990.72870.233965
10-0.081495-0.80260.212075
11-0.007901-0.07780.469069
12-0.096694-0.95230.171649
130.3474063.42160.000456
140.0737610.72650.234654
15-0.271929-2.67820.004347
160.0350270.3450.365431
17-0.071827-0.70740.240502
18-0.103994-1.02420.154139
19-0.057211-0.56350.28721

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.845169 & 8.324 & 0 \tabularnewline
2 & 0.116001 & 1.1425 & 0.128033 \tabularnewline
3 & -0.07349 & -0.7238 & 0.235467 \tabularnewline
4 & -0.039998 & -0.3939 & 0.347247 \tabularnewline
5 & -0.06306 & -0.6211 & 0.268005 \tabularnewline
6 & -0.104175 & -1.026 & 0.153721 \tabularnewline
7 & -0.143417 & -1.4125 & 0.080502 \tabularnewline
8 & -0.041019 & -0.404 & 0.343555 \tabularnewline
9 & 0.07399 & 0.7287 & 0.233965 \tabularnewline
10 & -0.081495 & -0.8026 & 0.212075 \tabularnewline
11 & -0.007901 & -0.0778 & 0.469069 \tabularnewline
12 & -0.096694 & -0.9523 & 0.171649 \tabularnewline
13 & 0.347406 & 3.4216 & 0.000456 \tabularnewline
14 & 0.073761 & 0.7265 & 0.234654 \tabularnewline
15 & -0.271929 & -2.6782 & 0.004347 \tabularnewline
16 & 0.035027 & 0.345 & 0.365431 \tabularnewline
17 & -0.071827 & -0.7074 & 0.240502 \tabularnewline
18 & -0.103994 & -1.0242 & 0.154139 \tabularnewline
19 & -0.057211 & -0.5635 & 0.28721 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31279&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]0.845169[/C][C]8.324[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.116001[/C][C]1.1425[/C][C]0.128033[/C][/ROW]
[ROW][C]3[/C][C]-0.07349[/C][C]-0.7238[/C][C]0.235467[/C][/ROW]
[ROW][C]4[/C][C]-0.039998[/C][C]-0.3939[/C][C]0.347247[/C][/ROW]
[ROW][C]5[/C][C]-0.06306[/C][C]-0.6211[/C][C]0.268005[/C][/ROW]
[ROW][C]6[/C][C]-0.104175[/C][C]-1.026[/C][C]0.153721[/C][/ROW]
[ROW][C]7[/C][C]-0.143417[/C][C]-1.4125[/C][C]0.080502[/C][/ROW]
[ROW][C]8[/C][C]-0.041019[/C][C]-0.404[/C][C]0.343555[/C][/ROW]
[ROW][C]9[/C][C]0.07399[/C][C]0.7287[/C][C]0.233965[/C][/ROW]
[ROW][C]10[/C][C]-0.081495[/C][C]-0.8026[/C][C]0.212075[/C][/ROW]
[ROW][C]11[/C][C]-0.007901[/C][C]-0.0778[/C][C]0.469069[/C][/ROW]
[ROW][C]12[/C][C]-0.096694[/C][C]-0.9523[/C][C]0.171649[/C][/ROW]
[ROW][C]13[/C][C]0.347406[/C][C]3.4216[/C][C]0.000456[/C][/ROW]
[ROW][C]14[/C][C]0.073761[/C][C]0.7265[/C][C]0.234654[/C][/ROW]
[ROW][C]15[/C][C]-0.271929[/C][C]-2.6782[/C][C]0.004347[/C][/ROW]
[ROW][C]16[/C][C]0.035027[/C][C]0.345[/C][C]0.365431[/C][/ROW]
[ROW][C]17[/C][C]-0.071827[/C][C]-0.7074[/C][C]0.240502[/C][/ROW]
[ROW][C]18[/C][C]-0.103994[/C][C]-1.0242[/C][C]0.154139[/C][/ROW]
[ROW][C]19[/C][C]-0.057211[/C][C]-0.5635[/C][C]0.28721[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31279&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31279&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
10.8451698.3240
20.1160011.14250.128033
3-0.07349-0.72380.235467
4-0.039998-0.39390.347247
5-0.06306-0.62110.268005
6-0.104175-1.0260.153721
7-0.143417-1.41250.080502
8-0.041019-0.4040.343555
90.073990.72870.233965
10-0.081495-0.80260.212075
11-0.007901-0.07780.469069
12-0.096694-0.95230.171649
130.3474063.42160.000456
140.0737610.72650.234654
15-0.271929-2.67820.004347
160.0350270.3450.365431
17-0.071827-0.70740.240502
18-0.103994-1.02420.154139
19-0.057211-0.56350.28721



Parameters (Session):
par1 = Default ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = -0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')