Home » date » 2008 » Dec » 09 »

ACF suiker met d=1

*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 09:13:46 -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/t1228839301uwkr6h4umweapwj.htm/, Retrieved Tue, 09 Dec 2008 16:15:01 +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/t1228839301uwkr6h4umweapwj.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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0725450.66090.255247
2-0.044992-0.40990.341468
30.1365061.24360.108569
40.1611821.46840.072882
5-0.100938-0.91960.180225
60.0150120.13680.445772
70.1218321.10990.135115
80.0213910.19490.422981
9-0.071302-0.64960.258876
10-0.087296-0.79530.214353
110.2227762.02960.022801
12-0.021897-0.19950.421182
13-0.069339-0.63170.264657
140.0698320.63620.2632
150.1596311.45430.074816
16-0.134931-1.22930.11122
17-0.02104-0.19170.424228
180.2271152.06910.020823
19-0.097752-0.89060.187869
20-0.038243-0.34840.364206
210.1627861.4830.070925
220.0945690.86160.195705
230.0453370.4130.340321
240.0458110.41740.338746
250.0812940.74060.230505
260.0527080.48020.316176
27-0.103778-0.94550.173582
28-0.089397-0.81440.208861
290.0686480.62540.266708
30-0.111233-1.01340.156912
31-0.076021-0.69260.245253
320.0511870.46630.321099
330.0020340.01850.492631
34-0.101496-0.92470.178909
35-0.006881-0.06270.475084
36-0.003805-0.03470.486216
37-0.156183-1.42290.079257
38-0.077493-0.7060.241085
390.0393390.35840.36048
40-0.033249-0.30290.381356
41-0.083513-0.76080.224454
42-0.172645-1.57290.059777
43-0.029959-0.27290.392791
440.0181830.16570.434416
45-0.093681-0.85350.197926
46-0.013156-0.11990.452443
470.032190.29330.385027
48-0.079724-0.72630.234844
49-0.085183-0.77610.21996
500.0152050.13850.44508
51-0.035506-0.32350.373574
52-0.015653-0.14260.443472
53-0.061184-0.55740.289374
54-0.040086-0.36520.357946
55-0.019006-0.17320.431477
56-0.004782-0.04360.482678
570.0283080.25790.398561
58-0.004795-0.04370.482629
59-0.054001-0.4920.31202
60-0.078284-0.71320.238862


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0725450.66090.255247
2-0.050521-0.46030.323263
30.1447291.31850.095475
40.1405291.28030.102006
5-0.113536-1.03440.151986
60.0283430.25820.398439
70.0733560.66830.252898
80.0128580.11710.453515
9-0.041815-0.3810.352106
10-0.126804-1.15520.125654
110.2251832.05150.021685
12-0.042405-0.38630.350122
13-0.015764-0.14360.443077
140.0383910.34980.363703
150.0822060.74890.228009
16-0.08392-0.76450.223355
17-0.000551-0.0050.498004
180.1639751.49390.069499
19-0.162152-1.47730.071693
200.0692780.63110.264839
210.1540121.40310.082156
22-0.039143-0.35660.361144
230.1582211.44150.076609
24-0.015024-0.13690.445731
250.0302540.27560.391759
26-0.01782-0.16240.435712
27-0.101168-0.92170.179681
28-0.047707-0.43460.332478
29-0.085468-0.77870.2192
30-0.043502-0.39630.346443
310.0393570.35860.360416
32-0.027072-0.24660.402899
33-0.013029-0.11870.452901
34-0.013803-0.12580.450116
35-0.014667-0.13360.447012
36-0.122054-1.1120.134683
37-0.106659-0.97170.16701
38-0.060534-0.55150.29139
390.022420.20430.419325
40-0.00287-0.02610.489603
41-0.042863-0.39050.348582
42-0.185619-1.69110.047288
43-0.023005-0.20960.417254
440.0110040.10030.460192
45-0.028198-0.25690.398948
46-0.02452-0.22340.411893
47-0.071333-0.64990.258784
480.0399650.36410.358356
49-0.023815-0.2170.414383
50-0.004634-0.04220.483212
510.0405570.36950.35635
520.0227040.20680.418319
530.0165580.15090.440229
54-0.042516-0.38730.349747
550.0314350.28640.387648
560.0245830.2240.411668
570.0857130.78090.218547
580.0414960.3780.35318
59-0.054087-0.49280.311743
600.0465670.42420.336244
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839301uwkr6h4umweapwj/1fgfg1228839220.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839301uwkr6h4umweapwj/1fgfg1228839220.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839301uwkr6h4umweapwj/2ydcd1228839220.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/09/t1228839301uwkr6h4umweapwj/2ydcd1228839220.ps (open in new window)


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