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Consumentenvertrouwen-ACF

*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, 20 Dec 2010 11:57:25 +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/Dec/20/t129284614858dy80fefs62jmd.htm/, Retrieved Mon, 20 Dec 2010 12:55:52 +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/2010/Dec/20/t129284614858dy80fefs62jmd.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
9 11 13 12 13 15 13 16 10 14 14 45 13 8 7 3 3 4 4 0 -4 -14 -18 -8 -1 1 2 0 1 0 -1 -3 -3 -3 -4 -8 -9 -13 -18 -11 -9 -10 -13 -11 -5 -15 -6 -6 -3 -1 -3 -4 -6 0 -4 -2 -2 -6 -7 -6 -6 -3 -2 -5 -11 -11 -11 -10 -14 -8 -9 -5 -1 -2 -5 -4 -6 -2 -2 -2 -2 2 1 -8 -1 1 -1 2 2 1 -1 -2 -2 -1 -8 -4 -6 -3 -3 -7 -9 -11 -13 -11 -9 -17 -22 -25 -20 -24 -24 -22 -19 -18 -17 -11 -11 -12 -10 -15 -15 -15 -13 -8 -13 -9 -7 -4 -4 -2 0
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.278489-3.17530.000935
2-0.0086-0.09810.46102
3-0.080555-0.91850.180038
40.0120220.13710.445593
5-0.039347-0.44860.327226
60.0157650.17980.428813
70.0993571.13280.129683
8-0.037953-0.43270.332965
90.063410.7230.235493
10-0.072815-0.83020.203968
11-0.168269-1.91860.028616
120.003130.03570.485794
130.0434460.49540.310589
140.0026710.03050.487875
150.042180.48090.315691
160.0271730.30980.378598
17-0.010645-0.12140.45179
18-0.028039-0.31970.374859
190.0367820.41940.337815
20-0.031845-0.36310.358566
21-0.047649-0.54330.293933
22-0.002549-0.02910.488429
230.1049841.1970.116741
24-0.060548-0.69040.245602
250.0029320.03340.48669
260.0441530.50340.307762
27-0.1475-1.68180.047508
280.0300290.34240.366308
290.0179520.20470.419071
300.0362080.41280.340206
31-0.038999-0.44470.328653
32-0.044163-0.50350.307718
330.1108111.26340.104346
34-0.19918-2.2710.012396
350.0612480.69830.243107
36-0.034774-0.39650.346199
370.0462320.52710.299504
380.0700220.79840.213055
39-0.018355-0.20930.417277
40-0.087315-0.99550.16066
41-0.03652-0.41640.338905
420.1273551.45210.074446
43-0.037312-0.42540.335618
440.0212520.24230.404463
450.0647730.73850.230762
460.0049980.0570.477321
47-0.05084-0.57970.281573
480.0129740.14790.441317
490.0203990.23260.408227
50-0.056026-0.63880.262041
510.0421620.48070.315763
520.015450.17620.430222
53-0.051399-0.5860.279432
540.018090.20630.418454
55-0.007832-0.08930.464491
560.0555720.63360.263723
57-0.097341-1.10990.134554
580.0471920.53810.295722
59-0.095195-1.08540.139878
600.0086880.09910.460624


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.278489-3.17530.000935
2-0.0934-1.06490.144443
3-0.119406-1.36140.087866
4-0.053002-0.60430.273342
5-0.069439-0.79170.214981
6-0.030194-0.34430.3656
70.0950831.08410.140161
80.0146440.1670.433827
90.0797940.90980.182307
10-0.015472-0.17640.430124
11-0.207464-2.36550.009743
12-0.11963-1.3640.087463
13-0.040037-0.45650.324397
14-0.050819-0.57940.281653
150.0195270.22260.412084
160.0337660.3850.350436
170.0396590.45220.325946
180.0377510.43040.333797
190.0677330.77230.220676
200.0131980.15050.440309
21-0.093146-1.0620.145097
22-0.130572-1.48880.069487
230.0286820.3270.372086
24-0.039211-0.44710.327781
25-0.019717-0.22480.411241
260.0840320.95810.169892
27-0.102367-1.16720.12264
28-0.022239-0.25360.400118
290.0258890.29520.384164
300.0235160.26810.394514
31-0.034258-0.39060.348367
32-0.156361-1.78280.038477
330.0476240.5430.294032
34-0.14622-1.66720.048945
35-0.078929-0.89990.184911
36-0.032159-0.36670.357233
37-0.009949-0.11340.454928
380.0579320.66050.255041
390.0287650.3280.371729
40-0.070018-0.79830.213067
41-0.065357-0.74520.228753
420.0407770.46490.321379
43-0.007948-0.09060.463968
440.0118020.13460.446581
450.0180570.20590.418603
460.0254820.29050.385932
470.0104540.11920.452654
480.0110770.12630.449848
490.0614940.70110.242234
50-0.019992-0.22790.410024
51-0.049007-0.55880.288643
52-0.019365-0.22080.412798
53-0.043893-0.50050.3088
54-0.006009-0.06850.47274
550.0004470.00510.49797
560.0671290.76540.222715
57-0.020055-0.22870.409747
58-0.012377-0.14110.443998
59-0.114081-1.30070.097827
60-0.065888-0.75120.226934
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/10jip1292846242.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/10jip1292846242.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/2bshs1292846242.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/2bshs1292846242.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/3bshs1292846242.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/20/t129284614858dy80fefs62jmd/3bshs1292846242.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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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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