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paper ACF ruw

*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: Mon, 27 Dec 2010 12:07:41 +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/27/t1293451650ztqc5qyytdl3gvd.htm/, Retrieved Mon, 27 Dec 2010 13:07:33 +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/27/t1293451650ztqc5qyytdl3gvd.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 «
5,2 7,9 8,7 8,9 15,3 15,4 18,1 19,7 13 12,6 6,2 3,5 3,4 0 9,5 8,9 10,4 13,2 18,9 19 16,3 10,6 5,8 3,6 2,6 5 7,3 9,2 15,7 16,8 18,4 18,1 14,6 7,8 7,6 3,8 5,6 2,2 6,8 11,8 14,9 16,7 16,7 15,9 13,6 9,2 2,8 2,5 4,8 2,8 7,8 9 12,9 16,4 21,8 17,8 13,5 10 10,4 5,5 4 6,8 5,7 9,1 13,6 15 20,9 20,4 14 13,7 7,1 0,8 2,1 1,3 3,9 10,7 11,1 16,4 17,1 17,3 12,9 10,9 5,3 0,7 -0,2 6,5 8,6 8,5 13,3 16,2 17,5 21,2 14,8 10,3 7,3 5,1 4,4 6,2 7,7 9,3 15,6 16,3 16,6 17,4 15,3 9,7 3,7 4,6 5,4 3,1 7,9 10,1 15 15,6 19,7 18,1 17,7 10,7 6,2 4,2 4 5,9 7,1 10,5 15,1 16,8 15,3 18,4 16,1 11,3 7,9 5,6 3,4 4,8 6,5 8,5 15,1 15,7 18,7 19,2 12,9 14,4 6,2 3,3 4,6 7,2 7,8 9,9 13,6 17,1 17,8 18,6 14,7 10,5 8,6 4,4 2,3 2,8 8,8 10,7 13,9 19,3 19,5 20,4 15,3 7,9 8,3 4,5 3,2 5 6,6 11,1 12,8 16,3 17,4 18,9 15,8 11,7 6,4 2,9 4,7 2,4 7,2 10,7 13,4 18,5 18,3 16,8 16,6 14, etc...
 
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
10.79417312.30330
20.4544657.04050
30.0075960.11770.453214
4-0.45077-6.98330
5-0.767012-11.88250
6-0.884261-13.69890
7-0.769578-11.92230
8-0.441433-6.83870
90.0050360.0780.46894
100.4343026.72820
110.75375711.67720
120.86355413.37810
130.74305411.51130
140.4157556.44090
15-0.017171-0.2660.395228
16-0.425378-6.58990
17-0.736902-11.4160
18-0.837057-12.96760
19-0.714266-11.06540
20-0.408209-6.32390
210.0020880.03230.487113
220.4287696.64250
230.70579410.93410
240.8178212.66960
250.7082110.97150
260.3854715.97170
27-0.006617-0.10250.459222
28-0.413996-6.41360
29-0.693841-10.74890
30-0.782663-12.1250
31-0.665554-10.31070
32-0.388391-6.01690
330.0179410.27790.390649
340.4119426.38180
350.6895310.68220
360.78764912.20220
370.67452810.44970
380.3823395.92320
39-0.012091-0.18730.425785
40-0.393172-6.0910
41-0.661552-10.24870
42-0.757721-11.73860
43-0.650333-10.07490
44-0.374083-5.79530
45-0.009145-0.14170.44373
460.3752495.81330
470.64620110.01090
480.72517211.23430
490.632479.79820
500.3653575.66010
51-0.004481-0.06940.472359
52-0.357381-5.53650
53-0.610848-9.46320
54-0.703367-10.89650
55-0.599246-9.28350
56-0.35111-5.43940
57-0.005382-0.08340.466812
580.3395895.26090
590.5983719.26990
600.69808810.81470


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.79417312.30330
2-0.477255-7.39360
3-0.513919-7.96160
4-0.508875-7.88350
5-0.28912-4.4796e-06
6-0.229543-3.55610.000227
7-0.145841-2.25940.012379
80.015210.23560.40696
90.137332.12750.017199
100.0635170.9840.163054
110.10661.65140.049979
120.048510.75150.226539
130.0355710.55110.291051
14-0.093999-1.45620.073318
15-0.066581-1.03150.151681
160.0784491.21530.112716
17-0.068744-1.0650.143978
18-0.011447-0.17730.429695
19-0.009441-0.14630.441923
20-0.026778-0.41480.339316
21-0.084345-1.30670.096287
220.1185681.83680.033734
23-0.087045-1.34850.089385
240.0872211.35120.088949
250.0463590.71820.236667
26-0.094364-1.46190.072541
270.0539730.83610.201954
28-0.06062-0.93910.174308
290.0607720.94150.173703
300.0524950.81320.208443
310.0416630.64540.25963
32-0.13709-2.12380.017355
330.1037951.6080.054577
340.0854071.32310.093529
350.0529090.81970.206609
360.0450740.69830.242838
370.1054161.63310.05188
38-0.009228-0.1430.443219
390.0260940.40420.343197
400.0205420.31820.37529
410.100151.55150.061047
420.0289340.44820.327191
43-0.018648-0.28890.386457
44-0.028119-0.43560.331751
45-0.064399-0.99770.159722
460.0479160.74230.229313
47-0.037811-0.58580.279292
48-0.037312-0.5780.281889
49-0.041258-0.63920.261665
500.076841.19040.117534
51-0.048137-0.74570.228281
520.0216030.33470.369082
530.0502950.77920.218324
540.0521830.80840.209826
550.017480.27080.393391
56-0.052429-0.81220.208734
570.0422590.65470.256654
58-0.041304-0.63990.261431
590.1068181.65480.049635
600.0707541.09610.137064
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/17d3h1293451658.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/17d3h1293451658.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/2i42k1293451658.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/2i42k1293451658.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/3i42k1293451658.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/27/t1293451650ztqc5qyytdl3gvd/3i42k1293451658.ps (open in new window)


 
Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
 
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; 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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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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