Home » date » 2009 » Jun » 04 »

autocorrelation-trend prijzen energiegrondstoffen - Charlotte De Saeger

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Thu, 04 Jun 2009 07:15:06 -0600
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7.htm/, Retrieved Thu, 04 Jun 2009 15:18:07 +0200
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
106.8 114.3 105.7 90.1 91.6 97.7 100.8 104.6 95.9 102.7 104 107.9 113.8 113.8 123.1 125.1 137.6 134 140.3 152.1 150.6 167.3 153.2 142 154.4 158.5 180.9 181.3 172.4 192 199.3 215.4 214.3 201.5 190.5 196 215.7 209.4 214.1 237.8 239 237.8 251.5 248.8 215.4 201.2 203.1 214.2 188.9 203 213.3 228.5 228.2 240.9 258.8 248.5 269.2 289.6 323.4 317.2 322.8 340.9 368.2 388.5 441.2 474.3 483.9 417.9 365.9 263 199.4 157.2
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5848664.92823e-06
20.3777053.18260.001083
30.0872980.73560.232203
4-0.039371-0.33170.370529
5-0.220979-1.8620.033371
6-0.217458-1.83230.035548
7-0.096263-0.81110.210001
8-0.06822-0.57480.28361
9-0.135807-1.14430.128164
10-0.033276-0.28040.389997
11-0.041601-0.35050.363487
12-0.085471-0.72020.236885
13-0.158574-1.33620.092881
14-0.070641-0.59520.276789
15-0.001232-0.01040.495873
16-0.106559-0.89790.186142
17-0.104817-0.88320.190055
18-0.104445-0.88010.190896
19-0.064841-0.54640.293266
20-0.070951-0.59780.275922
210.0120430.10150.459731
220.0649120.5470.293061
230.1010630.85160.198657
240.0746530.6290.265673
250.1583161.3340.093234
260.1126020.94880.172971
270.031680.26690.395144
28-0.040864-0.34430.36581
29-0.049312-0.41550.33951
30-0.049975-0.42110.337477
31-0.070854-0.5970.276196
32-0.024224-0.20410.419424
330.0020460.01720.493145
340.0158070.13320.447208
350.068790.57960.281997
360.0365740.30820.379425
370.0423030.35640.361281
38-0.020802-0.17530.430679
39-0.038419-0.32370.373548
40-0.034996-0.29490.384471
41-0.036275-0.30570.380378
42-0.020204-0.17020.432653
43-0.061992-0.52240.301524
44-0.017388-0.14650.441964
450.0156520.13190.447723
460.0312370.26320.396577
470.0388550.32740.372166
48-0.006738-0.05680.477442


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5848664.92823e-06
20.0541640.45640.32475
3-0.233723-1.96940.026406
4-0.034449-0.29030.386227
5-0.184881-1.55780.061859
60.0136030.11460.454535
70.1824091.5370.064369
8-0.116525-0.98190.164751
9-0.229639-1.9350.028489
100.1809061.52430.065933
11-0.068249-0.57510.283528
12-0.149091-1.25630.10657
13-0.036349-0.30630.380144
140.0446250.3760.354012
150.0701890.59140.278058
16-0.231032-1.94670.027763
17-0.093603-0.78870.216453
18-0.022749-0.19170.424268
190.0801240.67510.250892
200.011320.09540.462139
21-0.055037-0.46370.322123
22-0.096444-0.81260.209568
230.1451861.22340.112619
240.0316210.26640.395334
250.0053940.04540.481939
26-0.061692-0.51980.302401
27-0.104569-0.88110.190614
280.0769870.64870.259311
29-0.027887-0.2350.407451
30-0.046442-0.39130.348363
31-0.020786-0.17510.430732
320.0462760.38990.348877
33-0.014634-0.12330.451106
340.01390.11710.453547
350.0675710.56940.285453
36-0.131271-1.10610.136207
370.0680370.57330.284131
380.0129860.10940.456587
39-0.053875-0.4540.325621
40-0.021423-0.18050.428632
410.0492610.41510.339666
42-0.00661-0.05570.47787
43-0.090062-0.75890.22522
440.0822640.69320.245232
450.0133890.11280.455246
46-0.024247-0.20430.419347
470.006130.05160.479477
48-0.091025-0.7670.222815
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7/1k5ru1244121301.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7/1k5ru1244121301.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7/23ypa1244121301.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244121487sqcnurr0x1nzkm7/23ypa1244121301.ps (open in new window)


 
Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 48 ; 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('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 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('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,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')
 





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