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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 computationThu, 26 Nov 2009 02:26:31 -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/Nov/26/t1259227662xkwlz48l95fy5v7.htm/, Retrieved Sun, 28 Apr 2024 20:37:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59726, Retrieved Sun, 28 Apr 2024 20:37:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsBasisjaar 2000 = 100
Estimated Impact141

Tree of Dependent Computations

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [Grondstofprijsind...] [2009-11-26 09:26:31] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
117.1
118.7
126.5
127.5
134.6
131.8
135.9
142.7
141.7
153.4
145
137.7
148.3
152.2
169.4
168.6
161.1
174.1
179
190.6
190
181.6
174.8
180.5
196.8
193.8
197
216.3
221.4
217.9
229.7
227.4
204.2
196.6
198.8
207.5
190.7
201.6
210.5
223.5
223.8
231.2
244
234.7
250.2
265.7
287.6
283.3
295.4
312.3
333.8
347.7
383.2
407.1
413.6
362.7
321.9
239.4
191
159.7
163.4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59726&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]2 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=59726&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59726&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.600863.60520.000469
20.3602222.16130.018699
30.1486770.89210.189141
40.0276580.16590.434563
5-0.156483-0.93890.17702
6-0.11341-0.68050.250283
7-0.023524-0.14110.444271
8-0.104251-0.62550.267793
9-0.141252-0.84750.201155
10-0.088432-0.53060.299479
11-0.065561-0.39340.348185
12-0.286813-1.72090.046929
13-0.193131-1.15880.127087
14-0.118054-0.70830.241652
15-0.038488-0.23090.40934
16-0.0638-0.38280.352061
17-0.005457-0.03270.487031

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.60086 & 3.6052 & 0.000469 \tabularnewline
2 & 0.360222 & 2.1613 & 0.018699 \tabularnewline
3 & 0.148677 & 0.8921 & 0.189141 \tabularnewline
4 & 0.027658 & 0.1659 & 0.434563 \tabularnewline
5 & -0.156483 & -0.9389 & 0.17702 \tabularnewline
6 & -0.11341 & -0.6805 & 0.250283 \tabularnewline
7 & -0.023524 & -0.1411 & 0.444271 \tabularnewline
8 & -0.104251 & -0.6255 & 0.267793 \tabularnewline
9 & -0.141252 & -0.8475 & 0.201155 \tabularnewline
10 & -0.088432 & -0.5306 & 0.299479 \tabularnewline
11 & -0.065561 & -0.3934 & 0.348185 \tabularnewline
12 & -0.286813 & -1.7209 & 0.046929 \tabularnewline
13 & -0.193131 & -1.1588 & 0.127087 \tabularnewline
14 & -0.118054 & -0.7083 & 0.241652 \tabularnewline
15 & -0.038488 & -0.2309 & 0.40934 \tabularnewline
16 & -0.0638 & -0.3828 & 0.352061 \tabularnewline
17 & -0.005457 & -0.0327 & 0.487031 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59726&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]0.60086[/C][C]3.6052[/C][C]0.000469[/C][/ROW]
[ROW][C]2[/C][C]0.360222[/C][C]2.1613[/C][C]0.018699[/C][/ROW]
[ROW][C]3[/C][C]0.148677[/C][C]0.8921[/C][C]0.189141[/C][/ROW]
[ROW][C]4[/C][C]0.027658[/C][C]0.1659[/C][C]0.434563[/C][/ROW]
[ROW][C]5[/C][C]-0.156483[/C][C]-0.9389[/C][C]0.17702[/C][/ROW]
[ROW][C]6[/C][C]-0.11341[/C][C]-0.6805[/C][C]0.250283[/C][/ROW]
[ROW][C]7[/C][C]-0.023524[/C][C]-0.1411[/C][C]0.444271[/C][/ROW]
[ROW][C]8[/C][C]-0.104251[/C][C]-0.6255[/C][C]0.267793[/C][/ROW]
[ROW][C]9[/C][C]-0.141252[/C][C]-0.8475[/C][C]0.201155[/C][/ROW]
[ROW][C]10[/C][C]-0.088432[/C][C]-0.5306[/C][C]0.299479[/C][/ROW]
[ROW][C]11[/C][C]-0.065561[/C][C]-0.3934[/C][C]0.348185[/C][/ROW]
[ROW][C]12[/C][C]-0.286813[/C][C]-1.7209[/C][C]0.046929[/C][/ROW]
[ROW][C]13[/C][C]-0.193131[/C][C]-1.1588[/C][C]0.127087[/C][/ROW]
[ROW][C]14[/C][C]-0.118054[/C][C]-0.7083[/C][C]0.241652[/C][/ROW]
[ROW][C]15[/C][C]-0.038488[/C][C]-0.2309[/C][C]0.40934[/C][/ROW]
[ROW][C]16[/C][C]-0.0638[/C][C]-0.3828[/C][C]0.352061[/C][/ROW]
[ROW][C]17[/C][C]-0.005457[/C][C]-0.0327[/C][C]0.487031[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59726&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59726&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
10.600863.60520.000469
20.3602222.16130.018699
30.1486770.89210.189141
40.0276580.16590.434563
5-0.156483-0.93890.17702
6-0.11341-0.68050.250283
7-0.023524-0.14110.444271
8-0.104251-0.62550.267793
9-0.141252-0.84750.201155
10-0.088432-0.53060.299479
11-0.065561-0.39340.348185
12-0.286813-1.72090.046929
13-0.193131-1.15880.127087
14-0.118054-0.70830.241652
15-0.038488-0.23090.40934
16-0.0638-0.38280.352061
17-0.005457-0.03270.487031






