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Workshop 8

*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, 24 Nov 2009 04:49:44 -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/Nov/24/t12590635045wbg0zpliqnv1v6.htm/, Retrieved Tue, 24 Nov 2009 12:51:47 +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/Nov/24/t12590635045wbg0zpliqnv1v6.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:
JSSHWWS8P2
 
Dataseries X:
» Textbox « » Textfile « » CSV «
11.1 10.9 10 9.2 9.2 9.5 9.6 9.5 9.1 8.9 9 10.1 10.3 10.2 9.6 9.2 9.3 9.4 9.4 9.2 9 9 9 9.8 10 9.8 9.3 9 9 9.1 9.1 9.1 9.2 8.8 8.3 8.4 8.1 7.7 7.9 7.9 8 7.9 7.6 7.1 6.8 6.5 6.9 8.2 8.7 8.3 7.9 7.5 7.8 8.3 8.4 8.2 7.7 7.2 7.3 8.1
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8634646.68840
20.655845.08012e-06
30.5225824.04797.5e-05
40.5098073.94890.000104
50.5580914.3232.9e-05
60.578434.48051.7e-05
70.5262124.0766.8e-05
80.4313413.34120.00072
90.3712172.87540.002788
100.3776952.92560.002424
110.4267533.30560.000801
120.4224943.27260.000885
130.3415582.64570.005197
140.2378941.84270.035156
150.1721471.33340.093713
160.1392161.07840.142595
170.1120030.86760.194543
180.070990.54990.292218
190.0129070.10.460349
20-0.040674-0.31510.376906
21-0.06345-0.49150.312439
22-0.054525-0.42240.337139
23-0.03032-0.23490.407558
24-0.056601-0.43840.331325
25-0.132525-1.02650.154381
26-0.206126-1.59660.057799
27-0.232429-1.80040.038413
28-0.228652-1.77110.040809
29-0.219354-1.69910.047239
30-0.231683-1.79460.038877
31-0.271983-2.10680.019664
32-0.328292-2.54290.006795
33-0.363846-2.81830.003264
34-0.342512-2.65310.005096
35-0.287611-2.22780.014827
36-0.265717-2.05820.021959
37-0.28386-2.19880.015881
38-0.308818-2.39210.009951
39-0.319389-2.4740.008104
40-0.301988-2.33920.011337
41-0.280975-2.17640.016735
42-0.285149-2.20880.015511
43-0.320398-2.48180.007945
44-0.349814-2.70970.004384
45-0.329006-2.54850.006699
46-0.237261-1.83780.035521
47-0.134779-1.0440.150338
48-0.101962-0.78980.216379
49-0.127412-0.98690.163821
50-0.157693-1.22150.11334
51-0.158674-1.22910.111919
52-0.122506-0.94890.173232
53-0.089723-0.6950.244872
54-0.087184-0.67530.251033
55-0.108887-0.84340.201168
56-0.133839-1.03670.152015
57-0.128135-0.99250.162462
58-0.081185-0.62890.265914
59-0.025703-0.19910.421432
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8634646.68840
2-0.352674-2.73180.00413
30.2742192.12410.018897
40.2595462.01040.024443
50.1111020.86060.196444
6-0.002533-0.01960.492204
7-0.063537-0.49220.312203
8-0.030852-0.2390.405968
90.0908230.70350.242229
100.0661310.51230.305178
110.077430.59980.275459
12-0.176837-1.36980.087931
13-0.076346-0.59140.278245
14-0.014916-0.11550.454202
15-0.041256-0.31960.375203
16-0.165179-1.27950.102829
17-0.097089-0.7520.227481
18-0.038472-0.2980.383366
19-0.033768-0.26160.397275
20-0.029465-0.22820.410121
210.0155120.12020.452382
220.0058270.04510.482075
230.0995810.77130.221764
24-0.148721-1.1520.126948
25-0.051781-0.40110.344888
26-0.016064-0.12440.450696
270.0374720.29030.38631
28-0.0526-0.40740.342568
290.0221620.17170.432138
30-0.028046-0.21720.414378
31-0.019272-0.14930.440916
32-0.115382-0.89370.187514
33-0.022043-0.17070.4325
340.0417570.32340.37374
350.0594110.46020.323518
36-0.080351-0.62240.26802
370.0680920.52740.299917
380.0059060.04570.481833
39-0.007072-0.05480.478249
400.026390.20440.419361
41-0.059718-0.46260.322671
42-0.106602-0.82570.206113
43-0.045376-0.35150.36323
440.0151560.11740.453467
450.0954010.7390.231403
460.1323531.02520.154693
470.0746860.57850.282541
48-0.070468-0.54580.293598
490.0431790.33450.369598
50-0.046031-0.35660.361338
51-0.078617-0.6090.272422
52-0.02648-0.20510.419089
53-0.076376-0.59160.278168
540.0050040.03880.484604
550.0364110.2820.389441
56-0.068615-0.53150.298522
57-0.035546-0.27530.392001
58-0.063152-0.48920.313251
590.0202650.1570.437897
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/24/t12590635045wbg0zpliqnv1v6/14aor1259063378.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t12590635045wbg0zpliqnv1v6/14aor1259063378.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/24/t12590635045wbg0zpliqnv1v6/29m4d1259063378.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/24/t12590635045wbg0zpliqnv1v6/29m4d1259063378.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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