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paper - time-series (3)

*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: Fri, 10 Dec 2010 14:05:08 +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/10/t1291989824xswegafmr0elzm4.htm/, Retrieved Fri, 10 Dec 2010 15:03:46 +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/10/t1291989824xswegafmr0elzm4.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 «
296.95 296.84 287.54 287.81 283.99 275.79 269.52 278.35 283.43 289.46 282.30 293.55 304.78 300.99 315.29 316.21 331.79 329.38 317.27 317.98 340.28 339.21 336.71 340.11 347.72 328.68 303.05 299.83 320.04 317.94 303.31 308.85 319.19 314.52 312.39 315.77 320.23 309.45 296.54 297.28 301.39 306.68 305.91 314.76 323.34 341.58 330.12 318.16 317.84 325.39 327.56 329.77 333.29 346.10 358.00 344.82 313.30 301.26 306.38 319.31
 
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
10.3441862.55260.00675
2-0.025788-0.19120.424517
3-0.246124-1.82530.036694
4-0.461798-3.42480.000585
5-0.196303-1.45580.075564
6-0.100803-0.74760.22895
70.0150890.11190.455653
80.2376591.76250.041768
90.1922091.42550.079837
100.0352570.26150.397353
110.0283720.21040.417063
12-0.078602-0.58290.281161
13-0.043459-0.32230.374223
140.035810.26560.39578
15-0.136931-1.01550.157156
16-0.176567-1.30950.097911
17-0.084038-0.62320.26785
18-0.106351-0.78870.216831
19-0.010458-0.07760.469229
200.1756951.3030.099004
210.1347840.99960.160944
220.1535641.13890.129848
230.0631630.46840.320665
24-0.051821-0.38430.351112
25-0.040495-0.30030.382534
26-0.207563-1.53930.064729
27-0.234391-1.73830.043878
28-0.07167-0.53150.2986
290.0696390.51650.303804
300.1779391.31960.096213
310.2754332.04270.022945
320.080090.5940.277487
33-0.055416-0.4110.341342
34-0.031932-0.23680.406839
35-0.113672-0.8430.201436
36-0.014541-0.10780.457257
370.0578120.42870.334891
380.0627160.46510.321843
390.0466590.3460.365318
40-0.022842-0.16940.433051
41-0.089949-0.66710.253756
420.011520.08540.466113
430.0289060.21440.415525
44-0.007857-0.05830.476874
450.0628370.4660.321524
46-0.057693-0.42790.33521
47-0.044824-0.33240.370417
48-0.083045-0.61590.270257
49-0.086051-0.63820.263005
500.0123280.09140.463742
510.0420250.31170.378238
520.0450830.33430.369695
530.0153360.11370.454931
54-0.023125-0.17150.432231
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3441862.55260.00675
2-0.163637-1.21360.11505
3-0.209194-1.55140.063268
4-0.367762-2.72740.004275
50.0494630.36680.357576
6-0.188008-1.39430.084417
7-0.083698-0.62070.268673
80.0767730.56940.285714
90.023830.17670.430186
10-0.149816-1.11110.135686
110.0987230.73220.233592
120.0101230.07510.470214
130.0501010.37160.355823
140.0510230.37840.353296
15-0.13785-1.02230.155553
16-0.186083-1.380.086581
17-0.003812-0.02830.488776
18-0.157722-1.16970.123583
19-0.185853-1.37830.086843
200.0953180.70690.241307
21-0.062318-0.46220.322894
22-0.076913-0.57040.285364
230.0402390.29840.383253
240.1395021.03460.152698
25-0.015661-0.11610.45398
26-0.147222-1.09180.139835
27-0.090191-0.66890.253186
28-0.05253-0.38960.349178
290.0120540.08940.464546
30-0.050149-0.37190.355694
310.0658980.48870.313495
32-0.121617-0.90190.185511
33-0.100662-0.74650.229264
340.0624430.46310.322565
350.0782520.58030.282031
360.0832060.61710.269868
370.1016080.75350.227169
380.1074760.79710.21442
39-0.031077-0.23050.40929
400.0883740.65540.257471
410.0277410.20570.418878
420.0212770.15780.437598
43-0.047489-0.35220.363023
44-0.095435-0.70780.24104
45-0.080399-0.59630.276725
46-0.046165-0.34240.366688
470.1072470.79540.214909
48-0.138914-1.03020.153709
490.019140.14190.443822
500.0736860.54650.293477
51-0.000477-0.00350.498596
520.0028920.02140.491484
530.093960.69680.244423
54-0.049992-0.37080.356123
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/10/t1291989824xswegafmr0elzm4/1sueu1291989906.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/10/t1291989824xswegafmr0elzm4/1sueu1291989906.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/10/t1291989824xswegafmr0elzm4/2sueu1291989906.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/10/t1291989824xswegafmr0elzm4/2sueu1291989906.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 4 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 4 ; 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 (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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