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workshop

*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: Sun, 14 Dec 2008 08:28:30 -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/14/t12292685773ku0sneo41zf4h1.htm/, Retrieved Sun, 14 Dec 2008 16:29:37 +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/14/t12292685773ku0sneo41zf4h1.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 «
2074 2049 2406 2558 2251 2059 2397 1747 1707 2319 1631 1627 1791 2034 1997 2169 2028 2253 2218 1855 2187 1852 1570 1851 1954 1828 2251 2277 2085 2282 2266 1878 2267 2069 1746 2299 2360 2214 2825 2355 2333 3016 2155 2172 2150 2533 2058 2160 2259 2498 2695 2799 2945 2930 2318 2540 2570 2669 2450 2842
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5113563.96091e-04
20.4317443.34430.000713
30.522934.05067.4e-05
40.2672042.06970.021395
50.1554251.20390.116675
60.2772432.14750.017901
70.1416391.09710.138484
80.1636161.26740.104961
90.2607352.01960.023947
100.1814151.40520.082555
110.3049282.3620.01072
120.3682682.85260.00297
130.1389711.07650.143015
140.2319741.79690.038696
150.1846811.43050.078875
16-0.047764-0.370.356352
17-0.003233-0.0250.490053
180.0405450.31410.377281
19-0.14978-1.16020.125283
20-0.026645-0.20640.418592
210.0677640.52490.300793
22-0.094794-0.73430.232822
230.037810.29290.385316
24-0.002266-0.01760.493026
25-0.15364-1.19010.119349
26-0.110437-0.85540.197854
27-0.169472-1.31270.097137
28-0.306917-2.37740.010321
29-0.225881-1.74970.042644
30-0.278299-2.15570.017564
31-0.315979-2.44760.008663
32-0.115802-0.8970.186653
33-0.186332-1.44330.077065
34-0.215187-1.66680.05038
35-0.090825-0.70350.242224
36-0.112714-0.87310.19305
37-0.186915-1.44780.076434
38-0.14774-1.14440.128504
39-0.129963-1.00670.159063
40-0.234474-1.81620.037166
41-0.217338-1.68350.048738
42-0.184858-1.43190.07868
43-0.188697-1.46160.074529
44-0.174077-1.34840.0913
45-0.211089-1.63510.053633
46-0.125675-0.97350.167112
47-0.089532-0.69350.245333
48-0.094727-0.73380.232978
49-0.068198-0.52830.299634
50-0.011442-0.08860.464837
51-0.066833-0.51770.30329
52-0.063549-0.49230.312169
530.017370.13450.446711
540.0054850.04250.483125
550.008160.06320.474907
560.0159190.12330.451137
570.0002410.00190.499257
58-0.02074-0.16060.436454
59-0.013609-0.10540.458199
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5113563.96091e-04
20.2305431.78580.039594
30.3363032.6050.005784
4-0.181212-1.40370.082787
5-0.138706-1.07440.14347
60.1519151.17670.121976
70.0037220.02880.488546
80.138431.07230.143946
90.0748920.58010.282005
10-0.008613-0.06670.473515
110.2277911.76450.041372
120.0979870.7590.225411
13-0.250147-1.93760.028689
140.0144250.11170.455703
15-0.095684-0.74120.230742
16-0.108525-0.84060.201947
17-0.043598-0.33770.368382
180.0198960.15410.439018
19-0.079655-0.6170.269783
200.0535520.41480.339879
210.0834870.64670.26015
22-0.149842-1.16070.125187
230.0089810.06960.472385
24-0.154544-1.19710.117989
25-0.081626-0.63230.264805
26-0.090375-0.70.243304
27-0.033992-0.26330.39661
28-0.03132-0.24260.404571
29-0.026616-0.20620.41868
30-0.055019-0.42620.335754
310.0484030.37490.354519
320.1142710.88510.189808
33-0.093327-0.72290.236273
34-0.024488-0.18970.4251
35-0.108401-0.83970.202214
360.1827721.41570.08101
370.0540990.4190.338339
38-0.106273-0.82320.206831
390.1381911.07040.144358
40-0.02788-0.2160.414877
41-0.086619-0.67090.252415
420.0594630.46060.323376
43-0.06402-0.49590.31089
44-0.138005-1.0690.144681
45-0.063472-0.49170.312379
460.0530610.4110.341266
470.0714080.55310.291116
480.0905260.70120.24294
490.0048610.03770.485044
50-0.049352-0.38230.351802
51-0.014436-0.11180.455668
520.0230740.17870.429375
530.0287670.22280.412213
54-0.005582-0.04320.482827
550.0032860.02550.48989
560.0087990.06820.472945
57-0.082452-0.63870.262734
58-0.047386-0.3670.357437
59-0.020365-0.15770.437592
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292685773ku0sneo41zf4h1/1byor1229268505.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292685773ku0sneo41zf4h1/1byor1229268505.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292685773ku0sneo41zf4h1/2ju1w1229268505.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292685773ku0sneo41zf4h1/2ju1w1229268505.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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