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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 computationFri, 27 Nov 2009 14:44:37 -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/27/t1259358381q83orltqmcp3bz1.htm/, Retrieved Mon, 29 Apr 2024 22:40:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61297, Retrieved Mon, 29 Apr 2024 22:40:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

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] [ACF met d=D=0, la...] [2009-11-27 21:44:37] [7d2d29a9bcbcfc0ea3924e19a42d8563] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104.08
103.86
107.47
111.1
117.33
119.04
123.68
125.9
124.54
119.39
118.8
114.81
117.9
120.53
125.15
126.49
131.85
127.4
131.08
122.37
124.34
119.61
119.97
116.46
117.03
120.96
124.71
127.08
131.91
137.69
142.46
144.32
138.06
124.45
126.71
121.83
122.51
125.48
127.77
128.03
132.84
133.41
139.99
138.53
136.12
124.75
122.88
121.46
118.4
122.45
128.94
133.25
137.94
140.04
130.74
131.55
129.47
125.45
127.87
124.68

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=61297&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=61297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61297&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
10.8133876.30050
20.5762254.46341.8e-05
30.2781052.15420.017625
40.0327840.25390.400205
5-0.124678-0.96570.169023
6-0.158047-1.22420.112825
7-0.11321-0.87690.192013
80.0470980.36480.358265
90.2132981.65220.05186
100.3432932.65910.005015
110.4108633.18250.001157
120.4102893.17810.001172
130.3188532.46980.00819
140.1875281.45260.075775
150.0309340.23960.405723
16-0.093265-0.72240.236418
17-0.181713-1.40750.082213

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.813387 & 6.3005 & 0 \tabularnewline
2 & 0.576225 & 4.4634 & 1.8e-05 \tabularnewline
3 & 0.278105 & 2.1542 & 0.017625 \tabularnewline
4 & 0.032784 & 0.2539 & 0.400205 \tabularnewline
5 & -0.124678 & -0.9657 & 0.169023 \tabularnewline
6 & -0.158047 & -1.2242 & 0.112825 \tabularnewline
7 & -0.11321 & -0.8769 & 0.192013 \tabularnewline
8 & 0.047098 & 0.3648 & 0.358265 \tabularnewline
9 & 0.213298 & 1.6522 & 0.05186 \tabularnewline
10 & 0.343293 & 2.6591 & 0.005015 \tabularnewline
11 & 0.410863 & 3.1825 & 0.001157 \tabularnewline
12 & 0.410289 & 3.1781 & 0.001172 \tabularnewline
13 & 0.318853 & 2.4698 & 0.00819 \tabularnewline
14 & 0.187528 & 1.4526 & 0.075775 \tabularnewline
15 & 0.030934 & 0.2396 & 0.405723 \tabularnewline
16 & -0.093265 & -0.7224 & 0.236418 \tabularnewline
17 & -0.181713 & -1.4075 & 0.082213 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61297&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]0.813387[/C][C]6.3005[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.576225[/C][C]4.4634[/C][C]1.8e-05[/C][/ROW]
[ROW][C]3[/C][C]0.278105[/C][C]2.1542[/C][C]0.017625[/C][/ROW]
[ROW][C]4[/C][C]0.032784[/C][C]0.2539[/C][C]0.400205[/C][/ROW]
[ROW][C]5[/C][C]-0.124678[/C][C]-0.9657[/C][C]0.169023[/C][/ROW]
[ROW][C]6[/C][C]-0.158047[/C][C]-1.2242[/C][C]0.112825[/C][/ROW]
[ROW][C]7[/C][C]-0.11321[/C][C]-0.8769[/C][C]0.192013[/C][/ROW]
[ROW][C]8[/C][C]0.047098[/C][C]0.3648[/C][C]0.358265[/C][/ROW]
[ROW][C]9[/C][C]0.213298[/C][C]1.6522[/C][C]0.05186[/C][/ROW]
[ROW][C]10[/C][C]0.343293[/C][C]2.6591[/C][C]0.005015[/C][/ROW]
[ROW][C]11[/C][C]0.410863[/C][C]3.1825[/C][C]0.001157[/C][/ROW]
[ROW][C]12[/C][C]0.410289[/C][C]3.1781[/C][C]0.001172[/C][/ROW]
[ROW][C]13[/C][C]0.318853[/C][C]2.4698[/C][C]0.00819[/C][/ROW]
[ROW][C]14[/C][C]0.187528[/C][C]1.4526[/C][C]0.075775[/C][/ROW]
[ROW][C]15[/C][C]0.030934[/C][C]0.2396[/C][C]0.405723[/C][/ROW]
[ROW][C]16[/C][C]-0.093265[/C][C]-0.7224[/C][C]0.236418[/C][/ROW]
[ROW][C]17[/C][C]-0.181713[/C][C]-1.4075[/C][C]0.082213[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61297&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
10.8133876.30050
20.5762254.46341.8e-05
30.2781052.15420.017625
40.0327840.25390.400205
5-0.124678-0.96570.169023
6-0.158047-1.22420.112825
7-0.11321-0.87690.192013
80.0470980.36480.358265
90.2132981.65220.05186
100.3432932.65910.005015
110.4108633.18250.001157
120.4102893.17810.001172
130.3188532.46980.00819
140.1875281.45260.075775
150.0309340.23960.405723
16-0.093265-0.72240.236418
17-0.181713-1.40750.082213






