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*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: Sat, 25 Dec 2010 12:49:36 +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/25/t1293281399756uh1o8hllhs7g.htm/, Retrieved Sat, 25 Dec 2010 13:49:59 +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/25/t1293281399756uh1o8hllhs7g.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 «
130 127 122 117 112 113 149 157 157 147 137 132 125 123 117 114 111 112 144 150 149 134 123 116 117 111 105 102 95 93 124 130 124 115 106 105 105 101 95 93 84 87 116 120 117 109 105 107 109 109 108 107 99 103 131 137 135 124 118 121 121
 
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'RServer@AstonUniversity' @ vre.aston.ac.uk


Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7967866.22310
20.4783973.73640.000207
30.2287071.78630.039514
40.1127670.88070.190958
50.1060040.82790.205471
60.1135490.88680.189323
70.0752880.5880.279345
80.0468470.36590.357857
90.0978190.7640.22391
100.2459241.92070.029722
110.4520373.53050.000398
120.5603794.37672.4e-05
130.3709632.89730.00261
140.1024260.80.213416
15-0.102724-0.80230.212746
16-0.194546-1.51940.066908
17-0.198327-1.5490.063279
18-0.19889-1.55340.062753
19-0.247575-1.93360.028902
20-0.281506-2.19860.015854
21-0.251075-1.9610.027227
22-0.134696-1.0520.148472
230.0347920.27170.393373
240.1312031.02470.154769
250.004610.0360.485697
26-0.16718-1.30570.098275
27-0.286362-2.23660.014491
28-0.32393-2.530.007003
29-0.301576-2.35540.010868
30-0.284974-2.22570.014869
31-0.302176-2.36010.010743
32-0.308061-2.4060.009586
33-0.262924-2.05350.022159
34-0.158545-1.23830.110179
35-0.020039-0.15650.438074
360.0598970.46780.320792
37-0.005962-0.04660.481506
38-0.099128-0.77420.220897
39-0.158644-1.23910.110037
40-0.160367-1.25250.107582
41-0.12309-0.96140.170082
42-0.094045-0.73450.232725
43-0.088135-0.68840.246919
44-0.079018-0.61720.269715
45-0.049512-0.38670.350163
460.0068110.05320.478874
470.0782360.6110.27172
480.1175560.91810.18108
490.0804740.62850.266004
500.0253270.19780.421927
51-0.012202-0.09530.462196
52-0.014601-0.1140.454791
530.0090430.07060.471962
540.0267570.2090.417579
550.021490.16780.433631
560.0136290.10640.457788
570.0045060.03520.48602
580.0020650.01610.493593
590.0035110.02740.489105
600.002010.01570.493764


Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7967866.22310
2-0.42853-3.34690.000702
30.0859720.67150.252231
40.0924040.72170.236618
50.0710580.5550.290469
6-0.066897-0.52250.301614
7-0.071257-0.55650.28994
80.1258160.98270.164829
90.1913951.49480.070055
100.2280741.78130.039919
110.2731642.13350.018458
12-0.029211-0.22810.410148
13-0.601835-4.70058e-06
140.1859921.45260.075723
15-0.072258-0.56430.287293
16-0.146578-1.14480.128379
17-0.107361-0.83850.202507
18-0.054739-0.42750.335251
19-0.109933-0.85860.196961
20-0.036817-0.28760.387332
21-0.070317-0.54920.292438
220.0055680.04350.482726
23-0.044616-0.34850.364347
240.035770.27940.390453
25-0.045961-0.3590.360429
260.0991740.77460.220792
27-0.021314-0.16650.434171
28-0.032861-0.25670.399155
29-0.005146-0.04020.484035
300.0376690.29420.384801
310.0514330.40170.344654
32-0.064093-0.50060.309234
330.034660.27070.393765
34-0.060669-0.47380.318653
35-0.054534-0.42590.33583
36-0.008421-0.06580.473887
370.1101190.86010.196563
38-0.115631-0.90310.18501
39-0.022944-0.17920.429189
400.0515120.40230.344427
410.0190520.14880.441099
42-0.013951-0.1090.456794
430.0551660.43090.334045
44-0.024036-0.18770.425856
45-0.070332-0.54930.292399
46-0.045703-0.3570.36118
47-0.022154-0.1730.431601
480.0144270.11270.455328
490.0141490.11050.456185
50-0.105581-0.82460.206401
51-0.005323-0.04160.483486
520.0153590.120.452454
53-0.009895-0.07730.469327
54-0.033584-0.26230.396988
55-0.088674-0.69260.245605
560.0422450.32990.371287
57-0.107604-0.84040.201979
58-0.037412-0.29220.385563
59-0.052623-0.4110.341257
60-0.003317-0.02590.489708
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/16eph1293281372.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/16eph1293281372.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/2yn621293281372.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/2yn621293281372.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/3yn621293281372.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293281399756uh1o8hllhs7g/3yn621293281372.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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