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ACF Uitvoer

*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: Mon, 22 Dec 2008 09:25:42 -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/22/t1229963248el34b6pndtbrbu2.htm/, Retrieved Mon, 22 Dec 2008 17:27:30 +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/2008/Dec/22/t1229963248el34b6pndtbrbu2.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},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
15916,4 16535,9 15796 14418,6 15044,5 14944,2 16754,8 14254 15454,9 15644,8 14568,3 12520,2 14803 15873,2 14755,3 12875,1 14291,1 14205,3 15859,4 15258,9 15498,6 15106,5 15023,6 12083 15761,3 16943 15070,3 13659,6 14768,9 14725,1 15998,1 15370,6 14956,9 15469,7 15101,8 11703,7 16283,6 16726,5 14968,9 14861 14583,3 15305,8 17903,9 16379,4 15420,3 17870,5 15912,8 13866,5 17823,2 17872 17420,4 16704,4 15991,2 16583,6 19123,5 17838,7 17209,4 18586,5 16258,1 15141,6 19202,1 17746,5 19090,1 18040,3 17515,5 17751,8 21072,4 17170 19439,5 19795,4 17574,9 16165,4 19464,6 19932,1 19961,2 17343,4 18924,2 18574,1 21350,6 18594,6 19823,1 20844,4 19640,2 17735,4 19813,6 22238,5 20682,2 17818,6 21872,1 22117 21865,9 23451,3 20953,7 22497,3
 
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'George Udny Yule' @ 72.249.76.132


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7050496.83570
20.6165695.97790
30.6577056.37670
40.6658436.45560
50.5972335.79040
60.6226926.03720
70.5574035.40420
80.5809535.63260
90.4869374.7214e-06
100.4043113.91998.4e-05
110.4889764.74084e-06
120.6373426.17930
130.419884.07094.9e-05
140.336213.25970.000777
150.3687423.57510.000278
160.3661843.55030.000302
170.3443683.33880.000604
180.349933.39270.000507
190.299032.89920.002328
200.3140763.04510.001509
210.2279832.21040.014753
220.1489071.44370.076073
230.2551382.47370.007584
240.3286473.18630.000978
250.1817241.76190.04067
260.1087151.0540.147286
270.1115191.08120.141183
280.1092351.05910.146139
290.0894060.86680.194124
300.0760470.73730.231388
310.0366730.35560.361486
320.0375130.36370.358447
33-0.037273-0.36140.359313
34-0.105245-1.02040.155081
35-0.023168-0.22460.411381
360.0415630.4030.343942
37-0.07597-0.73660.231613
38-0.138487-1.34270.091304
39-0.150393-1.45810.074071
40-0.127445-1.23560.109838
41-0.159838-1.54970.062288
42-0.164655-1.59640.05688
43-0.183036-1.77460.039601
44-0.167834-1.62720.05352
45-0.251434-2.43770.00833
46-0.283679-2.75040.00357
47-0.232654-2.25570.013205
48-0.173654-1.68360.047785
49-0.259734-2.51820.006743
50-0.309351-2.99930.001732
51-0.312772-3.03240.001568
52-0.28184-2.73250.003754
53-0.315472-3.05860.001448
54-0.299959-2.90820.002268
55-0.311006-3.01530.00165
56-0.279764-2.71240.003972
57-0.327405-3.17430.001015
58-0.353969-3.43190.000446
59-0.298733-2.89630.002348
60-0.237882-2.30640.011644


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7050496.83570
20.237572.30330.011733
30.3345883.24390.000816
40.2209042.14170.0174
50.0304910.29560.384087
60.1723071.67060.049066
7-0.094639-0.91760.180599
80.1389471.34710.090587
9-0.206799-2.0050.02392
10-0.185432-1.79780.037707
110.2032551.97060.025854
120.4213224.08494.6e-05
13-0.307355-2.97990.001835
14-0.268899-2.60710.00531
15-0.070645-0.68490.247536
160.0504210.48880.313044
170.1885521.82810.035355
18-0.008898-0.08630.465717
19-0.129848-1.25890.105588
20-0.07014-0.680.249076
210.0614780.59610.276286
220.0360920.34990.363588
230.0385810.37410.354604
24-0.099805-0.96760.167853
25-0.031619-0.30660.379929
26-0.01965-0.19050.424661
27-0.061921-0.60030.274861
28-0.019941-0.19330.423558
29-0.12973-1.25780.105793
30-0.018235-0.17680.430023
31-0.007883-0.07640.469621
320.0171060.16580.434316
330.0437130.42380.336336
34-0.053213-0.51590.30356
35-0.081161-0.78690.216663
360.0766470.74310.229632
37-0.00201-0.01950.492247
38-0.039077-0.37890.352822
39-0.104897-1.0170.155879
400.0137320.13310.447185
41-0.063394-0.61460.270144
420.0269740.26150.397131
430.0024520.02380.490541
440.0228080.22110.412735
45-0.061806-0.59920.27523
460.011760.1140.454733
47-0.049546-0.48040.31604
48-0.053264-0.51640.303389
490.0191540.18570.426538
50-0.006837-0.06630.473644
510.0130750.12680.449699
52-0.025176-0.24410.403848
53-0.046387-0.44970.326968
540.048440.46960.319848
55-0.021418-0.20770.417972
560.054910.53240.297863
570.0847510.82170.206665
58-0.05397-0.52330.301011
59-0.004921-0.04770.481025
60-0.025171-0.2440.403864
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229963248el34b6pndtbrbu2/1geog1229963140.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229963248el34b6pndtbrbu2/1geog1229963140.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229963248el34b6pndtbrbu2/28nho1229963140.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/22/t1229963248el34b6pndtbrbu2/28nho1229963140.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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