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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, 03 Dec 2009 13:28:19 -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/03/t1259872180j1cfvqrm7z0y9sp.htm/, Retrieved Sat, 20 Apr 2024 05:13:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63114, Retrieved Sat, 20 Apr 2024 05:13:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsBasisjaar 2000 = 100
Estimated Impact102

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] [] [2009-11-27 14:47:30] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [Grondstofprijsind...] [2009-12-03 20:28:19] [c483349466b1550829c7523719d2d027] [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 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=63114&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=63114&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63114&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
1-0.243388-1.86950.033259
20.1275540.97980.165603
3-0.211422-1.6240.054857
40.0856240.65770.256647
5-0.259145-1.99050.025586
6-0.115734-0.8890.188816
70.086910.66760.253507
80.1012620.77780.219896
9-0.216117-1.660.051108
100.1310761.00680.159068
110.0668380.51340.304797
120.0094370.07250.471228
13-0.177425-1.36280.089059
140.0575330.44190.330083
150.1568051.20440.116615
16-0.069737-0.53570.297103
17-0.054411-0.41790.338756

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.243388 & -1.8695 & 0.033259 \tabularnewline
2 & 0.127554 & 0.9798 & 0.165603 \tabularnewline
3 & -0.211422 & -1.624 & 0.054857 \tabularnewline
4 & 0.085624 & 0.6577 & 0.256647 \tabularnewline
5 & -0.259145 & -1.9905 & 0.025586 \tabularnewline
6 & -0.115734 & -0.889 & 0.188816 \tabularnewline
7 & 0.08691 & 0.6676 & 0.253507 \tabularnewline
8 & 0.101262 & 0.7778 & 0.219896 \tabularnewline
9 & -0.216117 & -1.66 & 0.051108 \tabularnewline
10 & 0.131076 & 1.0068 & 0.159068 \tabularnewline
11 & 0.066838 & 0.5134 & 0.304797 \tabularnewline
12 & 0.009437 & 0.0725 & 0.471228 \tabularnewline
13 & -0.177425 & -1.3628 & 0.089059 \tabularnewline
14 & 0.057533 & 0.4419 & 0.330083 \tabularnewline
15 & 0.156805 & 1.2044 & 0.116615 \tabularnewline
16 & -0.069737 & -0.5357 & 0.297103 \tabularnewline
17 & -0.054411 & -0.4179 & 0.338756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63114&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]-0.243388[/C][C]-1.8695[/C][C]0.033259[/C][/ROW]
[ROW][C]2[/C][C]0.127554[/C][C]0.9798[/C][C]0.165603[/C][/ROW]
[ROW][C]3[/C][C]-0.211422[/C][C]-1.624[/C][C]0.054857[/C][/ROW]
[ROW][C]4[/C][C]0.085624[/C][C]0.6577[/C][C]0.256647[/C][/ROW]
[ROW][C]5[/C][C]-0.259145[/C][C]-1.9905[/C][C]0.025586[/C][/ROW]
[ROW][C]6[/C][C]-0.115734[/C][C]-0.889[/C][C]0.188816[/C][/ROW]
[ROW][C]7[/C][C]0.08691[/C][C]0.6676[/C][C]0.253507[/C][/ROW]
[ROW][C]8[/C][C]0.101262[/C][C]0.7778[/C][C]0.219896[/C][/ROW]
[ROW][C]9[/C][C]-0.216117[/C][C]-1.66[/C][C]0.051108[/C][/ROW]
[ROW][C]10[/C][C]0.131076[/C][C]1.0068[/C][C]0.159068[/C][/ROW]
[ROW][C]11[/C][C]0.066838[/C][C]0.5134[/C][C]0.304797[/C][/ROW]
[ROW][C]12[/C][C]0.009437[/C][C]0.0725[/C][C]0.471228[/C][/ROW]
[ROW][C]13[/C][C]-0.177425[/C][C]-1.3628[/C][C]0.089059[/C][/ROW]
[ROW][C]14[/C][C]0.057533[/C][C]0.4419[/C][C]0.330083[/C][/ROW]
[ROW][C]15[/C][C]0.156805[/C][C]1.2044[/C][C]0.116615[/C][/ROW]
[ROW][C]16[/C][C]-0.069737[/C][C]-0.5357[/C][C]0.297103[/C][/ROW]
[ROW][C]17[/C][C]-0.054411[/C][C]-0.4179[/C][C]0.338756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63114&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63114&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
1-0.243388-1.86950.033259
20.1275540.97980.165603
3-0.211422-1.6240.054857
40.0856240.65770.256647
5-0.259145-1.99050.025586
6-0.115734-0.8890.188816
70.086910.66760.253507
80.1012620.77780.219896
9-0.216117-1.660.051108
100.1310761.00680.159068
110.0668380.51340.304797
120.0094370.07250.471228
13-0.177425-1.36280.089059
140.0575330.44190.330083
150.1568051.20440.116615
16-0.069737-0.53570.297103
17-0.054411-0.41790.338756






