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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, 26 Nov 2009 12:14:52 -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/t12592629177fp0hdew6rih24q.htm/, Retrieved Mon, 29 Apr 2024 00:22:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60303, Retrieved Mon, 29 Apr 2024 00:22:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151

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] [Industriële produ...] [2009-11-26 19:14:52] [fcf610eda12f49b9bf9c81ec9669e97a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.7
24.7
24.2
23.6
24.4
22.5
19.4
18.1
18.1
20.7
19.1
18.3
16.9
17.9
20.2
21.2
23.8
24
26.6
25.3
27.6
24.7
26.6
24.4
24.6
26
24.8
24
22.7
23
24.1
24
22.7
22.6
23.1
24.4
23
22
21.3
21.5
21.3
23.2
21.8
23.3
21
22.4
20.4
19.9
21.3
18.9
15.6
12.5
7.8
5.5
4
3.3
3.7
3.1
5
6.3

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=60303&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=60303&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60303&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
10.9157946.34480
20.8316765.7620
30.6902234.7828e-06
40.5728093.96850.00012
50.4324812.99630.002158
60.2971732.05890.022477
70.1763781.2220.113841
80.0826450.57260.2848
90.0233150.16150.436177
10-0.027859-0.1930.423881
11-0.053308-0.36930.356753
12-0.079115-0.54810.293074
13-0.074964-0.51940.302946
14-0.065078-0.45090.327055
15-0.028191-0.19530.422987
16-0.012149-0.08420.466634
17-9.1e-05-6e-040.49975

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.915794 & 6.3448 & 0 \tabularnewline
2 & 0.831676 & 5.762 & 0 \tabularnewline
3 & 0.690223 & 4.782 & 8e-06 \tabularnewline
4 & 0.572809 & 3.9685 & 0.00012 \tabularnewline
5 & 0.432481 & 2.9963 & 0.002158 \tabularnewline
6 & 0.297173 & 2.0589 & 0.022477 \tabularnewline
7 & 0.176378 & 1.222 & 0.113841 \tabularnewline
8 & 0.082645 & 0.5726 & 0.2848 \tabularnewline
9 & 0.023315 & 0.1615 & 0.436177 \tabularnewline
10 & -0.027859 & -0.193 & 0.423881 \tabularnewline
11 & -0.053308 & -0.3693 & 0.356753 \tabularnewline
12 & -0.079115 & -0.5481 & 0.293074 \tabularnewline
13 & -0.074964 & -0.5194 & 0.302946 \tabularnewline
14 & -0.065078 & -0.4509 & 0.327055 \tabularnewline
15 & -0.028191 & -0.1953 & 0.422987 \tabularnewline
16 & -0.012149 & -0.0842 & 0.466634 \tabularnewline
17 & -9.1e-05 & -6e-04 & 0.49975 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60303&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]0.915794[/C][C]6.3448[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.831676[/C][C]5.762[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.690223[/C][C]4.782[/C][C]8e-06[/C][/ROW]
[ROW][C]4[/C][C]0.572809[/C][C]3.9685[/C][C]0.00012[/C][/ROW]
[ROW][C]5[/C][C]0.432481[/C][C]2.9963[/C][C]0.002158[/C][/ROW]
[ROW][C]6[/C][C]0.297173[/C][C]2.0589[/C][C]0.022477[/C][/ROW]
[ROW][C]7[/C][C]0.176378[/C][C]1.222[/C][C]0.113841[/C][/ROW]
[ROW][C]8[/C][C]0.082645[/C][C]0.5726[/C][C]0.2848[/C][/ROW]
[ROW][C]9[/C][C]0.023315[/C][C]0.1615[/C][C]0.436177[/C][/ROW]
[ROW][C]10[/C][C]-0.027859[/C][C]-0.193[/C][C]0.423881[/C][/ROW]
[ROW][C]11[/C][C]-0.053308[/C][C]-0.3693[/C][C]0.356753[/C][/ROW]
[ROW][C]12[/C][C]-0.079115[/C][C]-0.5481[/C][C]0.293074[/C][/ROW]
[ROW][C]13[/C][C]-0.074964[/C][C]-0.5194[/C][C]0.302946[/C][/ROW]
[ROW][C]14[/C][C]-0.065078[/C][C]-0.4509[/C][C]0.327055[/C][/ROW]
[ROW][C]15[/C][C]-0.028191[/C][C]-0.1953[/C][C]0.422987[/C][/ROW]
[ROW][C]16[/C][C]-0.012149[/C][C]-0.0842[/C][C]0.466634[/C][/ROW]
[ROW][C]17[/C][C]-9.1e-05[/C][C]-6e-04[/C][C]0.49975[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60303&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60303&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
10.9157946.34480
20.8316765.7620
30.6902234.7828e-06
40.5728093.96850.00012
50.4324812.99630.002158
60.2971732.05890.022477
70.1763781.2220.113841
80.0826450.57260.2848
90.0233150.16150.436177
10-0.027859-0.1930.423881
11-0.053308-0.36930.356753
12-0.079115-0.54810.293074
13-0.074964-0.51940.302946
14-0.065078-0.45090.327055
15-0.028191-0.19530.422987
16-0.012149-0.08420.466634
17-9.1e-05-6e-040.49975






