Inducing stationarity in time series
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 2 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 8.4261 | 0 |
| 1 | -0.108903 | -0.9176 | 0.81904 |
| 2 | -0.095202 | -0.8022 | 0.787438 |
| 3 | 0.005652 | 0.0476 | 0.481075 |
| 4 | -0.215358 | -1.8146 | 0.963098 |
| 5 | -0.005875 | -0.0495 | 0.51967 |
| 6 | 0.200053 | 1.6857 | 0.048124 |
| 7 | -0.00425 | -0.0358 | 0.514234 |
| 8 | 0.116585 | 0.9824 | 0.164629 |
| 9 | 0.017825 | 0.1502 | 0.440517 |
| 10 | -0.017412 | -0.1467 | 0.558114 |
| 11 | 0.04402 | 0.3709 | 0.3559 |
| 12 | -0.302342 | -2.5476 | 0.993493 |
| 13 | -0.02553 | -0.2151 | 0.584854 |
| 14 | 0.144313 | 1.216 | 0.114005 |
| 15 | 0.009461 | 0.0797 | 0.468341 |
| 16 | 0.126176 | 1.0632 | 0.145652 |
| 17 | -0.073929 | -0.6229 | 0.732339 |
| 18 | -0.108673 | -0.9157 | 0.818536 |
| 19 | -0.018354 | -0.1547 | 0.561232 |
| 20 | -0.009329 | -0.0786 | 0.531217 |
| 21 | 0.040355 | 0.34 | 0.367418 |
| 22 | -0.040938 | -0.345 | 0.634425 |
| 23 | 0.06243 | 0.526 | 0.300249 |
| 24 | -0.052167 | -0.4396 | 0.669207 |
| 25 | -0.088219 | -0.7433 | 0.770137 |
| 26 | -0.071377 | -0.6014 | 0.725267 |
| 27 | -0.02319 | -0.1954 | 0.577181 |
| 28 | -0.025679 | -0.2164 | 0.585342 |
| 29 | 0.060779 | 0.5121 | 0.305075 |
| 30 | 0.054984 | 0.4633 | 0.322282 |
| 31 | -0.01192 | -0.1004 | 0.539862 |
| 32 | -0.111236 | -0.9373 | 0.824106 |
| 33 | -0.055889 | -0.4709 | 0.680433 |
| 34 | 0.091216 | 0.7686 | 0.222341 |
| 35 | -0.107323 | -0.9043 | 0.815557 |
| 36 | 0.161375 | 1.3598 | 0.089102 |
| 37 | 0.008438 | 0.0711 | 0.471759 |
| 38 | -0.091927 | -0.7746 | 0.779423 |
| 39 | 0.000123 | 0.001 | 0.499588 |
| 40 | -0.030791 | -0.2594 | 0.601979 |
| 41 | -0.021508 | -0.1812 | 0.571647 |
| 42 | 0.061676 | 0.5197 | 0.302448 |
| 43 | -0.052623 | -0.4434 | 0.670592 |
| 44 | 0.056666 | 0.4775 | 0.317245 |
| 45 | 0.008646 | 0.0729 | 0.471064 |
| 46 | -0.10353 | -0.8724 | 0.807024 |
| 47 | 0.072297 | 0.6092 | 0.272174 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | -0.108903 | -0.9176 | 0.81904 |
| 1 | -0.108347 | -0.9129 | 0.817819 |
| 2 | -0.018062 | -0.1522 | 0.560267 |
| 3 | -0.232687 | -1.9607 | 0.973079 |
| 4 | -0.067364 | -0.5676 | 0.713959 |
| 5 | 0.151453 | 1.2762 | 0.103029 |
| 6 | 0.02762 | 0.2327 | 0.408319 |
| 7 | 0.119208 | 1.0045 | 0.159284 |
| 8 | 0.053964 | 0.4547 | 0.325354 |
| 9 | 0.103565 | 0.8727 | 0.192897 |
| 10 | 0.095998 | 0.8089 | 0.21064 |
| 11 | -0.297689 | -2.5084 | 0.992792 |
| 12 | -0.104015 | -0.8764 | 0.808128 |
| 13 | 0.048095 | 0.4053 | 0.343254 |
| 14 | 0.013685 | 0.1153 | 0.454261 |
| 15 | 0.012653 | 0.1066 | 0.457697 |
| 16 | -0.129712 | -1.093 | 0.860951 |
| 17 | 0.044198 | 0.3724 | 0.355346 |
| 18 | 0.011341 | 0.0956 | 0.46207 |
| 19 | 0.016417 | 0.1383 | 0.445186 |
| 20 | 0.026447 | 0.2228 | 0.412149 |
| 21 | -0.099792 | -0.8409 | 0.798377 |
| 22 | 0.133809 | 1.1275 | 0.131665 |
| 23 | -0.160391 | -1.3515 | 0.909583 |
| 24 | -0.162519 | -1.3694 | 0.912407 |
| 25 | -0.102492 | -0.8636 | 0.804646 |
| 26 | -0.045005 | -0.3792 | 0.647171 |
| 27 | 0.019656 | 0.1656 | 0.434462 |
| 28 | -0.110498 | -0.9311 | 0.822514 |
| 29 | 0.047432 | 0.3997 | 0.345301 |
| 30 | 0.079612 | 0.6708 | 0.252254 |
| 31 | -0.069752 | -0.5877 | 0.720714 |
| 32 | 0.001295 | 0.0109 | 0.495661 |
| 33 | 0.060404 | 0.509 | 0.306174 |
| 34 | -0.032431 | -0.2733 | 0.60728 |
| 35 | 0.120314 | 1.0138 | 0.157064 |
| 36 | -0.144927 | -1.2212 | 0.88697 |
| 37 | -0.059234 | -0.4991 | 0.690381 |
| 38 | -0.084308 | -0.7104 | 0.760105 |
| 39 | -0.025107 | -0.2116 | 0.583471 |
| 40 | 0.021748 | 0.1833 | 0.427561 |
| 41 | -0.051454 | -0.4336 | 0.667039 |
| 42 | -0.000474 | -0.004 | 0.501587 |
| 43 | -0.003305 | -0.0279 | 0.511071 |
| 44 | -0.010604 | -0.0893 | 0.535472 |
| 45 | -0.034163 | -0.2879 | 0.612853 |
| 46 | -0.01052 | -0.0886 | 0.535192 |
| 47 | -0.038511 | -0.3245 | 0.626743 |
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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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
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Software written by Ed van Stee & Patrick Wessa
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