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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 13 Dec 2007 07:11:03 -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/2007/Dec/13/t1197554163zwwy0wal64pmfkg.htm/, Retrieved Sun, 05 May 2024 15:20:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3547, Retrieved Sun, 05 May 2024 15:20:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact225

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [Paper_EDA_output1] [2007-12-13 08:57:44] [e44956fac49704be9081ff9a6fb8481a]
- RMPD    [(Partial) Autocorrelation Function] [Paper_(P)ACF_output9] [2007-12-13 14:11:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102,61
102,18
101,64
102
102,18
101,89
102,09
101,6
101,33
101,44
101,49
100,41
101,38
101,4
102,16
104,46
104,75
104,2
106,05
107,54
108,23
108,99
109,51
111,99
111,08
112,95
115,49
114,67
116,85
119,57
119,41
118,46
122,81
121,76
121,37
118,61
116,08
117,84
117,02
119,78
122,58
120,98
118,92
117,81
119,73
117,16
116,03
115,55
115,36
116,09
117,32
120,45
119,86
118,51
118,92
119,11
120,34
121,23
119,43
119,28
120,64
122,24
123,1
120,72
118,34
118,8
119,29
121,47
122,35
121,53
121,72
121,58
121,55
122,02
123,74
125,8
129,29
128,89
130,04
131,57
131,97
134,43
132,63
130,26
129
131,65
134,21
138,63
138,1
140,51
144,36
145,57
148,7
147,86
143,16
141,96

Tables (Output of Computation)





Summary of compuational 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 compuational 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=3547&T=0

[TABLE]
[ROW][C]Summary of compuational 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=3547&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3547&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 compuational 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
019.74680
10.1590511.55020.062205
2-0.079002-0.770.778398
3-0.01906-0.18580.57349
4-0.143058-1.39440.916769
50.0628040.61210.270954
60.0542850.52910.298985
7-0.027417-0.26720.605063
8-0.146651-1.42940.921912
9-0.097031-0.94570.826659
100.0538640.5250.300402
110.3361143.2760.000735
120.0459180.44760.327748
13-0.134852-1.31440.904058
140.0523840.51060.305415
15-0.169005-1.64730.948595
16-0.08035-0.78320.782258
170.0053210.05190.479373
18-0.064605-0.62970.734797

