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S3 - ACF

*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 12:22:58 -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/t1228764212v6lvcmf4d2zvbdw.htm/, Retrieved Mon, 08 Dec 2008 19:23:34 +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/t1228764212v6lvcmf4d2zvbdw.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 «
14897 13063 12604 13630 14421 13978 12928 13430 13470 14786 14292 14309 14013 13241 12153 14290 15669 14170 14570 14469 14265 15321 14434 13692 14194 13519 11858 14616 15643 14077 14888 14160 14643 17193 15386 14287 17527 14497 14398 16630 16671 16615 16869 15664 16360 18448 16889 16505 18321 15052 15700 18135 16769 18883 19021 18102 17776 21490 17065 18690 18953 16399 16896 18553 19270 19422 17579 18637 18077 20439 18075 19563 19899 19228 17790 19221 22059 21231 19504 23913 23166 23574 25002 22604 23409
 
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'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.551753-4.68187e-06
2-0.001542-0.01310.494799
30.3313312.81140.003175
4-0.266155-2.25840.013476
5-0.042136-0.35750.360869
60.2687772.28070.012765
7-0.308186-2.6150.00543
80.0272450.23120.408916
90.296072.51220.007119
10-0.325885-2.76520.00361
110.0914650.77610.220113
120.0977440.82940.204815
13-0.26177-2.22120.014742
140.1664591.41240.081063
150.0223720.18980.424987
16-0.229834-1.95020.027523
170.1822071.54610.063236
180.1320351.12040.133142
19-0.221369-1.87840.032189
200.1471071.24820.107992
210.0789130.66960.252628
22-0.307871-2.61240.005469
230.4483893.80470.000148
24-0.33775-2.86590.002724
250.0225280.19120.424469
260.2256851.9150.029733
27-0.165336-1.40290.082469
28-0.068357-0.580.281853
290.2248981.90830.030168
30-0.237676-2.01680.023726
310.0144240.12240.451465
320.1649741.39990.082926
33-0.211793-1.79710.038255
34-0.011376-0.09650.461684
350.2163581.83590.035254
36-0.21592-1.83210.035533
370.11550.98010.165171
380.0343550.29150.38575
39-0.095071-0.80670.211247
400.051050.43320.333091
410.0780920.66260.25484
42-0.147083-1.2480.10803
430.0773440.65630.256866
440.1247811.05880.146615
45-0.253161-2.14810.017534
460.2920182.47790.007782
47-0.16703-1.41730.080355
48-0.038656-0.3280.37193
490.1371891.16410.124117
50-0.129927-1.10250.136964
51-0.037111-0.31490.376876
520.1108440.94050.175041
53-0.099244-0.84210.201257
54-0.005006-0.04250.483119
550.1263741.07230.14358
56-0.137053-1.16290.124349
570.0342750.29080.386006
580.0694240.58910.278824
59-0.113273-0.96120.169845
600.0567690.48170.315739


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.551753-4.68187e-06
2-0.439888-3.73260.000188
30.1557951.3220.095183
40.1093260.92770.178341
5-0.158847-1.34790.090964
60.0425930.36140.359423
7-0.102603-0.87060.193429
8-0.224195-1.90240.030562
90.1446351.22730.111859
100.0979110.83080.204416
11-0.048322-0.410.341502
12-0.180043-1.52770.065482
13-0.280274-2.37820.010027
14-0.116543-0.98890.163011
15-0.00589-0.050.480138
16-0.086318-0.73240.233142
17-0.141348-1.19940.117157
180.1344411.14080.128873
190.1919181.62850.053895
200.0054270.0460.4817
210.0712950.6050.273555
22-0.213212-1.80920.0373
230.2577762.18730.015984
24-0.058571-0.4970.310355
25-0.036312-0.30810.379442
260.0339010.28770.387218
27-0.012537-0.10640.457789
28-0.132892-1.12760.131611
29-0.067755-0.57490.28357
300.050340.42720.335271
310.04060.34450.365738
32-0.157351-1.33520.093014
330.0507280.43040.334081
34-0.089212-0.7570.225764
350.0136540.11590.454045
36-0.064533-0.54760.292838
370.0752290.63830.26264
380.0266940.22650.410724
390.0333680.28310.388943
40-0.072277-0.61330.270809
41-0.107384-0.91120.182619
420.0129230.10970.456494
430.0315910.26810.394711
44-0.006909-0.05860.476707
45-0.05979-0.50730.306735
460.0727610.61740.269461
470.0620980.52690.299934
48-0.098916-0.83930.202031
49-0.002068-0.01750.493024
50-0.039166-0.33230.3703
510.0176820.150.440578
52-0.097973-0.83130.204268
53-0.008215-0.06970.472311
54-0.006732-0.05710.477302
55-0.019506-0.16550.434502
56-0.068301-0.57960.282012
570.0695310.590.278521
58-0.105975-0.89920.185764
590.0251190.21310.415911
60-0.104852-0.88970.188296
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228764212v6lvcmf4d2zvbdw/1yl3k1228764176.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228764212v6lvcmf4d2zvbdw/1yl3k1228764176.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228764212v6lvcmf4d2zvbdw/2iozn1228764176.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/08/t1228764212v6lvcmf4d2zvbdw/2iozn1228764176.ps (open in new window)


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