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Paper10

*Unverified author*
R Software Module: rwasp_autocorrelation.wasp (opens new window with default values)
Title produced by software: (Partial) Autocorrelation Function
Date of computation: Fri, 19 Dec 2008 06:21:38 -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/19/t1229692935xvmsrk1ktasn3ft.htm/, Retrieved Fri, 19 Dec 2008 14:22:15 +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/19/t1229692935xvmsrk1ktasn3ft.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 «
4.256 5.008 4.181 4.666 4.476 4.912 4.340 3.830 4.285 5.537 3.813 4.610 4.207 5.099 4.112 4.199 5.110 4.218 4.736 4.624 4.145 5.299 5.011 4.730 4.619 5.578 5.369 4.902 6.102 5.024 5.731 5.732 4.491 4.755 5.208 4.962 4.163 5.592 5.754 4.929 5.219 4.429 4.143 4.308 3.996 4.634 4.138 3.759 3.922 5.560 4.004 3.937 5.250 3.908 4.814 4.407 3.243 3.740 3.949 3.711
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2211791.71320.045915
20.2394431.85470.034276
30.4291953.32450.000757
40.1830621.4180.080683
50.1600961.24010.109883
60.1545421.19710.117993
70.1088420.84310.201265
80.1147560.88890.188805
90.1987291.53930.064489
100.1143740.88590.189594
11-0.019831-0.15360.439218
120.2498241.93510.028846
13-0.067298-0.52130.302042
14-0.050133-0.38830.349573
150.0227530.17620.430348
16-0.190971-1.47930.072151
17-0.119095-0.92250.179979
18-0.234057-1.8130.037418
19-0.244168-1.89130.031706
20-0.274058-2.12280.018951
21-0.146031-1.13110.131247
22-0.176649-1.36830.088158
23-0.227507-1.76230.04156
24-0.044477-0.34450.36583
25-0.211093-1.63510.05363
26-0.178338-1.38140.08614
27-0.137862-1.06790.144927
28-0.233217-1.80650.037929
29-0.125933-0.97550.166622
30-0.15098-1.16950.123416
31-0.180013-1.39440.084173
32-0.109252-0.84630.200384
33-0.017961-0.13910.44491
34-0.062874-0.4870.314008
35-0.11362-0.88010.19116
360.1094640.84790.19993
37-0.03085-0.2390.405973
38-0.03582-0.27750.391189
390.0417640.32350.373719
400.0604230.4680.320728
410.0485080.37570.354218
42-0.01554-0.12040.452295
430.0468110.36260.359091
440.0580630.44980.327255
450.028070.21740.414305
460.0504120.39050.348778
47-0.006122-0.04740.481166
480.037990.29430.384784
490.0628170.48660.314165
500.0021260.01650.493456
510.0652740.50560.307491
520.0111240.08620.46581
530.0239220.18530.426811
540.0107690.08340.4669
550.0018520.01430.4943
560.0179980.13940.444795
570.0197890.15330.439344
58-0.004381-0.03390.48652
590.0141590.10970.456516
60NANANA


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2211791.71320.045915
20.2003231.55170.062997
30.3752132.90640.002558
40.0310370.24040.405417
5-0.010275-0.07960.468414
6-0.063847-0.49460.31136
7-0.002103-0.01630.493529
80.0389370.30160.381999
90.1688171.30770.09799
100.0386010.2990.382987
11-0.172431-1.33560.093354
120.1456661.12830.131837
13-0.215784-1.67150.04992
14-0.036382-0.28180.389527
15-0.089316-0.69180.245853
16-0.13895-1.07630.14305
17-0.05997-0.46450.321977
18-0.22862-1.77090.04083
19-0.094692-0.73350.23306
20-0.177402-1.37420.087253
210.1152450.89270.187797
220.0271960.21070.416934
230.0739920.57310.284347
240.0314820.24390.404086
25-0.06961-0.53920.295875
26-0.006102-0.04730.481228
27-0.068345-0.52940.29924
280.0781750.60550.273551
290.0252060.19520.422931
300.0853360.6610.255569
31-0.1243-0.96280.16975
32-0.009653-0.07480.470321
330.0108020.08370.466798
34-0.015344-0.11890.452893
35-0.051604-0.39970.34539
360.0184040.14260.443558
37-0.026098-0.20220.420241
38-0.15549-1.20440.116578
39-0.057444-0.4450.328974
400.1092590.84630.200369
410.0757140.58650.279877
42-0.072704-0.56320.287711
43-0.039181-0.30350.381281
44-0.047206-0.36570.357954
45-0.118165-0.91530.181848
46-0.016564-0.12830.449168
47-0.02002-0.15510.438641
48-0.063078-0.48860.313452
490.0363710.28170.389559
50-0.058488-0.4530.326074
510.0691920.5360.296983
52-0.069609-0.53920.295876
530.0062770.04860.480691
540.0128560.09960.460503
55-0.019743-0.15290.439483
560.0528860.40970.34176
57-0.008797-0.06810.472948
58-0.002-0.01550.493844
590.0296640.22980.409525
60NANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229692935xvmsrk1ktasn3ft/1jjnl1229692886.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229692935xvmsrk1ktasn3ft/1jjnl1229692886.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229692935xvmsrk1ktasn3ft/2exw31229692886.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/19/t1229692935xvmsrk1ktasn3ft/2exw31229692886.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1.0 ; 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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