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Author's title

Time Series analysis (degree of non-seasonal differencing=1) - King Size-si...

Author

*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 05 Jun 2009 10:06:28 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Jun/05/t1244218037jqlgyahw6atx6n6.htm/, Retrieved Fri, 10 May 2024 20:21:20 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41884, Retrieved Fri, 10 May 2024 20:21:20 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

116

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Univariate Data Series] [Tijdsreeks - Aant...] [2009-05-07 18:57:04] [93a1509a65b1df20cd27a0290949f2b0]
- RMPD    [(Partial) Autocorrelation Function] [Time Series analy...] [2009-06-05 16:06:28] [2f928979fcb5db36e984611041f4b2ce] [Current]

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Dataseries X:

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Histogram

Boxplots

2,98
2,98
2,98
3,03
3,07
3,08
3,08
3,08
3,08
3,08
3,08
3,08
3,08
3,08
3,12
3,15
3,15
3,15
3,15
3,16
3,19
3,2
3,2
3,2
3,21
3,21
3,21
3,21
3,21
3,28
3,3
3,3
3,3
3,3
3,3
3,3
3,3
3,45
3,49
3,5
3,54
3,64
3,67
3,67
3,68
3,68
3,68
3,68
3,7
3,83
3,87
3,87
3,87
3,87
3,87
3,87
3,87
3,87
3,87
3,88
3,88
3,88
3,88
3,88
3,88
3,89
3,89
3,91
3,95
3,99
3,99
3,99

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=41884&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=41884&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41884&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.257662	2.1711	0.016634
2	-0.116099	-0.9783	0.165632
3	-0.032476	-0.2736	0.392575
4	0.086423	0.7282	0.234439
5	-0.077733	-0.655	0.257296
6	-0.163489	-1.3776	0.08633
7	-0.034232	-0.2884	0.386925
8	0.243447	2.0513	0.021963
9	0.051403	0.4331	0.333116
10	-0.049782	-0.4195	0.33807
11	0.05818	0.4902	0.312742
12	0.281	2.3677	0.010312
13	-0.073179	-0.6166	0.269729
14	-0.183467	-1.5459	0.063285
15	-0.135048	-1.1379	0.129487
16	-0.13166	-1.1094	0.135504
17	-0.078556	-0.6619	0.25508
18	-0.080311	-0.6767	0.250393

