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OPGAVE 6 BIS oef 2 stap 2

*Unverified author*
R Software Module: /rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Fri, 04 Jun 2010 16:29:40 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jun/04/t1275669032xrjuyhxld4c8hdj.htm/, Retrieved Fri, 04 Jun 2010 18:30:35 +0200
 
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/2010/Jun/04/t1275669032xrjuyhxld4c8hdj.htm/},
    year = {2010},
}
@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 = {2010},
    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:
KDGP2W21
 
Dataseries X:
» Textbox « » Textfile « » CSV «
1954 2302 3054 2414 2226 2725 2589 3470 2400 3180 4009 3924 2072 2434 2956 2828 2687 2629 3150 4119 3030 3055 3821 4001 2529 2472 3134 2789 2758 2993 3282 3437 2804 3076 3782 3889 2271 2452 3084 2522 2769 3438 2839 3746 2632 2851 3871 3618 2389 2344 2678 2492 2858 2246 2800 3869 3007 3023 3907 4209 2353 2570 2903 2910 3782 2759 2931 3641 2794 3070 3576 4106 2452 2206 2488 2416 2534 2521 3093 3903 2907 3025 3812 4209 2138 2419 2622 2912 2708 2798 3254 2895 3263 3736 4077 4097 2175 3138 2823 2498 2822 2738 4137 3515 3785 3632 4504 4451 2550 2867 3458 2961 3163 2880 3331 3062 3534 3622 4464 5411 2564 2820 3508 3088 3299 2939 3320 3418 3604 3495 4163 4882 2211 3260 2992 2425 2707 3244 3965 3315 3333 3583 4021 4904 2252 2952 3573 3048 3059 2731 3563 3092 3478 3478 4308 5029 2075 3264 3308 3688 3136 2824 3644 4694 2914 3686 4358 5587 2265 3685 3754 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
1-0.345728-4.71512e-06
2-0.23915-3.26160.000659
30.0491750.67070.251636
40.1589952.16840.015699
50.0162310.22140.412526
6-0.273607-3.73150.000126
70.0205540.28030.389773
80.1384991.88890.030232
90.07861.0720.142563
10-0.232159-3.16620.000902
11-0.238476-3.25240.000679
120.74031910.09660
13-0.249138-3.39780.000415
14-0.198222-2.70340.00375
150.0568920.77590.219396
160.1354711.84760.033126
170.0109260.1490.440855
18-0.25638-3.49660.000295
190.0671970.91640.180311
200.0615390.83930.201194
210.0778851.06220.144758
22-0.208444-2.84280.002486
23-0.18832-2.56830.005502
240.6477518.83410
25-0.210286-2.86790.002305
26-0.166532-2.27120.01214
270.0396990.54140.294431
280.0865081.17980.119791
290.0375920.51270.304391
30-0.215488-2.93890.001856
310.0481420.65660.256136
320.0321070.43790.330989
330.1059221.44460.075129
34-0.224695-3.06440.001253
35-0.15526-2.11750.017775
360.5950828.11580
37-0.203901-2.78080.00299
38-0.14848-2.0250.022149
390.0282350.38510.35031
400.1123351.5320.063605
410.0399350.54460.293327
42-0.221144-3.0160.00146
430.0262070.35740.360594
440.0421680.57510.282959
450.097981.33630.091546
46-0.194599-2.6540.004322
47-0.140357-1.91420.028564
480.513777.00690
49-0.143402-1.95570.025996
50-0.161769-2.20620.014296
510.024260.33090.37056
520.1233181.68180.04714
53-0.017586-0.23980.405358
54-0.169144-2.30680.011083
550.072510.98890.161999
56-0.005617-0.07660.469509
570.093261.27190.102498
58-0.208649-2.84560.002465
59-0.075616-1.03130.151879
600.4323135.8960


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.345728-4.71512e-06
2-0.40737-5.55580
3-0.283278-3.86347.7e-05
4-0.058817-0.80220.211743
50.0689790.94070.174027
6-0.211444-2.88370.002197
7-0.253057-3.45120.000345
8-0.214893-2.93070.001903
9-0.032923-0.4490.326976
10-0.199769-2.72450.003527
11-0.676645-9.22820
120.2046622.79120.002899
130.0257250.35080.36305
140.0330670.4510.326268
150.1252131.70770.044682
160.0676750.9230.178611
170.0586610.80.212356
180.0269220.36720.356958
190.1690712.30580.011112
200.0228790.3120.377682
21-0.028323-0.38630.349865
22-0.070716-0.96440.168038
23-0.237135-3.23410.000722
240.0351880.47990.31593
250.0570540.77810.218744
260.1136681.55020.061394
270.0984721.3430.090458
28-0.086193-1.17550.120647
29-0.022751-0.31030.378344
300.0474470.64710.259185
310.014810.2020.420078
320.0097070.13240.44741
330.0460760.62840.265258
34-0.1169-1.59430.056284
35-0.193552-2.63970.004501
360.0436290.5950.276276
370.0027260.03720.485191
38-0.057898-0.78960.215375
39-0.089808-1.22480.111096
40-0.023018-0.31390.376967
410.0389710.53150.297853
420.0501790.68440.247303
430.0065940.08990.464222
440.005160.07040.471988
45-0.097035-1.32340.093666
460.0197440.26930.394007
470.0843311.15010.125785
48-0.006837-0.09320.462904
490.0476180.64940.258431
50-0.045731-0.62370.266801
51-0.026338-0.35920.359924
520.0593710.80970.20957
53-0.109465-1.49290.068579
54-0.083767-1.14240.127372
550.0294210.40120.344349
56-0.020089-0.2740.392201
570.059570.81240.208791
58-0.021095-0.28770.38695
590.0188550.25710.398674
60-0.064185-0.87540.19125
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Jun/04/t1275669032xrjuyhxld4c8hdj/1b5q31275668978.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Jun/04/t1275669032xrjuyhxld4c8hdj/1b5q31275668978.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Jun/04/t1275669032xrjuyhxld4c8hdj/24w7o1275668978.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Jun/04/t1275669032xrjuyhxld4c8hdj/24w7o1275668978.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; 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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Software written by Ed van Stee & Patrick Wessa


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