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.243388-1.86950.033259
20.0726180.55780.28955
3-0.176274-1.3540.090453
4-0.007148-0.05490.478201
5-0.234788-1.80340.038213
6-0.299633-2.30150.012455
70.0238230.1830.427716
80.0655740.50370.308181
9-0.323261-2.4830.007945
10-0.04525-0.34760.364698
110.0614970.47240.319203
12-0.115078-0.88390.190162
13-0.172594-1.32570.095022
14-0.119625-0.91890.180957
150.0919040.70590.241505
160.0289480.22240.412403
17-0.133396-1.02460.154859

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.243388 & -1.8695 & 0.033259 \tabularnewline
2 & 0.072618 & 0.5578 & 0.28955 \tabularnewline
3 & -0.176274 & -1.354 & 0.090453 \tabularnewline
4 & -0.007148 & -0.0549 & 0.478201 \tabularnewline
5 & -0.234788 & -1.8034 & 0.038213 \tabularnewline
6 & -0.299633 & -2.3015 & 0.012455 \tabularnewline
7 & 0.023823 & 0.183 & 0.427716 \tabularnewline
8 & 0.065574 & 0.5037 & 0.308181 \tabularnewline
9 & -0.323261 & -2.483 & 0.007945 \tabularnewline
10 & -0.04525 & -0.3476 & 0.364698 \tabularnewline
11 & 0.061497 & 0.4724 & 0.319203 \tabularnewline
12 & -0.115078 & -0.8839 & 0.190162 \tabularnewline
13 & -0.172594 & -1.3257 & 0.095022 \tabularnewline
14 & -0.119625 & -0.9189 & 0.180957 \tabularnewline
15 & 0.091904 & 0.7059 & 0.241505 \tabularnewline
16 & 0.028948 & 0.2224 & 0.412403 \tabularnewline
17 & -0.133396 & -1.0246 & 0.154859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63114&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]-0.243388[/C][C]-1.8695[/C][C]0.033259[/C][/ROW]
[ROW][C]2[/C][C]0.072618[/C][C]0.5578[/C][C]0.28955[/C][/ROW]
[ROW][C]3[/C][C]-0.176274[/C][C]-1.354[/C][C]0.090453[/C][/ROW]
[ROW][C]4[/C][C]-0.007148[/C][C]-0.0549[/C][C]0.478201[/C][/ROW]
[ROW][C]5[/C][C]-0.234788[/C][C]-1.8034[/C][C]0.038213[/C][/ROW]
[ROW][C]6[/C][C]-0.299633[/C][C]-2.3015[/C][C]0.012455[/C][/ROW]
[ROW][C]7[/C][C]0.023823[/C][C]0.183[/C][C]0.427716[/C][/ROW]
[ROW][C]8[/C][C]0.065574[/C][C]0.5037[/C][C]0.308181[/C][/ROW]
[ROW][C]9[/C][C]-0.323261[/C][C]-2.483[/C][C]0.007945[/C][/ROW]
[ROW][C]10[/C][C]-0.04525[/C][C]-0.3476[/C][C]0.364698[/C][/ROW]
[ROW][C]11[/C][C]0.061497[/C][C]0.4724[/C][C]0.319203[/C][/ROW]
[ROW][C]12[/C][C]-0.115078[/C][C]-0.8839[/C][C]0.190162[/C][/ROW]
[ROW][C]13[/C][C]-0.172594[/C][C]-1.3257[/C][C]0.095022[/C][/ROW]
[ROW][C]14[/C][C]-0.119625[/C][C]-0.9189[/C][C]0.180957[/C][/ROW]
[ROW][C]15[/C][C]0.091904[/C][C]0.7059[/C][C]0.241505[/C][/ROW]
[ROW][C]16[/C][C]0.028948[/C][C]0.2224[/C][C]0.412403[/C][/ROW]
[ROW][C]17[/C][C]-0.133396[/C][C]-1.0246[/C][C]0.154859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63114&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63114&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
1-0.243388-1.86950.033259
20.0726180.55780.28955
3-0.176274-1.3540.090453
4-0.007148-0.05490.478201
5-0.234788-1.80340.038213
6-0.299633-2.30150.012455
70.0238230.1830.427716
80.0655740.50370.308181
9-0.323261-2.4830.007945
10-0.04525-0.34760.364698
110.0614970.47240.319203
12-0.115078-0.88390.190162
13-0.172594-1.32570.095022
14-0.119625-0.91890.180957
150.0919040.70590.241505
160.0289480.22240.412403
17-0.133396-1.02460.154859


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 0 ; 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')