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ACF suiker zonder differentiatie

*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: Tue, 09 Dec 2008 09:11:56 -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/t1228839154q7gnznuae8u9ryd.htm/, Retrieved Tue, 09 Dec 2008 16:12:36 +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/t1228839154q7gnznuae8u9ryd.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 «
101.02 100.67 100.47 100.38 100.33 100.34 100.37 100.39 100.21 100.21 100.22 100.28 100.25 100.25 100.21 100.16 100.18 100.1 99.96 99.88 99.88 99.86 99.84 99.8 99.82 99.81 99.92 100.03 99.99 100.02 100.01 100.13 100.33 100.13 99.96 100.05 99.83 99.8 100.01 100.1 100.13 100.16 100.41 101.34 101.65 101.85 102.07 102.12 102.14 102.21 102.28 102.19 102.33 102.54 102.44 102.78 102.9 103.08 102.77 102.65 102.71 103.29 102.86 103.45 103.72 103.65 103.83 104.45 105.14 105.07 105.31 105.19 105.3 105.02 105.17 105.28 105.45 105.38 105.8 105.96 105.08 105.11 105.61 105.5
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9730768.91840
20.9423818.63710
30.9162068.39720
40.8874278.13340
50.8463797.75720
60.8075557.40140
70.7720527.0760
80.7333196.7210
90.6947346.36730
100.6574586.02570
110.6221695.70230
120.5801415.31710
130.5386224.93652e-06
140.4959954.54599e-06
150.4538634.15973.8e-05
160.4077353.7370.000169
170.3698253.38950.000534
180.3376233.09440.001339
190.3029582.77670.003385
200.2680422.45660.008042
210.2357122.16030.016798
220.2063851.89150.030999
230.1705761.56340.060864
240.1392941.27670.102621
250.107390.98420.163911
260.0724240.66380.254327
270.0331240.30360.381096
28-0.00325-0.02980.488154
29-0.037878-0.34720.36467
30-0.070559-0.64670.259799
31-0.103325-0.9470.173181
32-0.133163-1.22050.112853
33-0.162364-1.48810.070236
34-0.193597-1.77430.039815
35-0.223704-2.05030.021727
36-0.253386-2.32230.011318
37-0.283992-2.60280.005464
38-0.312581-2.86490.002635
39-0.337902-3.09690.001329
40-0.362085-3.31860.00067
41-0.383077-3.5110.00036
42-0.393713-3.60840.000261
43-0.399034-3.65720.000222
44-0.401518-3.680.000205
45-0.403323-3.69650.000194
46-0.402475-3.68870.000199
47-0.398796-3.6550.000223
48-0.395797-3.62750.000245
49-0.393927-3.61040.000259
50-0.389812-3.57270.000294
51-0.387557-3.5520.000315
52-0.387187-3.54860.000318
53-0.384307-3.52220.000347
54-0.378869-3.47240.000409
55-0.37328-3.42120.000483
56-0.36631-3.35730.000592
57-0.359409-3.2940.000723
58-0.35134-3.22010.000911
59-0.342867-3.14240.001157
60-0.334071-3.06180.001477


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9730768.91840
2-0.084627-0.77560.220076
30.0747590.68520.247559
4-0.076153-0.6980.243567
5-0.234131-2.14580.017385
60.0460250.42180.337115
70.0007660.0070.497207
8-0.063672-0.58360.28054
90.0439230.40260.344145
10-0.038065-0.34890.36403
110.0075190.06890.47261
12-0.13606-1.2470.10793
13-0.012473-0.11430.454631
14-0.075809-0.69480.24455
15-0.013842-0.12690.449675
16-0.064686-0.59290.277435
170.1377061.26210.105203
180.0598360.54840.292435
19-0.058815-0.5390.29564
20-0.006077-0.05570.477858
21-0.063034-0.57770.282501
22-0.011398-0.10450.458523
23-0.110441-1.01220.157173
240.069380.63590.263292
25-0.065641-0.60160.274528
26-0.079754-0.7310.23342
27-0.050958-0.4670.32084
28-0.054013-0.4950.310933
29-0.014867-0.13630.445972
300.0370430.33950.367539
31-0.042191-0.38670.349984
320.017410.15960.436804
33-0.052527-0.48140.315734
34-0.035263-0.32320.373677
35-0.043892-0.40230.344252
36-0.045665-0.41850.338315
37-0.065513-0.60040.274917
380.0706750.64770.259457
39-0.028355-0.25990.397798
400.0100130.09180.46355
410.0444070.4070.342524
420.1204091.10360.136466
430.0123510.11320.455073
440.0380180.34840.364189
45-0.028223-0.25870.398261
46-0.03647-0.33430.369511
470.0345060.31620.376299
48-0.035797-0.32810.371831
49-0.032689-0.29960.382613
500.0130550.11960.452523
51-0.094932-0.87010.193373
52-0.037922-0.34760.364519
530.0028720.02630.48953
54-0.021442-0.19650.422338
550.007880.07220.471298
560.0247890.22720.410411
57-0.06812-0.62430.26705
580.0579510.53110.298365
590.0344010.31530.376661
60-0.026653-0.24430.403806
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839154q7gnznuae8u9ryd/1twi91228839114.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839154q7gnznuae8u9ryd/1twi91228839114.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839154q7gnznuae8u9ryd/2dzs21228839114.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839154q7gnznuae8u9ryd/2dzs21228839114.ps (open in new window)


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