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WS 4 - Q2 - methode 2 - reeks 3 (1)

R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Thu, 29 Nov 2007 03:36:13 -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/Nov/29/t119633199957dl35hpykohev6.htm/, Retrieved Thu, 29 Nov 2007 11:26:43 +0100
 
User-defined keywords:
Christel Stuer, Steven Coomans
 
Dataseries X:
» Textbox « » Textfile « » CSV «
118,4 108,1 105,4 114,6 106,9 115,9 109,8 101,8 114,2 110,8 108,4 127,5 128,6 116,6 127,4 105 108,3 125 111,6 106,5 130,3 115 116,1 134 126,5 125,8 136,4 114,9 110,9 125,5 116,8 116,8 125,5 104,2 115,1 132,8 123,3 124,8 122 117,4 117,9 137,4 114,6 124,7 129,6 109,4 120,9 134,9 136,3 133,2 127,2 122,7 120,5 137,8 119,1 124,3 134,4 121,7 121 128,6
 
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
10.2271961.75990.041765
20.1069440.82840.205368
30.479343.7130.000225
4-0.040839-0.31630.623576
50.0666410.51620.303805
60.4719223.65550.000271
7-0.07566-0.58610.719983
8-0.033764-0.26150.602712
90.3407652.63960.005282
10-0.145989-1.13080.868685
110.0442360.34270.366529
120.5013573.88350.00013
13-0.034405-0.26650.604617
140.0342080.2650.395969
150.2444731.89370.031546
16-0.20864-1.61610.944343
17-0.021371-0.16550.565462
180.2108221.6330.053851
19-0.23091-1.78860.960638
20-0.122253-0.9470.826273
210.0962130.74530.229512
22-0.220458-1.70770.953565
230.0307080.23790.4064
240.2237531.73320.0441
25-0.111447-0.86330.804284
260.021820.1690.433175
270.1790641.3870.085283
28-0.152275-1.17950.878576
290.0102880.07970.468375
300.1141490.88420.190061
31-0.12441-0.96370.830462
32-0.032825-0.25430.599917
33-0.002695-0.02090.508292
34-0.220596-1.70870.953665
35-0.044557-0.34510.6344
360.0723950.56080.288522
37-0.142863-1.10660.863561
38-0.08791-0.6810.750739
39-0.05352-0.41460.660031
40-0.223423-1.73060.955671
41-0.127229-0.98550.835835
42-0.084745-0.65640.742973
43-0.157513-1.22010.886397
44-0.09313-0.72140.763261
45-0.093472-0.7240.76407
46-0.211554-1.63870.946744
47-0.140057-1.08490.858841
48-0.09188-0.71170.760295
49-0.147354-1.14140.87088
50-0.074938-0.58050.718113
51-0.084506-0.65460.742379
52-0.106935-0.82830.794613
53-0.049765-0.38550.649377
54-0.057709-0.4470.671763
55-0.058735-0.4550.674609
56-0.018866-0.14610.557848
57-0.024994-0.19360.576429
58-0.019099-0.14790.558557
59-0.003005-0.02330.509246


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.2271961.75990.041765
10.0583370.45190.326493
20.4689253.63230.000292
3-0.315091-2.44070.991186
40.1835711.42190.080111
50.2809792.17650.016734
6-0.218637-1.69360.952232
7-0.068951-0.53410.702373
80.1627891.2610.106102
9-0.104385-0.80860.78902
100.1157470.89660.186764
110.3167182.45330.008539
12-0.067833-0.52540.699391
13-0.104071-0.80610.788324
14-0.164529-1.27440.896289
150.024680.19120.424519
16-0.062505-0.48420.684983
17-0.120665-0.93470.823147
18-0.001807-0.0140.505562
19-0.08116-0.62870.734022
20-0.009399-0.07280.528898
210.129111.00010.160644
220.1266450.9810.165269
23-0.065465-0.50710.693026
240.0234590.18170.428211
25-0.021403-0.16580.565559
260.1451391.12420.132695
27-0.103576-0.80230.787226
28-0.03333-0.25820.601422
29-0.038563-0.29870.616901
300.1533941.18820.119721
31-0.073085-0.56610.713286
32-0.123811-0.9590.829305
33-0.081489-0.63120.734849
34-0.042546-0.32960.628559
350.0022040.01710.493219
36-0.076902-0.59570.723184
37-0.105421-0.81660.791302
38-0.169624-1.31390.903059
39-0.035537-0.27530.607973
40-0.033084-0.25630.600688
410.0045390.03520.486036
420.0699730.5420.294911
430.0163950.1270.449685
440.0066520.05150.47954
45-0.007795-0.06040.523974
460.0417630.32350.373723
47-0.140531-1.08850.859646
48-0.042703-0.33080.629017
490.0785480.60840.2726
500.0914290.70820.240779
510.0547630.42420.33647
520.0480520.37220.355525
53-0.086075-0.66670.746251
54-0.046457-0.35990.639889
550.005050.03910.484464
560.0369180.2860.387944
57-0.060059-0.46520.678269
58-0.089217-0.69110.753907
59NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t119633199957dl35hpykohev6/1i6cp1196332571.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t119633199957dl35hpykohev6/1i6cp1196332571.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t119633199957dl35hpykohev6/2875t1196332571.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t119633199957dl35hpykohev6/2875t1196332571.ps (open in new window)


 
Parameters:
par1 = 60 ; par2 = 1 ; 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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