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.600863.60520.000469
2-0.001268-0.00760.496985
3-0.105292-0.63170.265771
4-0.033022-0.19810.422028
5-0.209035-1.25420.108924
60.1341650.8050.213056
70.1083560.65010.259866
8-0.242854-1.45710.076876
9-0.039013-0.23410.408126
100.0564360.33860.368434
11-0.022406-0.13440.446903
12-0.365931-2.19560.017325
130.1758131.05490.149255
140.0296410.17780.42992
150.0222580.13350.447252
16-0.086203-0.51720.304083
17-0.163737-0.98240.166224

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.60086 & 3.6052 & 0.000469 \tabularnewline
2 & -0.001268 & -0.0076 & 0.496985 \tabularnewline
3 & -0.105292 & -0.6317 & 0.265771 \tabularnewline
4 & -0.033022 & -0.1981 & 0.422028 \tabularnewline
5 & -0.209035 & -1.2542 & 0.108924 \tabularnewline
6 & 0.134165 & 0.805 & 0.213056 \tabularnewline
7 & 0.108356 & 0.6501 & 0.259866 \tabularnewline
8 & -0.242854 & -1.4571 & 0.076876 \tabularnewline
9 & -0.039013 & -0.2341 & 0.408126 \tabularnewline
10 & 0.056436 & 0.3386 & 0.368434 \tabularnewline
11 & -0.022406 & -0.1344 & 0.446903 \tabularnewline
12 & -0.365931 & -2.1956 & 0.017325 \tabularnewline
13 & 0.175813 & 1.0549 & 0.149255 \tabularnewline
14 & 0.029641 & 0.1778 & 0.42992 \tabularnewline
15 & 0.022258 & 0.1335 & 0.447252 \tabularnewline
16 & -0.086203 & -0.5172 & 0.304083 \tabularnewline
17 & -0.163737 & -0.9824 & 0.166224 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59726&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]0.60086[/C][C]3.6052[/C][C]0.000469[/C][/ROW]
[ROW][C]2[/C][C]-0.001268[/C][C]-0.0076[/C][C]0.496985[/C][/ROW]
[ROW][C]3[/C][C]-0.105292[/C][C]-0.6317[/C][C]0.265771[/C][/ROW]
[ROW][C]4[/C][C]-0.033022[/C][C]-0.1981[/C][C]0.422028[/C][/ROW]
[ROW][C]5[/C][C]-0.209035[/C][C]-1.2542[/C][C]0.108924[/C][/ROW]
[ROW][C]6[/C][C]0.134165[/C][C]0.805[/C][C]0.213056[/C][/ROW]
[ROW][C]7[/C][C]0.108356[/C][C]0.6501[/C][C]0.259866[/C][/ROW]
[ROW][C]8[/C][C]-0.242854[/C][C]-1.4571[/C][C]0.076876[/C][/ROW]
[ROW][C]9[/C][C]-0.039013[/C][C]-0.2341[/C][C]0.408126[/C][/ROW]
[ROW][C]10[/C][C]0.056436[/C][C]0.3386[/C][C]0.368434[/C][/ROW]
[ROW][C]11[/C][C]-0.022406[/C][C]-0.1344[/C][C]0.446903[/C][/ROW]
[ROW][C]12[/C][C]-0.365931[/C][C]-2.1956[/C][C]0.017325[/C][/ROW]
[ROW][C]13[/C][C]0.175813[/C][C]1.0549[/C][C]0.149255[/C][/ROW]
[ROW][C]14[/C][C]0.029641[/C][C]0.1778[/C][C]0.42992[/C][/ROW]
[ROW][C]15[/C][C]0.022258[/C][C]0.1335[/C][C]0.447252[/C][/ROW]
[ROW][C]16[/C][C]-0.086203[/C][C]-0.5172[/C][C]0.304083[/C][/ROW]
[ROW][C]17[/C][C]-0.163737[/C][C]-0.9824[/C][C]0.166224[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59726&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59726&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
10.600863.60520.000469
2-0.001268-0.00760.496985
3-0.105292-0.63170.265771
4-0.033022-0.19810.422028
5-0.209035-1.25420.108924
60.1341650.8050.213056
70.1083560.65010.259866
8-0.242854-1.45710.076876
9-0.039013-0.23410.408126
100.0564360.33860.368434
11-0.022406-0.13440.446903
12-0.365931-2.19560.017325
130.1758131.05490.149255
140.0296410.17780.42992
150.0222580.13350.447252
16-0.086203-0.51720.304083
17-0.163737-0.98240.166224


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 2.0 ; par3 = 1 ; par4 = 2 ; 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')