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Ruwe aardolie correlatie d=0 D=0

R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Tue, 18 Dec 2007 07:13:21 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Dec/18/t11979861954nrfmt55i03coi6.htm/, Retrieved Tue, 18 Dec 2007 14:56:38 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
68,4 70,6 83,9 90,1 90,6 87,1 90,8 94,1 99,8 96,8 87 96,3 107,1 115,2 106,1 89,5 91,3 97,6 100,7 104,6 94,7 101,8 102,5 105,3 110,3 109,8 117,3 118,8 131,3 125,9 133,1 147 145,8 164,4 149,8 137,7 151,7 156,8 180 180,4 170,4 191,6 199,5 218,2 217,5 205 194 199,3 219,3 211,1 215,2 240,2 242,2 240,7 255,4 253 218,2 203,7 205,6 215,6
 
Text written by user:
 
Output produced by software:


Summary of compuational 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
017.7460
10.9393387.27610
20.8791556.80990
30.8406266.51150
40.8096776.27170
50.7730315.98790
60.7158115.54460
70.6631675.13692e-06
80.6152024.76536e-06
90.5784284.48051.7e-05
100.5443474.21654.2e-05
110.4868223.77090.000187
120.4308473.33730.000728
130.3883513.00820.001919
140.3595162.78480.003578
150.3206832.4840.007901
160.2565041.98690.025754
170.1954321.51380.067663
180.142131.10090.137661
190.098890.7660.22334
200.0629370.48750.313838
210.0066350.05140.479592
22-0.045122-0.34950.636035
23-0.091502-0.70880.759395
24-0.128479-0.99520.838181
25-0.159358-1.23440.889064
26-0.202509-1.56860.939003
27-0.246802-1.91170.969655
28-0.282863-2.1910.983828
29-0.306373-2.37320.989571
30-0.330568-2.56060.993508
31-0.354871-2.74880.996055
32-0.376843-2.9190.997531
33-0.39144-3.03210.998208
34-0.389824-3.01960.998143
35-0.393168-3.04550.998276
36-0.408596-3.1650.998782
37-0.417572-3.23450.999008
38-0.422456-3.27230.999114
39-0.413163-3.20030.998902
40-0.400793-3.10450.998546
41-0.401618-3.11090.998573
42-0.395318-3.06210.998356
43-0.387358-3.00050.998039
44-0.366796-2.84120.996935
45-0.340771-2.63960.994719
46-0.327282-2.53510.993067
47-0.326138-2.52630.992907
48-0.320882-2.48550.99213
49-0.303054-2.34740.98889
50-0.28328-2.19430.983951
51-0.267116-2.06910.978572
52-0.244528-1.89410.968483
53-0.219679-1.70160.952999
54-0.192344-1.48990.929254
55-0.153909-1.19220.881057
56-0.116513-0.90250.814801
57-0.091541-0.70910.759488
58-0.069507-0.53840.703853
59-0.037592-0.29120.614045


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.9393387.27610
1-0.027207-0.21070.5831
20.152191.17890.121554
30.0447910.3470.36492
4-0.034961-0.27080.606267
5-0.177905-1.3780.913346
6-0.001875-0.01450.505769
7-0.049902-0.38650.649768
80.064980.50330.308287
90.0173120.13410.446888
10-0.176003-1.36330.911061
11-0.017996-0.13940.555198
120.0235660.18250.427887
130.0568620.44050.330596
14-0.080516-0.62370.732396
15-0.174102-1.34860.908731
16-0.054277-0.42040.662163
17-0.059592-0.46160.676981
18-0.001576-0.01220.50485
190.0652230.50520.30763
20-0.12682-0.98230.835062
210.0130150.10080.460016
22-0.071216-0.55160.708377
23-0.028352-0.21960.586541
240.0311820.24150.404982
25-0.039768-0.3080.620443
26-0.068868-0.53340.702153
27-0.01774-0.13740.554419
28-0.004626-0.03580.514231
29-0.039433-0.30540.619458
300.088040.6820.248945
31-0.017234-0.13350.552875
320.026640.20630.418608
330.0581550.45050.326998
34-0.080701-0.62510.732865
35-0.063287-0.49020.687115
360.0348660.27010.394016
37-0.043666-0.33820.631817
380.0622720.48240.315655
390.0195930.15180.439941
40-0.072682-0.5630.71223
410.063390.4910.312604
42-0.043862-0.33980.632385
430.0473430.36670.357561
440.0556480.43110.333988
45-0.072851-0.56430.712675
46-0.150425-1.16520.875723
47-0.030153-0.23360.591941
48-0.038-0.29430.615246
490.0658440.510.305951
500.0515860.39960.345442
510.0887210.68720.247294
520.0136080.10540.458202
53-0.081146-0.62860.733987
540.1190970.92250.179975
550.0625590.48460.31487
56-0.083583-0.64740.740088
570.0126430.09790.461157
58-0.043609-0.33780.63165
59NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11979861954nrfmt55i03coi6/1arus1197987199.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11979861954nrfmt55i03coi6/1arus1197987199.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11979861954nrfmt55i03coi6/2m5381197987199.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t11979861954nrfmt55i03coi6/2m5381197987199.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 0.0 ; par3 = 0 ; 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('http://www.xycoon.com/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 1:par1) {
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(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('http://www.xycoon.com/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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
 





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