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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 28 Apr 2010 18:13:58 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Apr/28/t1272478471vctrobo8yl8rvet.htm/, Retrieved Fri, 29 Mar 2024 12:09:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75004, Retrieved Fri, 29 Mar 2024 12:09:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Het verkoopcijfer...] [2010-04-24 13:28:58] [e6858d370c345b8be9ebab3064023a2f]
- RMP     [(Partial) Autocorrelation Function] [Het verkoopcijfer...] [2010-04-28 18:13:58] [b9d93a00608bcde4713420de1fa47366] [Current]
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Dataseries X:
68897
38683
44720
39525
45315
50380
40600
36279
42438
38064
31879
11379
70249
39253
47060
41697
38708
49267
39018
32228
40870
39383
34571
12066
70938
34077
45409
40809
37013
44953
37848
32745
43412
34931
33008
8620
68906
39556
50669
36432
40891
48428
36222
33425
39401
37967
34801
12657
69116
41519
51321
38529
41547
52073
38401
40898
40439
41888
37898
8771
68184
50530
47221
41756
45633
48138
39486
39341
41117
41629
29722
7054
56676
34870
35117
30169
30936
35699
33228
27733
33666
35429
27438
8170
62557




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75004&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75004&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75004&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.238298-2.1970.015371
20.0403820.37230.355295
3-0.023297-0.21480.415222
40.1214911.12010.132914
50.0604220.55710.289473
6-0.194126-1.78970.038528
70.0398640.36750.357069
80.0933850.8610.195839
9-0.069497-0.64070.26171
10-0.010392-0.09580.461949
11-0.319507-2.94570.002078
120.7942267.32240
13-0.262063-2.41610.008914
14-0.014312-0.1320.447666
15-0.09-0.82980.204498
160.0450690.41550.339407
170.0045590.0420.483285
18-0.229349-2.11450.018701
19-0.007419-0.06840.472814

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.238298 & -2.197 & 0.015371 \tabularnewline
2 & 0.040382 & 0.3723 & 0.355295 \tabularnewline
3 & -0.023297 & -0.2148 & 0.415222 \tabularnewline
4 & 0.121491 & 1.1201 & 0.132914 \tabularnewline
5 & 0.060422 & 0.5571 & 0.289473 \tabularnewline
6 & -0.194126 & -1.7897 & 0.038528 \tabularnewline
7 & 0.039864 & 0.3675 & 0.357069 \tabularnewline
8 & 0.093385 & 0.861 & 0.195839 \tabularnewline
9 & -0.069497 & -0.6407 & 0.26171 \tabularnewline
10 & -0.010392 & -0.0958 & 0.461949 \tabularnewline
11 & -0.319507 & -2.9457 & 0.002078 \tabularnewline
12 & 0.794226 & 7.3224 & 0 \tabularnewline
13 & -0.262063 & -2.4161 & 0.008914 \tabularnewline
14 & -0.014312 & -0.132 & 0.447666 \tabularnewline
15 & -0.09 & -0.8298 & 0.204498 \tabularnewline
16 & 0.045069 & 0.4155 & 0.339407 \tabularnewline
17 & 0.004559 & 0.042 & 0.483285 \tabularnewline
18 & -0.229349 & -2.1145 & 0.018701 \tabularnewline
19 & -0.007419 & -0.0684 & 0.472814 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75004&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]-0.238298[/C][C]-2.197[/C][C]0.015371[/C][/ROW]
[ROW][C]2[/C][C]0.040382[/C][C]0.3723[/C][C]0.355295[/C][/ROW]
[ROW][C]3[/C][C]-0.023297[/C][C]-0.2148[/C][C]0.415222[/C][/ROW]
[ROW][C]4[/C][C]0.121491[/C][C]1.1201[/C][C]0.132914[/C][/ROW]
[ROW][C]5[/C][C]0.060422[/C][C]0.5571[/C][C]0.289473[/C][/ROW]
[ROW][C]6[/C][C]-0.194126[/C][C]-1.7897[/C][C]0.038528[/C][/ROW]
[ROW][C]7[/C][C]0.039864[/C][C]0.3675[/C][C]0.357069[/C][/ROW]
[ROW][C]8[/C][C]0.093385[/C][C]0.861[/C][C]0.195839[/C][/ROW]
[ROW][C]9[/C][C]-0.069497[/C][C]-0.6407[/C][C]0.26171[/C][/ROW]
[ROW][C]10[/C][C]-0.010392[/C][C]-0.0958[/C][C]0.461949[/C][/ROW]
[ROW][C]11[/C][C]-0.319507[/C][C]-2.9457[/C][C]0.002078[/C][/ROW]
[ROW][C]12[/C][C]0.794226[/C][C]7.3224[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.262063[/C][C]-2.4161[/C][C]0.008914[/C][/ROW]
[ROW][C]14[/C][C]-0.014312[/C][C]-0.132[/C][C]0.447666[/C][/ROW]
[ROW][C]15[/C][C]-0.09[/C][C]-0.8298[/C][C]0.204498[/C][/ROW]
[ROW][C]16[/C][C]0.045069[/C][C]0.4155[/C][C]0.339407[/C][/ROW]
[ROW][C]17[/C][C]0.004559[/C][C]0.042[/C][C]0.483285[/C][/ROW]
[ROW][C]18[/C][C]-0.229349[/C][C]-2.1145[/C][C]0.018701[/C][/ROW]
[ROW][C]19[/C][C]-0.007419[/C][C]-0.0684[/C][C]0.472814[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75004&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75004&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
1-0.238298-2.1970.015371
20.0403820.37230.355295
3-0.023297-0.21480.415222
40.1214911.12010.132914
50.0604220.55710.289473
6-0.194126-1.78970.038528
70.0398640.36750.357069
80.0933850.8610.195839
9-0.069497-0.64070.26171
10-0.010392-0.09580.461949
11-0.319507-2.94570.002078
120.7942267.32240
13-0.262063-2.41610.008914
14-0.014312-0.1320.447666
15-0.09-0.82980.204498
160.0450690.41550.339407
170.0045590.0420.483285
18-0.229349-2.11450.018701
19-0.007419-0.06840.472814







