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step22é

*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: Mon, 08 Dec 2008 11:59:41 -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/08/t1228762824h5s77yuyj49h7zq.htm/, Retrieved Mon, 08 Dec 2008 19:00:26 +0000
 
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/08/t1228762824h5s77yuyj49h7zq.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},
}
 
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
 
Feedback Forum:
2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc] [reply] 
test

Post a new message
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
97,8 107,4 117,5 105,6 97,4 99,5 98 104,3 100,6 101,1 103,9 96,9 95,5 108,4 117 103,8 100,8 110,6 104 112,6 107,3 98,9 109,8 104,9 102,2 123,9 124,9 112,7 121,9 100,6 104,3 120,4 107,5 102,9 125,6 107,5 108,8 128,4 121,1 119,5 128,7 108,7 105,5 119,8 111,3 110,6 120,1 97,5 107,7 127,3 117,2 119,8 116,2 111 112,4 130,6 109,1 118,8 123,9 101,6 112,8 128 129,6 125,8 119,5 115,7 113,6 129,7 112 116,8 127 112,1 114,2 121,1 131,6 125 120,4 117,7 117,5 120,6 127,5 112,3 124,5 115,2 105,4
 
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
10.3595383.31480.000675
20.1982611.82790.035538
30.4864074.48451.1e-05
40.1745281.60910.055655
50.2691032.4810.007536
60.5339424.92272e-06
70.1650691.52190.065878
80.1618081.49180.069728
90.36483.36330.000578
100.026420.24360.404071
110.2234182.05980.021238
120.6042345.57080
130.1513931.39580.083209
140.0626690.57780.282469
150.2374152.18890.015675
16-0.043026-0.39670.346298
170.1134381.04580.149299
180.2831852.61080.005337
19-0.039348-0.36280.358839
200.0100170.09240.463317
210.1194731.10150.136897
22-0.150362-1.38630.084646
230.0827310.76270.223865
240.2781792.56470.006042
250.0056860.05240.479157
26-0.017912-0.16510.434613
270.0538530.49650.310413
28-0.158961-1.46550.073231
290.0125910.11610.45393
300.0829780.7650.223191
31-0.099444-0.91680.180913
32-0.052247-0.48170.315631
33-0.066604-0.61410.270408
34-0.188083-1.7340.043268
350.007820.07210.471347
360.14751.35990.088732
37-0.027801-0.25630.399164
38-0.045363-0.41820.338417
39-0.030896-0.28480.388227
40-0.118933-1.09650.137977
41-0.028389-0.26170.39708
420.0090280.08320.466932
43-0.078385-0.72270.235932
44-0.08205-0.75650.225732
45-0.141251-1.30230.09817
46-0.198549-1.83050.035338
47-0.096545-0.89010.187961
48-0.002561-0.02360.490609
49-0.129462-1.19360.117981
50-0.175448-1.61760.054732
51-0.176288-1.62530.053901
52-0.167203-1.54150.063451
53-0.139284-1.28410.101292
54-0.130522-1.20340.11609
55-0.159253-1.46820.072865
56-0.150267-1.38540.084778
57-0.193123-1.78050.039283
58-0.251824-2.32170.011321
59-0.179448-1.65440.050865
60-0.100986-0.9310.177234


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3595383.31480.000675
20.0792360.73050.233541
30.4533694.17993.5e-05
4-0.171629-1.58230.058643
50.3090262.84910.002749
60.2471022.27820.012613
7-0.113711-1.04840.148721
80.0043310.03990.484121
90.0491010.45270.325962
10-0.191573-1.76620.040475
110.2245672.07040.020724
120.3991733.68020.000204
13-0.140109-1.29170.099975
14-0.234495-2.16190.016717
15-0.14282-1.31670.095734
16-0.078857-0.7270.234604
17-0.014838-0.13680.445758
18-0.069026-0.63640.263118
190.0391880.36130.359387
20-0.031494-0.29040.386125
21-0.024223-0.22330.411908
220.0073630.06790.473018
230.099570.9180.180612
24-0.071321-0.65750.256303
250.1230641.13460.129868
26-0.062041-0.5720.284418
270.0459010.42320.336615
28-0.114518-1.05580.147024
290.0155880.14370.443033
30-0.136172-1.25540.106379
310.1501661.38450.08492
32-0.100638-0.92780.178061
33-0.014401-0.13280.447345
34-0.005736-0.05290.478974
350.0736770.67930.249406
360.1041620.96030.169807
37-0.015592-0.14380.443018
38-0.06809-0.62780.265923
390.0286820.26440.396043
400.0152710.14080.444185
41-0.049804-0.45920.323641
42-0.047819-0.44090.330212
43-0.006206-0.05720.477252
44-0.085984-0.79270.215071
45-0.017434-0.16070.436342
46-0.089326-0.82350.206252
47-0.058654-0.54080.295044
48-0.129778-1.19650.117415
49-0.10658-0.98260.164291
50-0.049626-0.45750.324229
510.0073330.06760.47313
520.0443060.40850.341972
530.0593330.5470.292898
54-0.065907-0.60760.272524
550.0294050.27110.393485
560.0988540.91140.182333
570.0430790.39720.346118
58-0.104259-0.96120.169584
590.0046160.04260.483078
60-0.027434-0.25290.400466
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228762824h5s77yuyj49h7zq/1aoji1228762777.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228762824h5s77yuyj49h7zq/1aoji1228762777.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228762824h5s77yuyj49h7zq/22dk91228762777.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228762824h5s77yuyj49h7zq/22dk91228762777.ps (open in new window)


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