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 9.7468 & 0 \tabularnewline
1 & 0.159051 & 1.5502 & 0.062205 \tabularnewline
2 & -0.079002 & -0.77 & 0.778398 \tabularnewline
3 & -0.01906 & -0.1858 & 0.57349 \tabularnewline
4 & -0.143058 & -1.3944 & 0.916769 \tabularnewline
5 & 0.062804 & 0.6121 & 0.270954 \tabularnewline
6 & 0.054285 & 0.5291 & 0.298985 \tabularnewline
7 & -0.027417 & -0.2672 & 0.605063 \tabularnewline
8 & -0.146651 & -1.4294 & 0.921912 \tabularnewline
9 & -0.097031 & -0.9457 & 0.826659 \tabularnewline
10 & 0.053864 & 0.525 & 0.300402 \tabularnewline
11 & 0.336114 & 3.276 & 0.000735 \tabularnewline
12 & 0.045918 & 0.4476 & 0.327748 \tabularnewline
13 & -0.134852 & -1.3144 & 0.904058 \tabularnewline
14 & 0.052384 & 0.5106 & 0.305415 \tabularnewline
15 & -0.169005 & -1.6473 & 0.948595 \tabularnewline
16 & -0.08035 & -0.7832 & 0.782258 \tabularnewline
17 & 0.005321 & 0.0519 & 0.479373 \tabularnewline
18 & -0.064605 & -0.6297 & 0.734797 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3547&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]0[/C][C]1[/C][C]9.7468[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.159051[/C][C]1.5502[/C][C]0.062205[/C][/ROW]
[ROW][C]2[/C][C]-0.079002[/C][C]-0.77[/C][C]0.778398[/C][/ROW]
[ROW][C]3[/C][C]-0.01906[/C][C]-0.1858[/C][C]0.57349[/C][/ROW]
[ROW][C]4[/C][C]-0.143058[/C][C]-1.3944[/C][C]0.916769[/C][/ROW]
[ROW][C]5[/C][C]0.062804[/C][C]0.6121[/C][C]0.270954[/C][/ROW]
[ROW][C]6[/C][C]0.054285[/C][C]0.5291[/C][C]0.298985[/C][/ROW]
[ROW][C]7[/C][C]-0.027417[/C][C]-0.2672[/C][C]0.605063[/C][/ROW]
[ROW][C]8[/C][C]-0.146651[/C][C]-1.4294[/C][C]0.921912[/C][/ROW]
[ROW][C]9[/C][C]-0.097031[/C][C]-0.9457[/C][C]0.826659[/C][/ROW]
[ROW][C]10[/C][C]0.053864[/C][C]0.525[/C][C]0.300402[/C][/ROW]
[ROW][C]11[/C][C]0.336114[/C][C]3.276[/C][C]0.000735[/C][/ROW]
[ROW][C]12[/C][C]0.045918[/C][C]0.4476[/C][C]0.327748[/C][/ROW]
[ROW][C]13[/C][C]-0.134852[/C][C]-1.3144[/C][C]0.904058[/C][/ROW]
[ROW][C]14[/C][C]0.052384[/C][C]0.5106[/C][C]0.305415[/C][/ROW]
[ROW][C]15[/C][C]-0.169005[/C][C]-1.6473[/C][C]0.948595[/C][/ROW]
[ROW][C]16[/C][C]-0.08035[/C][C]-0.7832[/C][C]0.782258[/C][/ROW]
[ROW][C]17[/C][C]0.005321[/C][C]0.0519[/C][C]0.479373[/C][/ROW]
[ROW][C]18[/C][C]-0.064605[/C][C]-0.6297[/C][C]0.734797[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3547&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3547&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
019.74680
10.1590511.55020.062205
2-0.079002-0.770.778398
3-0.01906-0.18580.57349
4-0.143058-1.39440.916769
50.0628040.61210.270954
60.0542850.52910.298985
7-0.027417-0.26720.605063
8-0.146651-1.42940.921912
9-0.097031-0.94570.826659
100.0538640.5250.300402
110.3361143.2760.000735
120.0459180.44760.327748
13-0.134852-1.31440.904058
140.0523840.51060.305415
15-0.169005-1.64730.948595
16-0.08035-0.78320.782258
170.0053210.05190.479373
18-0.064605-0.62970.734797






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.1590511.55020.062205
1-0.107006-1.0430.850194
20.0123190.12010.452342
3-0.15597-1.52020.93411
40.12131.18230.120022
5-0.009926-0.09670.538433
6-0.015127-0.14740.55845
7-0.171451-1.67110.951003
8-0.017637-0.17190.56806
90.0494560.4820.315444
100.3370443.28510.000714
11-0.133228-1.29850.901379
12-0.07132-0.69510.755668
130.0988920.96390.168776
14-0.127634-1.2440.891723
15-0.110077-1.07290.856983
16-0.06601-0.64340.739237
170.0044260.04310.482841
180.10631.03610.151395

