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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 computationMon, 05 Dec 2011 09:12:41 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/05/t1323094579jkr8qo97m3zbnnx.htm/, Retrieved Thu, 28 Mar 2024 22:19:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=150929, Retrieved Thu, 28 Mar 2024 22:19:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Univariate Data Series] [] [2011-11-25 14:57:13] [493236dcc414c5f9e1823f06b33a5ad6]
- RMPD      [(Partial) Autocorrelation Function] [] [2011-12-05 14:12:41] [75a32e1bc492240bc1028714aca23077] [Current]
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Dataseries X:
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.457




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150929&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150929&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150929&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.080402-0.46880.321095
2-0.500127-2.91620.003117
3-0.170426-0.99370.163684
40.2506581.46160.07652
50.3089221.80130.040265
6-0.223941-1.30580.100195
7-0.221307-1.29040.102804
8-0.045032-0.26260.397229
90.1525260.88940.190027
100.2957831.72470.046832
11-0.094332-0.550.292942
12-0.413993-2.4140.010656
130.0779510.45450.32617
140.313561.82840.038141
15-0.010075-0.05870.476748
16-0.165233-0.96350.171058
17-0.106738-0.62240.26892

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.080402 & -0.4688 & 0.321095 \tabularnewline
2 & -0.500127 & -2.9162 & 0.003117 \tabularnewline
3 & -0.170426 & -0.9937 & 0.163684 \tabularnewline
4 & 0.250658 & 1.4616 & 0.07652 \tabularnewline
5 & 0.308922 & 1.8013 & 0.040265 \tabularnewline
6 & -0.223941 & -1.3058 & 0.100195 \tabularnewline
7 & -0.221307 & -1.2904 & 0.102804 \tabularnewline
8 & -0.045032 & -0.2626 & 0.397229 \tabularnewline
9 & 0.152526 & 0.8894 & 0.190027 \tabularnewline
10 & 0.295783 & 1.7247 & 0.046832 \tabularnewline
11 & -0.094332 & -0.55 & 0.292942 \tabularnewline
12 & -0.413993 & -2.414 & 0.010656 \tabularnewline
13 & 0.077951 & 0.4545 & 0.32617 \tabularnewline
14 & 0.31356 & 1.8284 & 0.038141 \tabularnewline
15 & -0.010075 & -0.0587 & 0.476748 \tabularnewline
16 & -0.165233 & -0.9635 & 0.171058 \tabularnewline
17 & -0.106738 & -0.6224 & 0.26892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150929&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]-0.080402[/C][C]-0.4688[/C][C]0.321095[/C][/ROW]
[ROW][C]2[/C][C]-0.500127[/C][C]-2.9162[/C][C]0.003117[/C][/ROW]
[ROW][C]3[/C][C]-0.170426[/C][C]-0.9937[/C][C]0.163684[/C][/ROW]
[ROW][C]4[/C][C]0.250658[/C][C]1.4616[/C][C]0.07652[/C][/ROW]
[ROW][C]5[/C][C]0.308922[/C][C]1.8013[/C][C]0.040265[/C][/ROW]
[ROW][C]6[/C][C]-0.223941[/C][C]-1.3058[/C][C]0.100195[/C][/ROW]
[ROW][C]7[/C][C]-0.221307[/C][C]-1.2904[/C][C]0.102804[/C][/ROW]
[ROW][C]8[/C][C]-0.045032[/C][C]-0.2626[/C][C]0.397229[/C][/ROW]
[ROW][C]9[/C][C]0.152526[/C][C]0.8894[/C][C]0.190027[/C][/ROW]
[ROW][C]10[/C][C]0.295783[/C][C]1.7247[/C][C]0.046832[/C][/ROW]
[ROW][C]11[/C][C]-0.094332[/C][C]-0.55[/C][C]0.292942[/C][/ROW]
[ROW][C]12[/C][C]-0.413993[/C][C]-2.414[/C][C]0.010656[/C][/ROW]
[ROW][C]13[/C][C]0.077951[/C][C]0.4545[/C][C]0.32617[/C][/ROW]
[ROW][C]14[/C][C]0.31356[/C][C]1.8284[/C][C]0.038141[/C][/ROW]
[ROW][C]15[/C][C]-0.010075[/C][C]-0.0587[/C][C]0.476748[/C][/ROW]
[ROW][C]16[/C][C]-0.165233[/C][C]-0.9635[/C][C]0.171058[/C][/ROW]
[ROW][C]17[/C][C]-0.106738[/C][C]-0.6224[/C][C]0.26892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150929&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150929&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
1-0.080402-0.46880.321095
2-0.500127-2.91620.003117
3-0.170426-0.99370.163684
40.2506581.46160.07652
50.3089221.80130.040265
6-0.223941-1.30580.100195
7-0.221307-1.29040.102804
8-0.045032-0.26260.397229
90.1525260.88940.190027
100.2957831.72470.046832
11-0.094332-0.550.292942
12-0.413993-2.4140.010656
130.0779510.45450.32617
140.313561.82840.038141
15-0.010075-0.05870.476748
16-0.165233-0.96350.171058
17-0.106738-0.62240.26892







