Home » date » 2008 » Dec » 15 »

ARIMA ACF prof bach d=1 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: Mon, 15 Dec 2008 15:44:07 -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/15/t1229381101iq25fdux2xl23xe.htm/, Retrieved Mon, 15 Dec 2008 23:45:01 +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/15/t1229381101iq25fdux2xl23xe.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 «
13363 12530 11420 10948 10173 10602 16094 19631 17140 14345 12632 12894 11808 10673 9939 9890 9283 10131 15864 19283 16203 13919 11937 11795 11268 10522 9929 9725 9372 10068 16230 19115 18351 16265 14103 14115 13327 12618 12129 11775 11493 12470 20792 22337 21325 18581 16475 16581 15745 14453 13712 13766 13336 15346 24446 26178 24628 21282 18850 18822 18060 17536 16417 15842 15188 16905 25430 27962 26607 23364 20827 20506 19181 18016 17354 16256 15770 17538 26899 28915 25247 22856 19980 19856 16994 16839 15618 15883 15513 17106 25272 26731 22891 19583 16939 16757 15435 14786 13680 13208 12707 14277 22436 23229 18241 16145 13994 14780 13100 12329 12463 11532 10784 13106 19491 20418 16094 14491 13067
 
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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3883524.21862.4e-05
2-0.172981-1.8790.031352
3-0.306243-3.32670.000586
4-0.235136-2.55420.005958
5-0.103389-1.12310.131839
6-0.14946-1.62350.05357
7-0.081076-0.88070.190132
8-0.199735-2.16970.016018
9-0.267245-2.9030.002206
10-0.123256-1.33890.091588
110.3898234.23462.3e-05
120.8787789.5460
130.3246283.52643e-04
14-0.164192-1.78360.038531
15-0.267881-2.90990.002161
16-0.232941-2.53040.006355
17-0.099689-1.08290.140531
18-0.126393-1.3730.086181
19-0.075911-0.82460.205631
20-0.182387-1.98120.024946
21-0.233268-2.53390.006295
22-0.085111-0.92450.178546
230.3682724.00055.5e-05
240.7622458.28010
250.2656262.88540.002324
26-0.157734-1.71340.04463
27-0.236569-2.56980.00571
28-0.205948-2.23720.013577
29-0.092221-1.00180.159251
30-0.120116-1.30480.097251
31-0.067897-0.73750.231127
32-0.159492-1.73250.042896
33-0.202796-2.20290.014771
34-0.05514-0.5990.275169
350.350053.80250.000114
360.663377.2060
370.2091722.27220.012443
38-0.171796-1.86620.032249
39-0.216438-2.35110.010188
40-0.185535-2.01540.023066
41-0.077369-0.84040.20118
42-0.090669-0.98490.163339
43-0.047975-0.52110.301622
44-0.143962-1.56380.060268
45-0.175117-1.90230.029788
46-0.034643-0.37630.353677
470.3128563.39850.000462
480.5551656.03060
490.1639421.78090.038754
50-0.160288-1.74120.04213
51-0.185538-2.01550.023064
52-0.159414-1.73170.042972
53-0.069559-0.75560.225696
54-0.067879-0.73740.231184
55-0.02946-0.320.37476
56-0.115154-1.25090.106725
57-0.1502-1.63160.052715
58-0.033825-0.36740.356976
590.2671972.90250.002209
600.4638045.03821e-06


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3883524.21862.4e-05
2-0.381306-4.1423.2e-05
3-0.090076-0.97850.164921
4-0.144471-1.56940.059622
5-0.073816-0.80180.212126
6-0.276727-3.0060.001617
7-0.02621-0.28470.388181
8-0.468295-5.0871e-06
9-0.364252-3.95686.5e-05
10-0.557935-6.06070
110.0787230.85510.197101
120.6087836.61310
13-0.258729-2.81050.002896
140.1981072.1520.016717
150.1395771.51620.066073
160.006640.07210.471313
170.197852.14920.01683
180.1201471.30510.097194
190.0106410.11560.454087
200.1185111.28740.100243
210.1059881.15130.125963
22-0.002409-0.02620.489586
230.024040.26110.397219
240.0101930.11070.45601
25-0.054391-0.59080.277878
26-0.053737-0.58370.280259
27-0.037524-0.40760.342146
280.0162050.1760.430287
29-0.123251-1.33890.091596
30-0.08342-0.90620.183345
310.0234250.25450.399793
32-0.100468-1.09140.138669
33-0.035411-0.38470.350589
340.0059430.06460.474316
35-0.02592-0.28160.389387
36-0.010074-0.10940.456522
370.0145850.15840.437192
38-0.127345-1.38330.084588
39-0.00469-0.05090.479727
40-0.093565-1.01640.155765
41-0.024518-0.26630.395224
420.0095170.10340.458916
43-0.03876-0.4210.337243
44-0.05541-0.60190.274194
450.0728010.79080.215317
46-0.098727-1.07240.142854
47-0.036891-0.40070.344667
48-0.092727-1.00730.157933
49-0.013064-0.14190.443695
50-0.029232-0.31750.375695
510.0041290.04490.48215
52-0.025958-0.2820.389227
53-0.030164-0.32770.371873
54-0.034353-0.37320.354846
550.0643480.6990.242964
560.0530720.57650.282686
57-0.009974-0.10830.456952
580.0164010.17820.429452
590.043920.47710.317089
60-0.027314-0.29670.383608
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229381101iq25fdux2xl23xe/1kegu1229381042.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229381101iq25fdux2xl23xe/1kegu1229381042.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229381101iq25fdux2xl23xe/2g3y21229381043.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/15/t1229381101iq25fdux2xl23xe/2g3y21229381043.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 0.3 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 0.3 ; 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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