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9157946.34480
2-0.043405-0.30070.382464
3-0.40201-2.78520.003817
40.0747660.5180.30342
5-0.11531-0.79890.214145
6-0.175842-1.21830.114538
70.0970370.67230.25231
80.0819440.56770.286434
90.0610780.42320.337034
10-0.073812-0.51140.305714
110.0250540.17360.431462
12-0.056656-0.39250.348205
130.0472910.32760.372305
140.0630050.43650.332212
150.1069170.74070.23123
16-0.135386-0.9380.176474
17-0.115442-0.79980.213881

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.915794 & 6.3448 & 0 \tabularnewline
2 & -0.043405 & -0.3007 & 0.382464 \tabularnewline
3 & -0.40201 & -2.7852 & 0.003817 \tabularnewline
4 & 0.074766 & 0.518 & 0.30342 \tabularnewline
5 & -0.11531 & -0.7989 & 0.214145 \tabularnewline
6 & -0.175842 & -1.2183 & 0.114538 \tabularnewline
7 & 0.097037 & 0.6723 & 0.25231 \tabularnewline
8 & 0.081944 & 0.5677 & 0.286434 \tabularnewline
9 & 0.061078 & 0.4232 & 0.337034 \tabularnewline
10 & -0.073812 & -0.5114 & 0.305714 \tabularnewline
11 & 0.025054 & 0.1736 & 0.431462 \tabularnewline
12 & -0.056656 & -0.3925 & 0.348205 \tabularnewline
13 & 0.047291 & 0.3276 & 0.372305 \tabularnewline
14 & 0.063005 & 0.4365 & 0.332212 \tabularnewline
15 & 0.106917 & 0.7407 & 0.23123 \tabularnewline
16 & -0.135386 & -0.938 & 0.176474 \tabularnewline
17 & -0.115442 & -0.7998 & 0.213881 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60303&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]0.915794[/C][C]6.3448[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.043405[/C][C]-0.3007[/C][C]0.382464[/C][/ROW]
[ROW][C]3[/C][C]-0.40201[/C][C]-2.7852[/C][C]0.003817[/C][/ROW]
[ROW][C]4[/C][C]0.074766[/C][C]0.518[/C][C]0.30342[/C][/ROW]
[ROW][C]5[/C][C]-0.11531[/C][C]-0.7989[/C][C]0.214145[/C][/ROW]
[ROW][C]6[/C][C]-0.175842[/C][C]-1.2183[/C][C]0.114538[/C][/ROW]
[ROW][C]7[/C][C]0.097037[/C][C]0.6723[/C][C]0.25231[/C][/ROW]
[ROW][C]8[/C][C]0.081944[/C][C]0.5677[/C][C]0.286434[/C][/ROW]
[ROW][C]9[/C][C]0.061078[/C][C]0.4232[/C][C]0.337034[/C][/ROW]
[ROW][C]10[/C][C]-0.073812[/C][C]-0.5114[/C][C]0.305714[/C][/ROW]
[ROW][C]11[/C][C]0.025054[/C][C]0.1736[/C][C]0.431462[/C][/ROW]
[ROW][C]12[/C][C]-0.056656[/C][C]-0.3925[/C][C]0.348205[/C][/ROW]
[ROW][C]13[/C][C]0.047291[/C][C]0.3276[/C][C]0.372305[/C][/ROW]
[ROW][C]14[/C][C]0.063005[/C][C]0.4365[/C][C]0.332212[/C][/ROW]
[ROW][C]15[/C][C]0.106917[/C][C]0.7407[/C][C]0.23123[/C][/ROW]
[ROW][C]16[/C][C]-0.135386[/C][C]-0.938[/C][C]0.176474[/C][/ROW]
[ROW][C]17[/C][C]-0.115442[/C][C]-0.7998[/C][C]0.213881[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60303&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60303&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
10.9157946.34480
2-0.043405-0.30070.382464
3-0.40201-2.78520.003817
40.0747660.5180.30342
5-0.11531-0.79890.214145
6-0.175842-1.21830.114538
70.0970370.67230.25231
80.0819440.56770.286434
90.0610780.42320.337034
10-0.073812-0.51140.305714
110.0250540.17360.431462
12-0.056656-0.39250.348205
130.0472910.32760.372305
140.0630050.43650.332212
150.1069170.74070.23123
16-0.135386-0.9380.176474
17-0.115442-0.79980.213881


Figures (Output of Computation)

Input Parameters & R Code

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