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.159051 & 1.5502 & 0.062205 \tabularnewline
1 & -0.107006 & -1.043 & 0.850194 \tabularnewline
2 & 0.012319 & 0.1201 & 0.452342 \tabularnewline
3 & -0.15597 & -1.5202 & 0.93411 \tabularnewline
4 & 0.1213 & 1.1823 & 0.120022 \tabularnewline
5 & -0.009926 & -0.0967 & 0.538433 \tabularnewline
6 & -0.015127 & -0.1474 & 0.55845 \tabularnewline
7 & -0.171451 & -1.6711 & 0.951003 \tabularnewline
8 & -0.017637 & -0.1719 & 0.56806 \tabularnewline
9 & 0.049456 & 0.482 & 0.315444 \tabularnewline
10 & 0.337044 & 3.2851 & 0.000714 \tabularnewline
11 & -0.133228 & -1.2985 & 0.901379 \tabularnewline
12 & -0.07132 & -0.6951 & 0.755668 \tabularnewline
13 & 0.098892 & 0.9639 & 0.168776 \tabularnewline
14 & -0.127634 & -1.244 & 0.891723 \tabularnewline
15 & -0.110077 & -1.0729 & 0.856983 \tabularnewline
16 & -0.06601 & -0.6434 & 0.739237 \tabularnewline
17 & 0.004426 & 0.0431 & 0.482841 \tabularnewline
18 & 0.1063 & 1.0361 & 0.151395 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3547&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]0[/C][C]0.159051[/C][C]1.5502[/C][C]0.062205[/C][/ROW]
[ROW][C]1[/C][C]-0.107006[/C][C]-1.043[/C][C]0.850194[/C][/ROW]
[ROW][C]2[/C][C]0.012319[/C][C]0.1201[/C][C]0.452342[/C][/ROW]
[ROW][C]3[/C][C]-0.15597[/C][C]-1.5202[/C][C]0.93411[/C][/ROW]
[ROW][C]4[/C][C]0.1213[/C][C]1.1823[/C][C]0.120022[/C][/ROW]
[ROW][C]5[/C][C]-0.009926[/C][C]-0.0967[/C][C]0.538433[/C][/ROW]
[ROW][C]6[/C][C]-0.015127[/C][C]-0.1474[/C][C]0.55845[/C][/ROW]
[ROW][C]7[/C][C]-0.171451[/C][C]-1.6711[/C][C]0.951003[/C][/ROW]
[ROW][C]8[/C][C]-0.017637[/C][C]-0.1719[/C][C]0.56806[/C][/ROW]
[ROW][C]9[/C][C]0.049456[/C][C]0.482[/C][C]0.315444[/C][/ROW]
[ROW][C]10[/C][C]0.337044[/C][C]3.2851[/C][C]0.000714[/C][/ROW]
[ROW][C]11[/C][C]-0.133228[/C][C]-1.2985[/C][C]0.901379[/C][/ROW]
[ROW][C]12[/C][C]-0.07132[/C][C]-0.6951[/C][C]0.755668[/C][/ROW]
[ROW][C]13[/C][C]0.098892[/C][C]0.9639[/C][C]0.168776[/C][/ROW]
[ROW][C]14[/C][C]-0.127634[/C][C]-1.244[/C][C]0.891723[/C][/ROW]
[ROW][C]15[/C][C]-0.110077[/C][C]-1.0729[/C][C]0.856983[/C][/ROW]
[ROW][C]16[/C][C]-0.06601[/C][C]-0.6434[/C][C]0.739237[/C][/ROW]
[ROW][C]17[/C][C]0.004426[/C][C]0.0431[/C][C]0.482841[/C][/ROW]
[ROW][C]18[/C][C]0.1063[/C][C]1.0361[/C][C]0.151395[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3547&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3547&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
00.1590511.55020.062205
1-0.107006-1.0430.850194
20.0123190.12010.452342
3-0.15597-1.52020.93411
40.12131.18230.120022
5-0.009926-0.09670.538433
6-0.015127-0.14740.55845
7-0.171451-1.67110.951003
8-0.017637-0.17190.56806
90.0494560.4820.315444
100.3370443.28510.000714
11-0.133228-1.29850.901379
12-0.07132-0.69510.755668
130.0988920.96390.168776
14-0.127634-1.2440.891723
15-0.110077-1.07290.856983
16-0.06601-0.64340.739237
170.0044260.04310.482841
180.10631.03610.151395


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -0.4 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = Default ; par2 = -0.3 ; par3 = 1 ; 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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')