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Paper Analyse (17)

*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: Sun, 21 Dec 2008 04:57:49 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/21/t1229860711nxyrcd2lw9igpty.htm/, Retrieved Sun, 21 Dec 2008 12:58:33 +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/2008/Dec/21/t1229860711nxyrcd2lw9igpty.htm/},
    year = {2008},
}
@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 = {2008},
    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 «
1593 1477.9 1733.7 1569.7 1843.7 1950.3 1657.5 1772.1 1568.3 1809.8 1646.7 1808.5 1763.9 1625.5 1538.8 1342.4 1645.1 1619.9 1338.1 1505.5 1529.1 1511.9 1656.7 1694.4 1662.3 1588.7 1483.3 1585.6 1658.9 1584.4 1470.6 1618.7 1407.6 1473.9 1515.3 1485.4 1496.1 1493.5 1298.4 1375.3 1507.9 1455.3 1363.3 1392.8 1348.8 1880.3 1669.2 1543.6 1701.2 1516.5 1466.8 1484.1 1577.2 1684.5 1414.7 1674.5 1598.7 1739.1 1674.6 1671.8 1802 1526.8 1580.9 1634.8 1610.3 1712 1678.8 1708.1 1680.6 2056 1624 2021.4 1861.1 1750.8 1767.5 1710.3 2151.5 2047.9 1915.4 1984.7 1896.5 2170.8 2139.9 2330.5 2121.8 2226.8 1857.9 2155.9 2341.7 2290.2 2006.5 2111.9 1731.3 1762.2 1863.2 1943.5 1975.2
 
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
1-0.470806-4.61296e-06
20.0289550.28370.388625
30.0191310.18740.425854
4-0.141787-1.38920.083989
50.1444641.41540.080087
6-0.08808-0.8630.195144
70.1068071.04650.148981
8-0.019216-0.18830.425528
9-0.059788-0.58580.279692
10-0.087748-0.85970.196035
11-0.048008-0.47040.319574
120.3589573.5170.000334
13-0.293163-2.87240.002507
140.1639731.60660.055713
15-0.125559-1.23020.110811
16-0.052004-0.50950.305773
170.06360.62320.267331
180.0522360.51180.304982
19-0.046881-0.45930.323515
200.0880230.86240.195296
21-0.072758-0.71290.238825
22-0.082899-0.81220.209331
230.0342890.3360.368818
240.1978271.93830.027762
25-0.166618-1.63250.052923
260.1785731.74970.041687
27-0.257605-2.5240.006622
280.0385390.37760.353278
290.16631.62940.053253
30-0.180616-1.76970.039979
310.0750860.73570.231856
320.0975030.95530.170906
33-0.137846-1.35060.089998
34-0.00845-0.08280.467092
35-0.056841-0.55690.289438
360.2297382.2510.013335
37-0.128851-1.26250.104917
380.0329790.32310.373652
39-0.108138-1.05950.146009
400.0297170.29120.385776
410.0638850.62590.266418
42-0.095306-0.93380.176373
430.1523081.49230.069449
44-0.003339-0.03270.486985
45-0.174728-1.7120.045065
460.1375671.34790.090435
47-0.161222-1.57960.058739
480.1468361.43870.076745
49-0.017731-0.17370.431224
50-0.031276-0.30640.379966
51-0.016251-0.15920.436912
52-0.015327-0.15020.440473
530.0390680.38280.351361
54-0.025086-0.24580.403183
550.0854430.83720.202289
56-0.054009-0.52920.29895
57-0.021064-0.20640.418463
580.0147660.14470.442634
59-0.111176-1.08930.139375
600.2193942.14960.01705


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.470806-4.61296e-06
2-0.247581-2.42580.008572
3-0.110075-1.07850.141755
4-0.239425-2.34590.01052
5-0.065093-0.63780.262569
6-0.099742-0.97730.165445
70.0442990.4340.332617
80.05650.55360.290573
90.0009980.00980.496108
10-0.18823-1.84430.034114
11-0.279713-2.74060.003657
120.2432052.38290.009573
13-0.009136-0.08950.46443
140.0666250.65280.257727
15-0.078242-0.76660.222597
16-0.082331-0.80670.210923
17-0.122846-1.20360.115843
180.124681.22160.112424
19-0.112103-1.09840.137393
200.0255160.250.401558
210.0321520.3150.376714
220.0066830.06550.473963
23-0.086208-0.84470.200199
240.1785921.74980.041671
250.0274690.26910.3942
260.1495181.4650.073098
27-0.093152-0.91270.181844
28-0.082914-0.81240.209291
290.1372511.34480.090932
30-0.050178-0.49160.312047
31-0.111395-1.09140.138904
320.000550.00540.497854
330.0471020.46150.32274
34-0.027577-0.27020.393794
35-0.110535-1.0830.140756
360.0574710.56310.287341
370.044350.43450.332437
38-0.099054-0.97050.167112
390.0095630.09370.462771
40-0.097157-0.95190.17176
41-0.044946-0.44040.330327
420.0002460.00240.499041
430.0779950.76420.223312
44-0.039649-0.38850.349261
45-0.069738-0.68330.248033
460.0752530.73730.231361
47-0.12943-1.26820.103905
48-0.149124-1.46110.073626
49-0.052432-0.51370.30431
50-0.100524-0.98490.163567
510.0159240.1560.438171
52-0.019398-0.19010.42483
53-0.003559-0.03490.486129
54-0.008009-0.07850.468809
550.029140.28550.387935
56-0.024457-0.23960.405563
57-0.026822-0.26280.396635
58-0.077294-0.75730.225354
590.0200020.1960.422519
600.0814780.79830.213328
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229860711nxyrcd2lw9igpty/1oqzm1229860667.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229860711nxyrcd2lw9igpty/1oqzm1229860667.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229860711nxyrcd2lw9igpty/2ogik1229860667.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/21/t1229860711nxyrcd2lw9igpty/2ogik1229860667.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = -1.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = -1.0 ; 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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