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Identification and Estimation of ARMA processes B Step 2 ACF D=1 en d=1

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Tue, 09 Dec 2008 15:10:33 -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/09/t12288607554iuzrr2ahewqcjo.htm/, Retrieved Tue, 09 Dec 2008 22:12:37 +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/09/t12288607554iuzrr2ahewqcjo.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 «
93.7 105.7 109.5 105.3 102.8 100.6 97.6 110.3 107.2 107.2 108.1 97.1 92.2 112.2 111.6 115.7 111.3 104.2 103.2 112.7 106.4 102.6 110.6 95.2 89 112.5 116.8 107.2 113.6 101.8 102.6 122.7 110.3 110.5 121.6 100.3 100.7 123.4 127.1 124.1 131.2 111.6 114.2 130.1 125.9 119 133.8 107.5 113.5 134.4 126.8 135.6 139.9 129.8 131 153.1 134.1 144.1 155.9 123.3 128.1 144.3 153 149.9 150.9 141 138.9 157.4 142.9 151.7 161 138.5 135.9 151.5 164 159.1 157 142.1 144.8 152.1 154.6 148.7 157.7 146.4 136.5
 
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
1-0.587013-4.9812e-06
20.1232181.04550.149635
30.0850570.72170.236398
4-0.10461-0.88760.188843
50.0697420.59180.277925
6-0.02813-0.23870.406013
70.0126490.10730.457414
8-0.162615-1.37980.085955
90.3056412.59350.005751
10-0.255096-2.16460.016869
110.1272761.080.14188
12-0.136107-1.15490.125974
130.0553040.46930.320146
140.0267690.22710.410478
15-0.037284-0.31640.37632
160.0640890.54380.294125
17-0.179262-1.52110.066309
180.3532152.99710.001869
19-0.283513-2.40570.009356
200.0813640.69040.246082
210.0566240.48050.316175
22-0.128793-1.09280.139052
230.2470062.09590.019803
24-0.210842-1.78910.038906
250.0509950.43270.333262
260.0422720.35870.360439
270.0389060.33010.371131
28-0.209123-1.77450.040106
290.2757612.33990.011032
30-0.247991-2.10430.019423
310.0998710.84740.199781
320.0880120.74680.228807
33-0.157605-1.33730.092663
340.0723110.61360.270713
35-0.078899-0.66950.252666
360.0758920.6440.260824
37-0.05835-0.49510.311011
380.0322670.27380.392512
39-0.054482-0.46230.322631
400.1259131.06840.144452
41-0.080648-0.68430.247985
420.0084150.07140.471638
43-0.00638-0.05410.47849
440.0582590.49430.311286
45-0.074551-0.63260.264505
460.0155890.13230.447566
470.0828630.70310.242126
48-0.165744-1.40640.081955
490.1517511.28760.100996
50-0.020642-0.17520.430725
51-0.138683-1.17680.121583
520.1575081.33650.092798
53-0.108967-0.92460.179127
540.0131460.11150.455747
550.0394250.33450.369476
56-0.021305-0.18080.428523
57-0.032301-0.27410.392402
580.0903210.76640.222973
59-0.05463-0.46360.322183
60-0.00022-0.00190.499257


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.587013-4.9812e-06
2-0.337748-2.86590.002724
3-0.028322-0.24030.405381
4-0.015981-0.13560.446256
50.022980.1950.422976
60.0088490.07510.470178
70.0230630.19570.422698
8-0.264072-2.24070.014065
90.1070460.90830.18337
100.0213490.18120.428379
110.0653140.55420.290577
12-0.219054-1.85870.033576
13-0.162883-1.38210.085606
14-0.085248-0.72340.235904
150.0258020.21890.41366
160.0973020.82560.205869
17-0.116063-0.98480.164003
180.1935671.64250.052426
190.076440.64860.259326
20-0.077765-0.65990.255724
210.0400410.33980.367514
22-0.059842-0.50780.306581
230.2589232.1970.015618
240.020690.17560.430567
25-0.101773-0.86360.195346
260.0715820.60740.272751
270.0745530.63260.264498
28-0.174889-1.4840.07109
290.1107880.94010.175163
300.0209120.17740.429828
310.0648020.54990.292058
32-0.083689-0.71010.23996
330.0233440.19810.421771
34-0.039808-0.33780.368254
35-0.089042-0.75550.226194
36-0.237153-2.01230.023965
370.0328860.2790.390503
380.009530.08090.467886
39-0.104381-0.88570.189364
400.0731730.62090.268316
41-0.046622-0.39560.346783
42-0.003036-0.02580.489759
43-0.038164-0.32380.373501
440.0370710.31460.377005
45-0.016547-0.14040.444365
46-0.055229-0.46860.320375
47-0.0699-0.59310.277479
48-0.087633-0.74360.229772
49-0.047129-0.39990.345207
500.0929740.78890.216376
51-0.015359-0.13030.448335
520.0082080.06960.472334
53-0.000627-0.00530.497884
54-0.005188-0.0440.482503
55-0.112525-0.95480.171436
560.0380220.32260.373955
570.1847721.56780.060652
58-0.041809-0.35480.361904
590.0523590.44430.329086
600.0419920.35630.361322
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t12288607554iuzrr2ahewqcjo/1415k1228860632.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t12288607554iuzrr2ahewqcjo/1415k1228860632.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t12288607554iuzrr2ahewqcjo/2uk8j1228860632.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t12288607554iuzrr2ahewqcjo/2uk8j1228860632.ps (open in new window)


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