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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 12:32:52 -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/Dec/03/t1259868870ujxilb2gu95kzkv.htm/, Retrieved Fri, 26 Apr 2024 01:35:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63090, Retrieved Fri, 26 Apr 2024 01:35:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
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 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [] [2009-12-03 19:32:52] [ed082d38031561faed979d8cebfeba4d] [Current]
-   P         [(Partial) Autocorrelation Function] [] [2009-12-04 14:01:50] [325e037ef8beb77178124dff9c2e015a]
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Dataseries X:
1915
1843
1761
2858
3968
5061
4661
4269
3857
3568
3274
2987
1683
1381
1071
2772
4485
6181
5479
4782
4067
3489
2903
2330
1736
1483
1242
2334
3423
4523
3986
3462
2908
2575
2237
1904
1610
1251
941
2450
3946
5409
4741
4069
3539
3189
2960
2704
1697
1598
1456
2316
3083
4158
3469
2892
2578
2233
1947
2049




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=63090&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=63090&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63090&T=0

As an alternative you can also use a 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
10.7927976.1410
20.3772362.92210.002448
3-0.083682-0.64820.259666
4-0.384775-2.98050.002076
5-0.537663-4.16475.1e-05
6-0.547582-4.24163.9e-05
7-0.488893-3.7870.000178
8-0.336388-2.60570.005774
9-0.085189-0.65990.255931
100.2695532.08790.020528
110.5743184.44861.9e-05
120.7071415.47750
130.5350694.14465.4e-05
140.199651.54650.063624
15-0.167692-1.29890.099467
16-0.392911-3.04350.001734
17-0.485046-3.75710.000196

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.792797 & 6.141 & 0 \tabularnewline
2 & 0.377236 & 2.9221 & 0.002448 \tabularnewline
3 & -0.083682 & -0.6482 & 0.259666 \tabularnewline
4 & -0.384775 & -2.9805 & 0.002076 \tabularnewline
5 & -0.537663 & -4.1647 & 5.1e-05 \tabularnewline
6 & -0.547582 & -4.2416 & 3.9e-05 \tabularnewline
7 & -0.488893 & -3.787 & 0.000178 \tabularnewline
8 & -0.336388 & -2.6057 & 0.005774 \tabularnewline
9 & -0.085189 & -0.6599 & 0.255931 \tabularnewline
10 & 0.269553 & 2.0879 & 0.020528 \tabularnewline
11 & 0.574318 & 4.4486 & 1.9e-05 \tabularnewline
12 & 0.707141 & 5.4775 & 0 \tabularnewline
13 & 0.535069 & 4.1446 & 5.4e-05 \tabularnewline
14 & 0.19965 & 1.5465 & 0.063624 \tabularnewline
15 & -0.167692 & -1.2989 & 0.099467 \tabularnewline
16 & -0.392911 & -3.0435 & 0.001734 \tabularnewline
17 & -0.485046 & -3.7571 & 0.000196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63090&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]0.792797[/C][C]6.141[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.377236[/C][C]2.9221[/C][C]0.002448[/C][/ROW]
[ROW][C]3[/C][C]-0.083682[/C][C]-0.6482[/C][C]0.259666[/C][/ROW]
[ROW][C]4[/C][C]-0.384775[/C][C]-2.9805[/C][C]0.002076[/C][/ROW]
[ROW][C]5[/C][C]-0.537663[/C][C]-4.1647[/C][C]5.1e-05[/C][/ROW]
[ROW][C]6[/C][C]-0.547582[/C][C]-4.2416[/C][C]3.9e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.488893[/C][C]-3.787[/C][C]0.000178[/C][/ROW]
[ROW][C]8[/C][C]-0.336388[/C][C]-2.6057[/C][C]0.005774[/C][/ROW]
[ROW][C]9[/C][C]-0.085189[/C][C]-0.6599[/C][C]0.255931[/C][/ROW]
[ROW][C]10[/C][C]0.269553[/C][C]2.0879[/C][C]0.020528[/C][/ROW]
[ROW][C]11[/C][C]0.574318[/C][C]4.4486[/C][C]1.9e-05[/C][/ROW]
[ROW][C]12[/C][C]0.707141[/C][C]5.4775[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.535069[/C][C]4.1446[/C][C]5.4e-05[/C][/ROW]
[ROW][C]14[/C][C]0.19965[/C][C]1.5465[/C][C]0.063624[/C][/ROW]
[ROW][C]15[/C][C]-0.167692[/C][C]-1.2989[/C][C]0.099467[/C][/ROW]
[ROW][C]16[/C][C]-0.392911[/C][C]-3.0435[/C][C]0.001734[/C][/ROW]
[ROW][C]17[/C][C]-0.485046[/C][C]-3.7571[/C][C]0.000196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63090&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63090&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7927976.1410
20.3772362.92210.002448
3-0.083682-0.64820.259666
4-0.384775-2.98050.002076
5-0.537663-4.16475.1e-05
6-0.547582-4.24163.9e-05
7-0.488893-3.7870.000178
8-0.336388-2.60570.005774
9-0.085189-0.65990.255931
100.2695532.08790.020528
110.5743184.44861.9e-05
120.7071415.47750
130.5350694.14465.4e-05
140.199651.54650.063624
15-0.167692-1.29890.099467
16-0.392911-3.04350.001734
17-0.485046-3.75710.000196