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.257662 & 2.1711 & 0.016634 \tabularnewline
2 & -0.116099 & -0.9783 & 0.165632 \tabularnewline
3 & -0.032476 & -0.2736 & 0.392575 \tabularnewline
4 & 0.086423 & 0.7282 & 0.234439 \tabularnewline
5 & -0.077733 & -0.655 & 0.257296 \tabularnewline
6 & -0.163489 & -1.3776 & 0.08633 \tabularnewline
7 & -0.034232 & -0.2884 & 0.386925 \tabularnewline
8 & 0.243447 & 2.0513 & 0.021963 \tabularnewline
9 & 0.051403 & 0.4331 & 0.333116 \tabularnewline
10 & -0.049782 & -0.4195 & 0.33807 \tabularnewline
11 & 0.05818 & 0.4902 & 0.312742 \tabularnewline
12 & 0.281 & 2.3677 & 0.010312 \tabularnewline
13 & -0.073179 & -0.6166 & 0.269729 \tabularnewline
14 & -0.183467 & -1.5459 & 0.063285 \tabularnewline
15 & -0.135048 & -1.1379 & 0.129487 \tabularnewline
16 & -0.13166 & -1.1094 & 0.135504 \tabularnewline
17 & -0.078556 & -0.6619 & 0.25508 \tabularnewline
18 & -0.080311 & -0.6767 & 0.250393 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41884&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]0.257662[/C][C]2.1711[/C][C]0.016634[/C][/ROW]
[ROW][C]2[/C][C]-0.116099[/C][C]-0.9783[/C][C]0.165632[/C][/ROW]
[ROW][C]3[/C][C]-0.032476[/C][C]-0.2736[/C][C]0.392575[/C][/ROW]
[ROW][C]4[/C][C]0.086423[/C][C]0.7282[/C][C]0.234439[/C][/ROW]
[ROW][C]5[/C][C]-0.077733[/C][C]-0.655[/C][C]0.257296[/C][/ROW]
[ROW][C]6[/C][C]-0.163489[/C][C]-1.3776[/C][C]0.08633[/C][/ROW]
[ROW][C]7[/C][C]-0.034232[/C][C]-0.2884[/C][C]0.386925[/C][/ROW]
[ROW][C]8[/C][C]0.243447[/C][C]2.0513[/C][C]0.021963[/C][/ROW]
[ROW][C]9[/C][C]0.051403[/C][C]0.4331[/C][C]0.333116[/C][/ROW]
[ROW][C]10[/C][C]-0.049782[/C][C]-0.4195[/C][C]0.33807[/C][/ROW]
[ROW][C]11[/C][C]0.05818[/C][C]0.4902[/C][C]0.312742[/C][/ROW]
[ROW][C]12[/C][C]0.281[/C][C]2.3677[/C][C]0.010312[/C][/ROW]
[ROW][C]13[/C][C]-0.073179[/C][C]-0.6166[/C][C]0.269729[/C][/ROW]
[ROW][C]14[/C][C]-0.183467[/C][C]-1.5459[/C][C]0.063285[/C][/ROW]
[ROW][C]15[/C][C]-0.135048[/C][C]-1.1379[/C][C]0.129487[/C][/ROW]
[ROW][C]16[/C][C]-0.13166[/C][C]-1.1094[/C][C]0.135504[/C][/ROW]
[ROW][C]17[/C][C]-0.078556[/C][C]-0.6619[/C][C]0.25508[/C][/ROW]
[ROW][C]18[/C][C]-0.080311[/C][C]-0.6767[/C][C]0.250393[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41884&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41884&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 k	ACF(k)	T-STAT	P-value
1	0.257662	2.1711	0.016634
2	-0.116099	-0.9783	0.165632
3	-0.032476	-0.2736	0.392575
4	0.086423	0.7282	0.234439
5	-0.077733	-0.655	0.257296
6	-0.163489	-1.3776	0.08633
7	-0.034232	-0.2884	0.386925
8	0.243447	2.0513	0.021963
9	0.051403	0.4331	0.333116
10	-0.049782	-0.4195	0.33807
11	0.05818	0.4902	0.312742
12	0.281	2.3677	0.010312
13	-0.073179	-0.6166	0.269729
14	-0.183467	-1.5459	0.063285
15	-0.135048	-1.1379	0.129487
16	-0.13166	-1.1094	0.135504
17	-0.078556	-0.6619	0.25508
18	-0.080311	-0.6767	0.250393

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.257662	2.1711	0.016634
2	-0.195465	-1.647	0.051987
3	0.059747	0.5034	0.308107
4	0.063238	0.5329	0.2979
5	-0.1383	-1.1653	0.123891
6	-0.083486	-0.7035	0.242033
7	0.014914	0.1257	0.450175
8	0.229944	1.9375	0.028328
9	-0.092881	-0.7826	0.218224
10	0.039671	0.3343	0.369579
11	0.061799	0.5207	0.302089
12	0.22308	1.8797	0.032126
13	-0.221855	-1.8694	0.032847
14	0.018916	0.1594	0.436908
15	-0.133905	-1.1283	0.131495
16	-0.210932	-1.7773	0.039897
17	0.080091	0.6749	0.250977
18	-0.095773	-0.807	0.211183