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.238298-2.1970.015371
2-0.017391-0.16030.436498
3-0.01872-0.17260.431693
40.1190971.0980.137649
50.1260881.16250.124149
6-0.166082-1.53120.064716
7-0.053167-0.49020.312637
80.0925590.85340.197931
9-0.05032-0.46390.321942
10-0.002279-0.0210.491641
11-0.332221-3.06290.001468
120.7584546.99260
13-0.170028-1.56760.060347
14-0.16012-1.47620.071789
15-0.189549-1.74760.042076
16-0.17472-1.61080.055461
17-0.116529-1.07430.142854
18-0.021851-0.20150.420412
19-0.01319-0.12160.45175

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.238298 & -2.197 & 0.015371 \tabularnewline
2 & -0.017391 & -0.1603 & 0.436498 \tabularnewline
3 & -0.01872 & -0.1726 & 0.431693 \tabularnewline
4 & 0.119097 & 1.098 & 0.137649 \tabularnewline
5 & 0.126088 & 1.1625 & 0.124149 \tabularnewline
6 & -0.166082 & -1.5312 & 0.064716 \tabularnewline
7 & -0.053167 & -0.4902 & 0.312637 \tabularnewline
8 & 0.092559 & 0.8534 & 0.197931 \tabularnewline
9 & -0.05032 & -0.4639 & 0.321942 \tabularnewline
10 & -0.002279 & -0.021 & 0.491641 \tabularnewline
11 & -0.332221 & -3.0629 & 0.001468 \tabularnewline
12 & 0.758454 & 6.9926 & 0 \tabularnewline
13 & -0.170028 & -1.5676 & 0.060347 \tabularnewline
14 & -0.16012 & -1.4762 & 0.071789 \tabularnewline
15 & -0.189549 & -1.7476 & 0.042076 \tabularnewline
16 & -0.17472 & -1.6108 & 0.055461 \tabularnewline
17 & -0.116529 & -1.0743 & 0.142854 \tabularnewline
18 & -0.021851 & -0.2015 & 0.420412 \tabularnewline
19 & -0.01319 & -0.1216 & 0.45175 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75004&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]-0.238298[/C][C]-2.197[/C][C]0.015371[/C][/ROW]
[ROW][C]2[/C][C]-0.017391[/C][C]-0.1603[/C][C]0.436498[/C][/ROW]
[ROW][C]3[/C][C]-0.01872[/C][C]-0.1726[/C][C]0.431693[/C][/ROW]
[ROW][C]4[/C][C]0.119097[/C][C]1.098[/C][C]0.137649[/C][/ROW]
[ROW][C]5[/C][C]0.126088[/C][C]1.1625[/C][C]0.124149[/C][/ROW]
[ROW][C]6[/C][C]-0.166082[/C][C]-1.5312[/C][C]0.064716[/C][/ROW]
[ROW][C]7[/C][C]-0.053167[/C][C]-0.4902[/C][C]0.312637[/C][/ROW]
[ROW][C]8[/C][C]0.092559[/C][C]0.8534[/C][C]0.197931[/C][/ROW]
[ROW][C]9[/C][C]-0.05032[/C][C]-0.4639[/C][C]0.321942[/C][/ROW]
[ROW][C]10[/C][C]-0.002279[/C][C]-0.021[/C][C]0.491641[/C][/ROW]
[ROW][C]11[/C][C]-0.332221[/C][C]-3.0629[/C][C]0.001468[/C][/ROW]
[ROW][C]12[/C][C]0.758454[/C][C]6.9926[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.170028[/C][C]-1.5676[/C][C]0.060347[/C][/ROW]
[ROW][C]14[/C][C]-0.16012[/C][C]-1.4762[/C][C]0.071789[/C][/ROW]
[ROW][C]15[/C][C]-0.189549[/C][C]-1.7476[/C][C]0.042076[/C][/ROW]
[ROW][C]16[/C][C]-0.17472[/C][C]-1.6108[/C][C]0.055461[/C][/ROW]
[ROW][C]17[/C][C]-0.116529[/C][C]-1.0743[/C][C]0.142854[/C][/ROW]
[ROW][C]18[/C][C]-0.021851[/C][C]-0.2015[/C][C]0.420412[/C][/ROW]
[ROW][C]19[/C][C]-0.01319[/C][C]-0.1216[/C][C]0.45175[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75004&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75004&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
1-0.238298-2.1970.015371
2-0.017391-0.16030.436498
3-0.01872-0.17260.431693
40.1190971.0980.137649
50.1260881.16250.124149
6-0.166082-1.53120.064716
7-0.053167-0.49020.312637
80.0925590.85340.197931
9-0.05032-0.46390.321942
10-0.002279-0.0210.491641
11-0.332221-3.06290.001468
120.7584546.99260
13-0.170028-1.56760.060347
14-0.16012-1.47620.071789
15-0.189549-1.74760.042076
16-0.17472-1.61080.055461
17-0.116529-1.07430.142854
18-0.021851-0.20150.420412
19-0.01319-0.12160.45175



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')