FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

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 computationMon, 06 Dec 2010 17:46:41 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/06/t12916576258zi69g2sdbdun08.htm/, Retrieved Mon, 29 Apr 2024 00:54:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=105732, Retrieved Mon, 29 Apr 2024 00:54:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-06 17:46:41] [4dba6678eac10ee5c3460d144a14bd5c] [Current]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-06 17:51:47] [7f2363d2c77d3bf71367965cc53be730]
-   P           [(Partial) Autocorrelation Function] [] [2010-12-06 17:55:23] [7f2363d2c77d3bf71367965cc53be730]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5.81    
5.76
5.99    
6.12    
6.03    
6.25    
5.80    
5.67    
5.89    
5.91    
5.86    
6.07    
6.27    
6.68    
6.77    
6.71    
6.62
6.50
5.89
6.05
6.43
6.47
6.62
6.77
6.70
6.95
6.73
7.07
7.28
7.32
6.76
6.93
6.99
7.16
7.28
7.08
7.34
7.87
6.28
6.30
6.36
6.28
5.89
6.04
5.96
6.10
6.26
6.02
6.25
6.41
6.22
6.57
6.18
6.26
6.10
6.02
6.06
6.35
6.21
6.48
6.74
6.53
6.80
6.75
6.56
6.66
6.18
6.40
6.43
6.54
6.44
6.64
6.82
6.97
7.00
6.91
6.74
6.98
6.37
6.56
6.63
6.87
6.68
6.75
6.84
7.15
7.09
6.97
7.15

Tables (Output of Computation)





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=105732&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=105732&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105732&T=0

As an alternative you can also use a QR Code:  
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
10.7647627.21480
20.6344735.98560
30.5347365.04471e-06
40.4092453.86080.000107
50.2921872.75650.003544
60.2400242.26440.01299
70.1755511.65610.050608
80.2042131.92650.028614
90.1649661.55630.061595
100.0920720.86860.193701
110.0923690.87140.192939
120.0997780.94130.174548
13-0.033662-0.31760.375778
14-0.051189-0.48290.315169
15-0.171048-1.61370.05507
16-0.226185-2.13380.017804
17-0.270701-2.55380.006179
18-0.344038-3.24560.000826
19-0.369464-3.48550.000382

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.764762 & 7.2148 & 0 \tabularnewline
2 & 0.634473 & 5.9856 & 0 \tabularnewline
3 & 0.534736 & 5.0447 & 1e-06 \tabularnewline
4 & 0.409245 & 3.8608 & 0.000107 \tabularnewline
5 & 0.292187 & 2.7565 & 0.003544 \tabularnewline
6 & 0.240024 & 2.2644 & 0.01299 \tabularnewline
7 & 0.175551 & 1.6561 & 0.050608 \tabularnewline
8 & 0.204213 & 1.9265 & 0.028614 \tabularnewline
9 & 0.164966 & 1.5563 & 0.061595 \tabularnewline
10 & 0.092072 & 0.8686 & 0.193701 \tabularnewline
11 & 0.092369 & 0.8714 & 0.192939 \tabularnewline
12 & 0.099778 & 0.9413 & 0.174548 \tabularnewline
13 & -0.033662 & -0.3176 & 0.375778 \tabularnewline
14 & -0.051189 & -0.4829 & 0.315169 \tabularnewline
15 & -0.171048 & -1.6137 & 0.05507 \tabularnewline
16 & -0.226185 & -2.1338 & 0.017804 \tabularnewline
17 & -0.270701 & -2.5538 & 0.006179 \tabularnewline
18 & -0.344038 & -3.2456 & 0.000826 \tabularnewline
19 & -0.369464 & -3.4855 & 0.000382 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105732&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]0.764762[/C][C]7.2148[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.634473[/C][C]5.9856[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.534736[/C][C]5.0447[/C][C]1e-06[/C][/ROW]
[ROW][C]4[/C][C]0.409245[/C][C]3.8608[/C][C]0.000107[/C][/ROW]
[ROW][C]5[/C][C]0.292187[/C][C]2.7565[/C][C]0.003544[/C][/ROW]
[ROW][C]6[/C][C]0.240024[/C][C]2.2644[/C][C]0.01299[/C][/ROW]
[ROW][C]7[/C][C]0.175551[/C][C]1.6561[/C][C]0.050608[/C][/ROW]
[ROW][C]8[/C][C]0.204213[/C][C]1.9265[/C][C]0.028614[/C][/ROW]
[ROW][C]9[/C][C]0.164966[/C][C]1.5563[/C][C]0.061595[/C][/ROW]
[ROW][C]10[/C][C]0.092072[/C][C]0.8686[/C][C]0.193701[/C][/ROW]
[ROW][C]11[/C][C]0.092369[/C][C]0.8714[/C][C]0.192939[/C][/ROW]
[ROW][C]12[/C][C]0.099778[/C][C]0.9413[/C][C]0.174548[/C][/ROW]
[ROW][C]13[/C][C]-0.033662[/C][C]-0.3176[/C][C]0.375778[/C][/ROW]
[ROW][C]14[/C][C]-0.051189[/C][C]-0.4829[/C][C]0.315169[/C][/ROW]
[ROW][C]15[/C][C]-0.171048[/C][C]-1.6137[/C][C]0.05507[/C][/ROW]
[ROW][C]16[/C][C]-0.226185[/C][C]-2.1338[/C][C]0.017804[/C][/ROW]
[ROW][C]17[/C][C]-0.270701[/C][C]-2.5538[/C][C]0.006179[/C][/ROW]
[ROW][C]18[/C][C]-0.344038[/C][C]-3.2456[/C][C]0.000826[/C][/ROW]
[ROW][C]19[/C][C]-0.369464[/C][C]-3.4855[/C][C]0.000382[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105732&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105732&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7647627.21480
20.6344735.98560
30.5347365.04471e-06
40.4092453.86080.000107
50.2921872.75650.003544
60.2400242.26440.01299
70.1755511.65610.050608
80.2042131.92650.028614
90.1649661.55630.061595
100.0920720.86860.193701
110.0923690.87140.192939
120.0997780.94130.174548
13-0.033662-0.31760.375778
14-0.051189-0.48290.315169
15-0.171048-1.61370.05507
16-0.226185-2.13380.017804
17-0.270701-2.55380.006179
18-0.344038-3.24560.000826
19-0.369464-3.48550.000382