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.080402-0.46880.321095
2-0.509888-2.97310.002693
3-0.370138-2.15830.019029
4-0.172478-1.00570.16083
50.1073040.62570.267849
6-0.132011-0.76980.223381
7-0.036145-0.21080.417167
8-0.244923-1.42810.081188
9-0.224124-1.30690.100016
100.126980.74040.232067
110.1166390.68010.250517
12-0.241974-1.41090.083674
130.0304670.17760.430026
14-0.031298-0.18250.428139
15-0.231193-1.34810.093274
160.0786190.45840.324783
170.050340.29350.38545

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.080402 & -0.4688 & 0.321095 \tabularnewline
2 & -0.509888 & -2.9731 & 0.002693 \tabularnewline
3 & -0.370138 & -2.1583 & 0.019029 \tabularnewline
4 & -0.172478 & -1.0057 & 0.16083 \tabularnewline
5 & 0.107304 & 0.6257 & 0.267849 \tabularnewline
6 & -0.132011 & -0.7698 & 0.223381 \tabularnewline
7 & -0.036145 & -0.2108 & 0.417167 \tabularnewline
8 & -0.244923 & -1.4281 & 0.081188 \tabularnewline
9 & -0.224124 & -1.3069 & 0.100016 \tabularnewline
10 & 0.12698 & 0.7404 & 0.232067 \tabularnewline
11 & 0.116639 & 0.6801 & 0.250517 \tabularnewline
12 & -0.241974 & -1.4109 & 0.083674 \tabularnewline
13 & 0.030467 & 0.1776 & 0.430026 \tabularnewline
14 & -0.031298 & -0.1825 & 0.428139 \tabularnewline
15 & -0.231193 & -1.3481 & 0.093274 \tabularnewline
16 & 0.078619 & 0.4584 & 0.324783 \tabularnewline
17 & 0.05034 & 0.2935 & 0.38545 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=150929&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]-0.080402[/C][C]-0.4688[/C][C]0.321095[/C][/ROW]
[ROW][C]2[/C][C]-0.509888[/C][C]-2.9731[/C][C]0.002693[/C][/ROW]
[ROW][C]3[/C][C]-0.370138[/C][C]-2.1583[/C][C]0.019029[/C][/ROW]
[ROW][C]4[/C][C]-0.172478[/C][C]-1.0057[/C][C]0.16083[/C][/ROW]
[ROW][C]5[/C][C]0.107304[/C][C]0.6257[/C][C]0.267849[/C][/ROW]
[ROW][C]6[/C][C]-0.132011[/C][C]-0.7698[/C][C]0.223381[/C][/ROW]
[ROW][C]7[/C][C]-0.036145[/C][C]-0.2108[/C][C]0.417167[/C][/ROW]
[ROW][C]8[/C][C]-0.244923[/C][C]-1.4281[/C][C]0.081188[/C][/ROW]
[ROW][C]9[/C][C]-0.224124[/C][C]-1.3069[/C][C]0.100016[/C][/ROW]
[ROW][C]10[/C][C]0.12698[/C][C]0.7404[/C][C]0.232067[/C][/ROW]
[ROW][C]11[/C][C]0.116639[/C][C]0.6801[/C][C]0.250517[/C][/ROW]
[ROW][C]12[/C][C]-0.241974[/C][C]-1.4109[/C][C]0.083674[/C][/ROW]
[ROW][C]13[/C][C]0.030467[/C][C]0.1776[/C][C]0.430026[/C][/ROW]
[ROW][C]14[/C][C]-0.031298[/C][C]-0.1825[/C][C]0.428139[/C][/ROW]
[ROW][C]15[/C][C]-0.231193[/C][C]-1.3481[/C][C]0.093274[/C][/ROW]
[ROW][C]16[/C][C]0.078619[/C][C]0.4584[/C][C]0.324783[/C][/ROW]
[ROW][C]17[/C][C]0.05034[/C][C]0.2935[/C][C]0.38545[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=150929&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=150929&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
1-0.080402-0.46880.321095
2-0.509888-2.97310.002693
3-0.370138-2.15830.019029
4-0.172478-1.00570.16083
50.1073040.62570.267849
6-0.132011-0.76980.223381
7-0.036145-0.21080.417167
8-0.244923-1.42810.081188
9-0.224124-1.30690.100016
100.126980.74040.232067
110.1166390.68010.250517
12-0.241974-1.41090.083674
130.0304670.17760.430026
14-0.031298-0.18250.428139
15-0.231193-1.34810.093274
160.0786190.45840.324783
170.050340.29350.38545



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 2 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')