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8133876.30050
2-0.252286-1.95420.027671
3-0.327041-2.53320.006966
4-0.028679-0.22220.412476
50.0640980.49650.310678
60.1347741.0440.150347
70.0324710.25150.401137
80.256291.98520.025849
90.0793550.61470.270545
10-0.018999-0.14720.441749
110.0586910.45460.325511
120.0743090.57560.28352
13-0.067584-0.52350.301277
14-0.046883-0.36320.358883
15-0.029618-0.22940.409661
16-0.009981-0.07730.469316
17-0.107432-0.83220.204308

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.813387 & 6.3005 & 0 \tabularnewline
2 & -0.252286 & -1.9542 & 0.027671 \tabularnewline
3 & -0.327041 & -2.5332 & 0.006966 \tabularnewline
4 & -0.028679 & -0.2222 & 0.412476 \tabularnewline
5 & 0.064098 & 0.4965 & 0.310678 \tabularnewline
6 & 0.134774 & 1.044 & 0.150347 \tabularnewline
7 & 0.032471 & 0.2515 & 0.401137 \tabularnewline
8 & 0.25629 & 1.9852 & 0.025849 \tabularnewline
9 & 0.079355 & 0.6147 & 0.270545 \tabularnewline
10 & -0.018999 & -0.1472 & 0.441749 \tabularnewline
11 & 0.058691 & 0.4546 & 0.325511 \tabularnewline
12 & 0.074309 & 0.5756 & 0.28352 \tabularnewline
13 & -0.067584 & -0.5235 & 0.301277 \tabularnewline
14 & -0.046883 & -0.3632 & 0.358883 \tabularnewline
15 & -0.029618 & -0.2294 & 0.409661 \tabularnewline
16 & -0.009981 & -0.0773 & 0.469316 \tabularnewline
17 & -0.107432 & -0.8322 & 0.204308 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61297&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]0.813387[/C][C]6.3005[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.252286[/C][C]-1.9542[/C][C]0.027671[/C][/ROW]
[ROW][C]3[/C][C]-0.327041[/C][C]-2.5332[/C][C]0.006966[/C][/ROW]
[ROW][C]4[/C][C]-0.028679[/C][C]-0.2222[/C][C]0.412476[/C][/ROW]
[ROW][C]5[/C][C]0.064098[/C][C]0.4965[/C][C]0.310678[/C][/ROW]
[ROW][C]6[/C][C]0.134774[/C][C]1.044[/C][C]0.150347[/C][/ROW]
[ROW][C]7[/C][C]0.032471[/C][C]0.2515[/C][C]0.401137[/C][/ROW]
[ROW][C]8[/C][C]0.25629[/C][C]1.9852[/C][C]0.025849[/C][/ROW]
[ROW][C]9[/C][C]0.079355[/C][C]0.6147[/C][C]0.270545[/C][/ROW]
[ROW][C]10[/C][C]-0.018999[/C][C]-0.1472[/C][C]0.441749[/C][/ROW]
[ROW][C]11[/C][C]0.058691[/C][C]0.4546[/C][C]0.325511[/C][/ROW]
[ROW][C]12[/C][C]0.074309[/C][C]0.5756[/C][C]0.28352[/C][/ROW]
[ROW][C]13[/C][C]-0.067584[/C][C]-0.5235[/C][C]0.301277[/C][/ROW]
[ROW][C]14[/C][C]-0.046883[/C][C]-0.3632[/C][C]0.358883[/C][/ROW]
[ROW][C]15[/C][C]-0.029618[/C][C]-0.2294[/C][C]0.409661[/C][/ROW]
[ROW][C]16[/C][C]-0.009981[/C][C]-0.0773[/C][C]0.469316[/C][/ROW]
[ROW][C]17[/C][C]-0.107432[/C][C]-0.8322[/C][C]0.204308[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61297&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61297&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
10.8133876.30050
2-0.252286-1.95420.027671
3-0.327041-2.53320.006966
4-0.028679-0.22220.412476
50.0640980.49650.310678
60.1347741.0440.150347
70.0324710.25150.401137
80.256291.98520.025849
90.0793550.61470.270545
10-0.018999-0.14720.441749
110.0586910.45460.325511
120.0743090.57560.28352
13-0.067584-0.52350.301277
14-0.046883-0.36320.358883
15-0.029618-0.22940.409661
16-0.009981-0.07730.469316
17-0.107432-0.83220.204308


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')