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7647627.21480
20.1195051.12740.1313
30.0393660.37140.35562
4-0.091596-0.86410.194925
5-0.076535-0.7220.236086
60.0670170.63220.264428
7-0.02111-0.19910.421301
80.193311.82370.035779
9-0.093264-0.87990.190654
10-0.137385-1.29610.099148
110.0717540.67690.250105
120.0631630.59590.276384
13-0.274773-2.59220.005573
140.0668850.6310.26483
15-0.278568-2.6280.005058
160.0322250.3040.380914
17-0.057119-0.53890.295665
18-0.127513-1.2030.116091
190.0276830.26120.397288

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.764762 & 7.2148 & 0 \tabularnewline
2 & 0.119505 & 1.1274 & 0.1313 \tabularnewline
3 & 0.039366 & 0.3714 & 0.35562 \tabularnewline
4 & -0.091596 & -0.8641 & 0.194925 \tabularnewline
5 & -0.076535 & -0.722 & 0.236086 \tabularnewline
6 & 0.067017 & 0.6322 & 0.264428 \tabularnewline
7 & -0.02111 & -0.1991 & 0.421301 \tabularnewline
8 & 0.19331 & 1.8237 & 0.035779 \tabularnewline
9 & -0.093264 & -0.8799 & 0.190654 \tabularnewline
10 & -0.137385 & -1.2961 & 0.099148 \tabularnewline
11 & 0.071754 & 0.6769 & 0.250105 \tabularnewline
12 & 0.063163 & 0.5959 & 0.276384 \tabularnewline
13 & -0.274773 & -2.5922 & 0.005573 \tabularnewline
14 & 0.066885 & 0.631 & 0.26483 \tabularnewline
15 & -0.278568 & -2.628 & 0.005058 \tabularnewline
16 & 0.032225 & 0.304 & 0.380914 \tabularnewline
17 & -0.057119 & -0.5389 & 0.295665 \tabularnewline
18 & -0.127513 & -1.203 & 0.116091 \tabularnewline
19 & 0.027683 & 0.2612 & 0.397288 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=105732&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]0.764762[/C][C]7.2148[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.119505[/C][C]1.1274[/C][C]0.1313[/C][/ROW]
[ROW][C]3[/C][C]0.039366[/C][C]0.3714[/C][C]0.35562[/C][/ROW]
[ROW][C]4[/C][C]-0.091596[/C][C]-0.8641[/C][C]0.194925[/C][/ROW]
[ROW][C]5[/C][C]-0.076535[/C][C]-0.722[/C][C]0.236086[/C][/ROW]
[ROW][C]6[/C][C]0.067017[/C][C]0.6322[/C][C]0.264428[/C][/ROW]
[ROW][C]7[/C][C]-0.02111[/C][C]-0.1991[/C][C]0.421301[/C][/ROW]
[ROW][C]8[/C][C]0.19331[/C][C]1.8237[/C][C]0.035779[/C][/ROW]
[ROW][C]9[/C][C]-0.093264[/C][C]-0.8799[/C][C]0.190654[/C][/ROW]
[ROW][C]10[/C][C]-0.137385[/C][C]-1.2961[/C][C]0.099148[/C][/ROW]
[ROW][C]11[/C][C]0.071754[/C][C]0.6769[/C][C]0.250105[/C][/ROW]
[ROW][C]12[/C][C]0.063163[/C][C]0.5959[/C][C]0.276384[/C][/ROW]
[ROW][C]13[/C][C]-0.274773[/C][C]-2.5922[/C][C]0.005573[/C][/ROW]
[ROW][C]14[/C][C]0.066885[/C][C]0.631[/C][C]0.26483[/C][/ROW]
[ROW][C]15[/C][C]-0.278568[/C][C]-2.628[/C][C]0.005058[/C][/ROW]
[ROW][C]16[/C][C]0.032225[/C][C]0.304[/C][C]0.380914[/C][/ROW]
[ROW][C]17[/C][C]-0.057119[/C][C]-0.5389[/C][C]0.295665[/C][/ROW]
[ROW][C]18[/C][C]-0.127513[/C][C]-1.203[/C][C]0.116091[/C][/ROW]
[ROW][C]19[/C][C]0.027683[/C][C]0.2612[/C][C]0.397288[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=105732&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=105732&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7647627.21480
20.1195051.12740.1313
30.0393660.37140.35562
4-0.091596-0.86410.194925
5-0.076535-0.7220.236086
60.0670170.63220.264428
7-0.02111-0.19910.421301
80.193311.82370.035779
9-0.093264-0.87990.190654
10-0.137385-1.29610.099148
110.0717540.67690.250105
120.0631630.59590.276384
13-0.274773-2.59220.005573
140.0668850.6310.26483
15-0.278568-2.6280.005058
160.0322250.3040.380914
17-0.057119-0.53890.295665
18-0.127513-1.2030.116091
190.0276830.26120.397288


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')