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*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, 29 Dec 2009 13:25:23 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/29/t1262118351un1si8euruzqxdk.htm/, Retrieved Tue, 29 Dec 2009 21:25:54 +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/2009/Dec/29/t1262118351un1si8euruzqxdk.htm/},
    year = {2009},
}
@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 = {2009},
    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 «
-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
 
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
10.8882897.10630
20.8003436.40270
30.7395125.91610
40.6747675.39811e-06
50.5904494.72367e-06
60.5176974.14165.2e-05
70.4363453.49080.000439
80.342112.73690.00401
90.2453621.96290.027004
100.1823091.45850.0748
110.133021.06420.145627
120.0464660.37170.355662
13-0.023166-0.18530.426777
14-0.07909-0.63270.264585
15-0.085897-0.68720.247228
16-0.112661-0.90130.185408
17-0.165401-1.32320.095238
18-0.207606-1.66080.050818
19-0.249056-1.99240.025295
20-0.292525-2.34020.011202
21-0.336957-2.69570.004483
22-0.322872-2.5830.006046
23-0.305505-2.4440.008645
24-0.304003-2.4320.008911
25-0.302047-2.41640.009269
26-0.259104-2.07280.02111
27-0.273606-2.18880.016132
28-0.280017-2.24010.014281
29-0.262457-2.09970.019854
30-0.232413-1.85930.033791
31-0.19947-1.59580.057734
32-0.193945-1.55160.062849
33-0.179574-1.43660.077852
34-0.154215-1.23370.11091
35-0.131437-1.05150.148493
36-0.106926-0.85540.197758
37-0.072898-0.58320.280909
38-0.055175-0.44140.330205
39-0.035295-0.28240.38929
40-0.010276-0.08220.467369
410.0300860.24070.405284
420.053140.42510.336087
430.0425820.34070.367239
440.0079440.06360.474762
45-0.012778-0.10220.45945
46-0.025162-0.20130.420552
47-0.041777-0.33420.369655
48-0.05155-0.41240.340712
49-0.066625-0.5330.29794
50-0.094283-0.75430.22673
51-0.110399-0.88320.190219
52-0.101048-0.80840.210932
53-0.0884-0.70720.241005
54-0.089667-0.71730.237888
55-0.08353-0.66820.253191
56-0.066859-0.53490.297297
57-0.051466-0.41170.340958
58-0.040881-0.3270.37235
59-0.026436-0.21150.416591
60-0.01471-0.11770.453344


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8882897.10630
20.0534970.4280.335052
30.090750.7260.235242
4-0.02763-0.2210.412883
5-0.117699-0.94160.17497
6-0.015196-0.12160.451811
7-0.101183-0.80950.210624
8-0.11903-0.95220.172279
9-0.100729-0.80580.211661
100.0641940.51360.304666
110.0487950.39040.348784
12-0.175647-1.40520.082402
13-0.004528-0.03620.485609
14-0.037671-0.30140.382056
150.2181741.74540.042858
16-0.058107-0.46490.321806
17-0.191177-1.52940.065545
18-0.060543-0.48430.314897
19-0.088051-0.70440.241867
20-0.020954-0.16760.433701
21-0.157121-1.2570.106667
220.2024481.61960.05512
230.1190880.95270.172162
240.0359920.28790.387163
25-0.020993-0.16790.433577
260.017610.14090.444203
27-0.24275-1.9420.028271
28-0.040471-0.32380.373584
290.0210040.1680.433543
300.0083330.06670.473528
310.0995010.7960.214485
32-0.100347-0.80280.212537
33-0.041242-0.32990.371264
340.0490140.39210.34814
350.0565980.45280.326118
360.113390.90710.183873
37-0.006823-0.05460.478321
38-0.055038-0.44030.330599
39-0.075287-0.60230.274553
40-0.004358-0.03490.486147
41-0.075006-0.60010.275295
42-0.104157-0.83330.2039
430.0406110.32490.373161
44-0.13705-1.09640.138506
450.0369650.29570.3842
46-0.083551-0.66840.253138
470.0336750.26940.394244
480.0029030.02320.490771
49-0.017745-0.1420.443779
500.0112580.09010.464259
510.020330.16260.435656
520.0543270.43460.332651
530.0046290.0370.485289
54-0.069095-0.55280.291178
550.0416410.33310.370062
560.0089970.0720.471423
57-0.049343-0.39470.347172
58-0.015517-0.12410.450799
590.0307610.24610.4032
600.0237060.18970.425092
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/29/t1262118351un1si8euruzqxdk/109v01262118320.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/29/t1262118351un1si8euruzqxdk/109v01262118320.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/29/t1262118351un1si8euruzqxdk/2ewnk1262118320.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/29/t1262118351un1si8euruzqxdk/2ewnk1262118320.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; 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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