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CaseStatistiek - PCF 2

*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: Wed, 30 Dec 2009 16:01:02 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/31/t12622141237iawnibaqr98xgb.htm/, Retrieved Thu, 31 Dec 2009 00:02:05 +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/2009/Dec/31/t12622141237iawnibaqr98xgb.htm/},
    year = {2009},
}
@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 = {2009},
    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 «
15 14.4 13.5 12.8 12.3 12.2 14.5 17.2 18 18.1 18 18.3 18.7 18.6 18.3 17.9 17.4 17.4 20.1 23.2 24.2 24.2 23.9 23.8 23.8 23.3 22.4 21.5 20.5 19.9 22 24.9 25.7 25.3 24.4 23.8 23.5 23 22.2 21.4 20.3 19.5 21.7 24.7 25.3 24.9 24.1 23.4 23.1 22.4 21.3 20.3 19.3 18.7 21 24 24.8 24.2 23.3 22.7 22.3 21.8 21.2 20.5 19.7 19.2 21.2 23.9 24.8 24.2 23 22.2 21.8 21.2 20.5 19.7 19 18.4 20.7 24.5 26 25.2 24.1 23.7 23.5 23.1 22.7 22.5 21.7 20.5 21.9 22.9 21.5 19 17 16.1 15.9 15.7 15.1 14.8 14.3 14.5 18.9 21.6 20.4 17.9 15.7 14.5 14 13.9 14.4 15.8 15.6 14.7 16.7 17.9 18.7 20.1 19.5 19.4 18.6 17.8 17.1 16.5 15.5 14.9 18.6 19.1 18.8 18.2 18 19 20.7 21.2 20.7 19.6 18.6 18.7 23.8 24.9 24.8 23.8 22.3 21.7 20.7 19.7 18.4 17.4 17 18 23.8 25.5 25.6 23.7 22 21.3 20.7 20.4 20.3 20.4 19.8 19.5 23.1 23.5 23.5 22.9 21.9 21.5 20.5 20.2 19.4 19.2 18.8 18.8 22.6 23.3 23 etc...
 
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
10.93194313.24540
20.78099411.10
30.618898.79610
40.501137.12240
50.4368396.20870
60.4010425.69990
70.3556275.05440
80.2780043.95125.4e-05
90.1692462.40540.008527
100.0523110.74350.229027
11-0.033635-0.4780.316567
12-0.062737-0.89170.18682
13-0.032507-0.4620.322286
140.0244130.3470.364484
150.0658030.93520.17539
160.0670390.95280.170915
170.0383730.54540.293046
180.0004270.00610.497581
19-0.02715-0.38590.35
20-0.039554-0.56220.287311
21-0.042803-0.60830.271822
22-0.046932-0.6670.252758
23-0.06242-0.88720.188025
24-0.093535-1.32940.092611
25-0.134998-1.91870.028217
26-0.169882-2.41450.008325
27-0.189027-2.68660.00391
28-0.182436-2.59290.005106
29-0.153819-2.18620.014976
30-0.115005-1.63450.051853
31-0.080519-1.14440.126907
32-0.06434-0.91440.180789
33-0.0739-1.05030.147415
34-0.106376-1.51190.066062
35-0.144082-2.04780.020937
36-0.169367-2.40720.008488
37-0.171425-2.43640.00785
38-0.160493-2.2810.011795
39-0.149665-2.12710.017311
40-0.150441-2.13820.016852
41-0.164555-2.33880.010163
42-0.18314-2.60290.004965
43-0.193381-2.74850.003265
44-0.184903-2.6280.004625
45-0.151654-2.15540.016157
46-0.096023-1.36470.086927
47-0.035635-0.50650.306541
480.0100940.14350.443035
490.02920.4150.33929
500.026730.37990.352208
510.0131690.18720.425859
520.0005060.00720.497132
53-0.008964-0.12740.449374
54-0.014329-0.20370.419414
55-0.017344-0.24650.402773
56-0.02096-0.29790.383045
57-0.029866-0.42450.335834
58-0.046208-0.65670.256048
59-0.06416-0.91190.181459
60-0.074537-1.05940.145348


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.93194313.24540
2-0.665672-9.4610
30.367565.2240
40.1885972.68050.00398
5-0.102878-1.46220.072623
6-0.083434-1.18580.118542
7-0.139541-1.98320.024347
8-0.081811-1.16280.123151
9-0.088858-1.26290.10404
10-0.016275-0.23130.408654
110.1983872.81960.002644
120.079511.130.129899
130.127731.81540.035474
14-0.087718-1.24670.106974
15-0.059259-0.84220.200329
160.002280.03240.487092
170.0475310.67550.25005
18-0.156208-2.22010.013761
19-0.076703-1.09020.138472
20-0.068866-0.97880.164433
21-0.003513-0.04990.480117
220.0222140.31570.376269
23-0.006714-0.09540.462038
240.0134280.19080.42442
250.014340.20380.419354
260.0476060.67660.249715
27-0.097017-1.37890.084731
280.1349691.91830.028243
290.0358510.50950.305467
30-0.038383-0.54550.292996
31-0.041993-0.59680.275644
32-0.159705-2.26980.012137
33-0.094835-1.34790.089607
34-0.106808-1.5180.065286
350.0389050.55290.290457
360.0071210.10120.459743
370.0394760.56110.287688
38-0.017032-0.24210.404483
390.0915691.30140.097295
400.0483210.68680.24651
410.0072860.10350.458815
420.0338550.48120.315458
43-0.095522-1.35760.088048
44-0.041584-0.5910.277582
450.0129340.18380.427169
460.039740.56480.286416
47-0.027785-0.39490.346669
48-0.01544-0.21940.413263
49-0.008508-0.12090.451938
50-0.016024-0.22770.410038
51-0.063452-0.90180.184112
52-0.01442-0.20490.418911
530.0002130.0030.498795
540.0345150.49060.312138
550.0454770.64630.259393
560.0200650.28520.3879
57-0.019265-0.27380.392256
580.0095520.13580.446073
59-0.021183-0.30110.381835
60-0.04232-0.60150.274095
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/31/t12622141237iawnibaqr98xgb/1rgi01262214060.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/31/t12622141237iawnibaqr98xgb/1rgi01262214060.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/31/t12622141237iawnibaqr98xgb/29ytv1262214060.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/31/t12622141237iawnibaqr98xgb/29ytv1262214060.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
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 (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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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