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7927976.1410
2-0.676475-5.241e-06
3-0.242009-1.87460.032859
40.2027711.57070.060761
5-0.408825-3.16670.001212
6-0.155148-1.20180.117087
7-0.15228-1.17960.121417
80.0299070.23170.408797
90.2450171.89790.031262
100.32622.52670.007084
11-0.049124-0.38050.352454
120.0188290.14590.442263
13-0.380611-2.94820.002274
140.2049251.58730.058846
150.0316250.2450.40366
16-0.100986-0.78220.218576
17-0.014604-0.11310.455154

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.792797 & 6.141 & 0 \tabularnewline
2 & -0.676475 & -5.24 & 1e-06 \tabularnewline
3 & -0.242009 & -1.8746 & 0.032859 \tabularnewline
4 & 0.202771 & 1.5707 & 0.060761 \tabularnewline
5 & -0.408825 & -3.1667 & 0.001212 \tabularnewline
6 & -0.155148 & -1.2018 & 0.117087 \tabularnewline
7 & -0.15228 & -1.1796 & 0.121417 \tabularnewline
8 & 0.029907 & 0.2317 & 0.408797 \tabularnewline
9 & 0.245017 & 1.8979 & 0.031262 \tabularnewline
10 & 0.3262 & 2.5267 & 0.007084 \tabularnewline
11 & -0.049124 & -0.3805 & 0.352454 \tabularnewline
12 & 0.018829 & 0.1459 & 0.442263 \tabularnewline
13 & -0.380611 & -2.9482 & 0.002274 \tabularnewline
14 & 0.204925 & 1.5873 & 0.058846 \tabularnewline
15 & 0.031625 & 0.245 & 0.40366 \tabularnewline
16 & -0.100986 & -0.7822 & 0.218576 \tabularnewline
17 & -0.014604 & -0.1131 & 0.455154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63090&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]0.792797[/C][C]6.141[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.676475[/C][C]-5.24[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]-0.242009[/C][C]-1.8746[/C][C]0.032859[/C][/ROW]
[ROW][C]4[/C][C]0.202771[/C][C]1.5707[/C][C]0.060761[/C][/ROW]
[ROW][C]5[/C][C]-0.408825[/C][C]-3.1667[/C][C]0.001212[/C][/ROW]
[ROW][C]6[/C][C]-0.155148[/C][C]-1.2018[/C][C]0.117087[/C][/ROW]
[ROW][C]7[/C][C]-0.15228[/C][C]-1.1796[/C][C]0.121417[/C][/ROW]
[ROW][C]8[/C][C]0.029907[/C][C]0.2317[/C][C]0.408797[/C][/ROW]
[ROW][C]9[/C][C]0.245017[/C][C]1.8979[/C][C]0.031262[/C][/ROW]
[ROW][C]10[/C][C]0.3262[/C][C]2.5267[/C][C]0.007084[/C][/ROW]
[ROW][C]11[/C][C]-0.049124[/C][C]-0.3805[/C][C]0.352454[/C][/ROW]
[ROW][C]12[/C][C]0.018829[/C][C]0.1459[/C][C]0.442263[/C][/ROW]
[ROW][C]13[/C][C]-0.380611[/C][C]-2.9482[/C][C]0.002274[/C][/ROW]
[ROW][C]14[/C][C]0.204925[/C][C]1.5873[/C][C]0.058846[/C][/ROW]
[ROW][C]15[/C][C]0.031625[/C][C]0.245[/C][C]0.40366[/C][/ROW]
[ROW][C]16[/C][C]-0.100986[/C][C]-0.7822[/C][C]0.218576[/C][/ROW]
[ROW][C]17[/C][C]-0.014604[/C][C]-0.1131[/C][C]0.455154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63090&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63090&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7927976.1410
2-0.676475-5.241e-06
3-0.242009-1.87460.032859
40.2027711.57070.060761
5-0.408825-3.16670.001212
6-0.155148-1.20180.117087
7-0.15228-1.17960.121417
80.0299070.23170.408797
90.2450171.89790.031262
100.32622.52670.007084
11-0.049124-0.38050.352454
120.0188290.14590.442263
13-0.380611-2.94820.002274
140.2049251.58730.058846
150.0316250.2450.40366
16-0.100986-0.78220.218576
17-0.014604-0.11310.455154



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