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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 computationTue, 14 Dec 2010 15:42:32 +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/14/t1292341224r408sz769lhyhg0.htm/, Retrieved Thu, 02 May 2024 18:48:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109753, Retrieved Thu, 02 May 2024 18:48:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
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 Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:05:21] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [ACF geen differen...] [2010-12-03 12:24:26] [9f32078fdcdc094ca748857d5ebdb3de]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-07 15:41:58] [ed939ef6f97e5f2afb6796311d9e7a5f]
- R PD          [(Partial) Autocorrelation Function] [Paper - ACF (12 l...] [2010-12-14 15:42:32] [ee4a783fb13f41eb2e9bc8a0c4f26279] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.81
9.12
11.03
12.74
9.98
11.62
9.40
9.27
7.76
8.78
10.65
10.95
12.36
10.85
11.84
12.14
11.65
8.86
7.63
7.38
7.25
8.03
7.75
7.16
7.18
7.51
7.07
7.11
8.98
9.53
10.54
11.31
10.36
11.44
10.45
10.69
11.28
11.96
13.52
12.89
14.03
16.27
16.17
17.25
19.38
26.20
33.53
32.20
38.45
44.86
41.67
36.06
39.76
36.81
42.65
46.89
53.61
57.59
67.82
71.89
75.51
68.49
62.72
70.39
59.77
57.27
67.96
67.85
76.98
81.08
91.66
84.84
85.73
84.61
92.91
99.80
121.19
122.04
131.76
138.48
153.47
189.95
182.22
198.08
135.36
125.02
143.50
173.95
188.75
167.44
158.95
169.53
113.66
107.59
92.67
85.35
90.13
89.31
105.12
125.83
135.81
142.43
163.39
168.21
185.35
188.50
199.91
210.73
192.06
204.62
235.00
261.09
256.88
251.53
257.25
243.10
283.75

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109753&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109753&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109753&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'George Udny Yule' @ 72.249.76.132






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95086410.28520
20.9111789.85590
30.864839.35460
40.8224778.89640
50.7801548.43870
60.7325457.92370
70.6923037.48840
80.6591887.13020
90.6273916.78630
100.5916966.40020
110.5577846.03340
120.5260445.690

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950864 & 10.2852 & 0 \tabularnewline
2 & 0.911178 & 9.8559 & 0 \tabularnewline
3 & 0.86483 & 9.3546 & 0 \tabularnewline
4 & 0.822477 & 8.8964 & 0 \tabularnewline
5 & 0.780154 & 8.4387 & 0 \tabularnewline
6 & 0.732545 & 7.9237 & 0 \tabularnewline
7 & 0.692303 & 7.4884 & 0 \tabularnewline
8 & 0.659188 & 7.1302 & 0 \tabularnewline
9 & 0.627391 & 6.7863 & 0 \tabularnewline
10 & 0.591696 & 6.4002 & 0 \tabularnewline
11 & 0.557784 & 6.0334 & 0 \tabularnewline
12 & 0.526044 & 5.69 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109753&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]0.950864[/C][C]10.2852[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.911178[/C][C]9.8559[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.86483[/C][C]9.3546[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.822477[/C][C]8.8964[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.780154[/C][C]8.4387[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.732545[/C][C]7.9237[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.692303[/C][C]7.4884[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.659188[/C][C]7.1302[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.627391[/C][C]6.7863[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.591696[/C][C]6.4002[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.557784[/C][C]6.0334[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.526044[/C][C]5.69[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109753&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109753&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
10.95086410.28520
20.9111789.85590
30.864839.35460
40.8224778.89640
50.7801548.43870
60.7325457.92370
70.6923037.48840
80.6591887.13020
90.6273916.78630
100.5916966.40020
110.5577846.03340
120.5260445.690






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95086410.28520
20.073390.79380.214451
3-0.081546-0.88210.189777
40.0054610.05910.4765
5-0.012663-0.1370.445645
6-0.082922-0.89690.185798
70.0412780.44650.328034
80.0718690.77740.219251
9-0.004925-0.05330.478805
10-0.065276-0.70610.240775
11-0.003214-0.03480.486164
120.0032580.03520.485972

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.950864 & 10.2852 & 0 \tabularnewline
2 & 0.07339 & 0.7938 & 0.214451 \tabularnewline
3 & -0.081546 & -0.8821 & 0.189777 \tabularnewline
4 & 0.005461 & 0.0591 & 0.4765 \tabularnewline
5 & -0.012663 & -0.137 & 0.445645 \tabularnewline
6 & -0.082922 & -0.8969 & 0.185798 \tabularnewline
7 & 0.041278 & 0.4465 & 0.328034 \tabularnewline
8 & 0.071869 & 0.7774 & 0.219251 \tabularnewline
9 & -0.004925 & -0.0533 & 0.478805 \tabularnewline
10 & -0.065276 & -0.7061 & 0.240775 \tabularnewline
11 & -0.003214 & -0.0348 & 0.486164 \tabularnewline
12 & 0.003258 & 0.0352 & 0.485972 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109753&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]0.950864[/C][C]10.2852[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.07339[/C][C]0.7938[/C][C]0.214451[/C][/ROW]
[ROW][C]3[/C][C]-0.081546[/C][C]-0.8821[/C][C]0.189777[/C][/ROW]
[ROW][C]4[/C][C]0.005461[/C][C]0.0591[/C][C]0.4765[/C][/ROW]
[ROW][C]5[/C][C]-0.012663[/C][C]-0.137[/C][C]0.445645[/C][/ROW]
[ROW][C]6[/C][C]-0.082922[/C][C]-0.8969[/C][C]0.185798[/C][/ROW]
[ROW][C]7[/C][C]0.041278[/C][C]0.4465[/C][C]0.328034[/C][/ROW]
[ROW][C]8[/C][C]0.071869[/C][C]0.7774[/C][C]0.219251[/C][/ROW]
[ROW][C]9[/C][C]-0.004925[/C][C]-0.0533[/C][C]0.478805[/C][/ROW]
[ROW][C]10[/C][C]-0.065276[/C][C]-0.7061[/C][C]0.240775[/C][/ROW]
[ROW][C]11[/C][C]-0.003214[/C][C]-0.0348[/C][C]0.486164[/C][/ROW]
[ROW][C]12[/C][C]0.003258[/C][C]0.0352[/C][C]0.485972[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109753&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109753&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
10.95086410.28520
20.073390.79380.214451
3-0.081546-0.88210.189777
40.0054610.05910.4765
5-0.012663-0.1370.445645
6-0.082922-0.89690.185798
70.0412780.44650.328034
80.0718690.77740.219251
9-0.004925-0.05330.478805
10-0.065276-0.70610.240775
11-0.003214-0.03480.486164
120.0032580.03520.485972


Figures (Output of Computation)

Input Parameters & R Code

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