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.257662 & 2.1711 & 0.016634 \tabularnewline
2 & -0.195465 & -1.647 & 0.051987 \tabularnewline
3 & 0.059747 & 0.5034 & 0.308107 \tabularnewline
4 & 0.063238 & 0.5329 & 0.2979 \tabularnewline
5 & -0.1383 & -1.1653 & 0.123891 \tabularnewline
6 & -0.083486 & -0.7035 & 0.242033 \tabularnewline
7 & 0.014914 & 0.1257 & 0.450175 \tabularnewline
8 & 0.229944 & 1.9375 & 0.028328 \tabularnewline
9 & -0.092881 & -0.7826 & 0.218224 \tabularnewline
10 & 0.039671 & 0.3343 & 0.369579 \tabularnewline
11 & 0.061799 & 0.5207 & 0.302089 \tabularnewline
12 & 0.22308 & 1.8797 & 0.032126 \tabularnewline
13 & -0.221855 & -1.8694 & 0.032847 \tabularnewline
14 & 0.018916 & 0.1594 & 0.436908 \tabularnewline
15 & -0.133905 & -1.1283 & 0.131495 \tabularnewline
16 & -0.210932 & -1.7773 & 0.039897 \tabularnewline
17 & 0.080091 & 0.6749 & 0.250977 \tabularnewline
18 & -0.095773 & -0.807 & 0.211183 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41884&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]0.257662[/C][C]2.1711[/C][C]0.016634[/C][/ROW]
[ROW][C]2[/C][C]-0.195465[/C][C]-1.647[/C][C]0.051987[/C][/ROW]
[ROW][C]3[/C][C]0.059747[/C][C]0.5034[/C][C]0.308107[/C][/ROW]
[ROW][C]4[/C][C]0.063238[/C][C]0.5329[/C][C]0.2979[/C][/ROW]
[ROW][C]5[/C][C]-0.1383[/C][C]-1.1653[/C][C]0.123891[/C][/ROW]
[ROW][C]6[/C][C]-0.083486[/C][C]-0.7035[/C][C]0.242033[/C][/ROW]
[ROW][C]7[/C][C]0.014914[/C][C]0.1257[/C][C]0.450175[/C][/ROW]
[ROW][C]8[/C][C]0.229944[/C][C]1.9375[/C][C]0.028328[/C][/ROW]
[ROW][C]9[/C][C]-0.092881[/C][C]-0.7826[/C][C]0.218224[/C][/ROW]
[ROW][C]10[/C][C]0.039671[/C][C]0.3343[/C][C]0.369579[/C][/ROW]
[ROW][C]11[/C][C]0.061799[/C][C]0.5207[/C][C]0.302089[/C][/ROW]
[ROW][C]12[/C][C]0.22308[/C][C]1.8797[/C][C]0.032126[/C][/ROW]
[ROW][C]13[/C][C]-0.221855[/C][C]-1.8694[/C][C]0.032847[/C][/ROW]
[ROW][C]14[/C][C]0.018916[/C][C]0.1594[/C][C]0.436908[/C][/ROW]
[ROW][C]15[/C][C]-0.133905[/C][C]-1.1283[/C][C]0.131495[/C][/ROW]
[ROW][C]16[/C][C]-0.210932[/C][C]-1.7773[/C][C]0.039897[/C][/ROW]
[ROW][C]17[/C][C]0.080091[/C][C]0.6749[/C][C]0.250977[/C][/ROW]
[ROW][C]18[/C][C]-0.095773[/C][C]-0.807[/C][C]0.211183[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41884&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41884&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 k	PACF(k)	T-STAT	P-value
1	0.257662	2.1711	0.016634
2	-0.195465	-1.647	0.051987
3	0.059747	0.5034	0.308107
4	0.063238	0.5329	0.2979
5	-0.1383	-1.1653	0.123891
6	-0.083486	-0.7035	0.242033
7	0.014914	0.1257	0.450175
8	0.229944	1.9375	0.028328
9	-0.092881	-0.7826	0.218224
10	0.039671	0.3343	0.369579
11	0.061799	0.5207	0.302089
12	0.22308	1.8797	0.032126
13	-0.221855	-1.8694	0.032847
14	0.018916	0.1594	0.436908
15	-0.133905	-1.1283	0.131495
16	-0.210932	-1.7773	0.039897
17	0.080091	0.6749	0.250977
18	-0.095773	-0.807	0.211183

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

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 (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='lags',ylab='ACF')
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')

Free Statistics

Description of Statistical Computation

Time Series analysis (degree of non-seasonal differencing=1) - King Size-si...

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code