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ws9: acf d=D=0

*The author of this computation has been verified*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Fri, 04 Dec 2009 09:18:36 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943722kh3wd6j8wb48ldk.htm/, Retrieved Fri, 04 Dec 2009 17:22:04 +0100
 
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/Dec/04/t1259943722kh3wd6j8wb48ldk.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 «
6.3 6.2 6.1 6.3 6.5 6.6 6.5 6.2 6.2 5.9 6.1 6.1 6.1 6.1 6.1 6.4 6.7 6.9 7 7 6.8 6.4 5.9 5.5 5.5 5.6 5.8 5.9 6.1 6.1 6 6 5.9 5.5 5.6 5.4 5.2 5.2 5.2 5.5 5.8 5.8 5.5 5.3 5.1 5.2 5.8 5.8 5.5 5 4.9 5.3 6.1 6.5 6.8 6.6 6.4 6.4 6.6
 
Output produced by software:


Summary of computational 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
10.8671986.66110
20.6283764.82675e-06
30.3941923.02780.001825
40.245511.88580.032124
50.187741.44210.077287
60.1649711.26720.105037
70.1204840.92550.179249
80.0876420.67320.251728
90.0898530.69020.246396
100.1425111.09460.13906
110.2126841.63370.053828
120.2524171.93890.028653
130.2219321.70470.046757
140.1551221.19150.119111
150.0498970.38330.35145
16-0.077028-0.59170.278169
17-0.186983-1.43620.078107
18-0.261072-2.00530.024761
19-0.294811-2.26450.013616
20-0.283735-2.17940.016653
21-0.254807-1.95720.02753
22-0.225299-1.73060.044379
23-0.193605-1.48710.071156
24-0.1592-1.22280.113127
25-0.142523-1.09470.139039
26-0.124988-0.96010.170474
27-0.158024-1.21380.11483
28-0.222498-1.7090.04635
29-0.298004-2.2890.012837
30-0.359923-2.76460.003797
31-0.381732-2.93210.002392
32-0.353223-2.71320.004361
33-0.274775-2.11060.019528
34-0.161492-1.24040.10986
35-0.055164-0.42370.336654
360.0190730.14650.442013
370.0393410.30220.381788
380.0284290.21840.413949
390.0097620.0750.47024
40-1.3e-05-1e-040.499959
41-0.01245-0.09560.46207
42-0.03827-0.2940.38491
43-0.078706-0.60460.273896
44-0.108883-0.83630.203167
45-0.10217-0.78480.217861
46-0.058955-0.45280.326162
47-0.014358-0.11030.456278
480.0205230.15760.43764
490.0367060.28190.389485
500.0559080.42940.334583
510.0656330.50410.308021
520.077260.59340.277575
530.0713490.5480.292864
540.0558620.42910.334712
550.0337860.25950.398071
560.0192620.1480.441443
570.0170250.13080.4482
580.0122430.0940.462698
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8671986.66110
2-0.498681-3.83040.000156
30.0535480.41130.341168
40.1793861.37790.08672
50.0477640.36690.357511
6-0.106029-0.81440.209339
7-0.116089-0.89170.188088
80.2270951.74430.043153
90.0909970.6990.243662
100.0715860.54990.292246
11-0.017942-0.13780.445429
12-0.012321-0.09460.462461
13-0.091433-0.70230.242624
140.047750.36680.357549
15-0.239032-1.8360.035696
16-0.196787-1.51160.067993
170.0470180.36110.359639
180.0059640.04580.481808
19-0.067948-0.52190.301842
20-0.053349-0.40980.341726
21-0.006024-0.04630.481625
22-0.020246-0.15550.438476
230.0129220.09930.460636
24-0.019119-0.14690.441873
25-0.134108-1.03010.153582
260.1316921.01150.157944
27-0.197179-1.51460.067611
280.0076490.05880.476674
29-0.098625-0.75750.225868
30-0.01352-0.10390.458819
310.0368820.28330.388972
32-0.03273-0.25140.401188
330.2019411.55110.063109
340.0163530.12560.450234
35-0.029027-0.2230.412168
36-0.019395-0.1490.441041
37-0.062257-0.47820.317137
380.0021130.01620.493552
390.0643850.49460.311377
40-0.035288-0.27110.393649
41-0.071768-0.55130.291769
420.0640190.49170.312365
43-0.05911-0.4540.325735
44-0.04149-0.31870.375543
45-0.055795-0.42860.3349
46-0.056484-0.43390.332985
47-0.132621-1.01870.156256
480.013310.10220.459459
490.0292880.2250.411392
500.0075610.05810.476941
51-0.051455-0.39520.347048
520.0694830.53370.297774
530.0288710.22180.412631
54-0.016346-0.12560.450255
55-0.009009-0.06920.472533
560.0178070.13680.445835
57-0.016461-0.12640.449909
58-0.045688-0.35090.363443
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943722kh3wd6j8wb48ldk/1vfcn1259943515.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943722kh3wd6j8wb48ldk/1vfcn1259943515.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943722kh3wd6j8wb48ldk/2o0v21259943515.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/04/t1259943722kh3wd6j8wb48ldk/2o0v21259943515.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 0.5 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 0.5 ; 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('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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