Workshop 8, question 1
| Summary of compuational transaction | |
| Raw Input | view raw input (R code) |
| Raw Output | view raw output of R engine |
| Computing time | 1 seconds |
| R Server | 'Gwilym Jenkins' @ 72.249.127.135 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 6.9282 | 0 |
| 1 | 0.186635 | 1.293 | 0.101092 |
| 2 | 0.187462 | 1.2988 | 0.100113 |
| 3 | 0.261172 | 1.8095 | 0.038323 |
| 4 | -0.078519 | -0.544 | 0.705519 |
| 5 | 0.076068 | 0.527 | 0.300304 |
| 6 | 0.030646 | 0.2123 | 0.416378 |
| 7 | -0.092895 | -0.6436 | 0.738549 |
| 8 | 0.054124 | 0.375 | 0.354662 |
| 9 | -0.057899 | -0.4011 | 0.654949 |
| 10 | -0.040794 | -0.2826 | 0.610661 |
| 11 | 0.003561 | 0.0247 | 0.49021 |
| 12 | -0.234953 | -1.6278 | 0.944943 |
| 13 | -0.092873 | -0.6434 | 0.7385 |
| 14 | -0.004766 | -0.033 | 0.513102 |
| 15 | -0.07508 | -0.5202 | 0.697333 |
| 16 | -0.145553 | -1.0084 | 0.840845 |
| 17 | 0.051185 | 0.3546 | 0.362213 |
| 18 | 0.054786 | 0.3796 | 0.35297 |
| 19 | -0.101051 | -0.7001 | 0.756379 |
| 20 | 0.021639 | 0.1499 | 0.440729 |
| 21 | 0.055452 | 0.3842 | 0.35127 |
| 22 | -0.086575 | -0.5998 | 0.724274 |
| 23 | 0.085542 | 0.5926 | 0.278099 |
| 24 | -0.037562 | -0.2602 | 0.602103 |
| 25 | -0.125059 | -0.8664 | 0.804718 |
| 26 | 0.001901 | 0.0132 | 0.494773 |
| 27 | -0.143292 | -0.9928 | 0.837097 |
| 28 | -0.028302 | -0.1961 | 0.577314 |
| 29 | -0.022309 | -0.1546 | 0.561092 |
| 30 | -0.164698 | -1.1411 | 0.870247 |
| 31 | 0.080168 | 0.5554 | 0.290592 |
| 32 | -0.01864 | -0.1291 | 0.551108 |
| 33 | -0.189933 | -1.3159 | 0.90277 |
| 34 | -0.054647 | -0.3786 | 0.646674 |
| 35 | -0.07963 | -0.5517 | 0.70814 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.186635 | 1.293 | 0.101092 |
| 1 | 0.158137 | 1.0956 | 0.139359 |
| 2 | 0.214874 | 1.4887 | 0.071555 |
| 3 | -0.193965 | -1.3438 | 0.907339 |
| 4 | 0.048237 | 0.3342 | 0.369843 |
| 5 | -0.004045 | -0.028 | 0.511119 |
| 6 | -0.053573 | -0.3712 | 0.643925 |
| 7 | 0.03336 | 0.2311 | 0.4091 |
| 8 | -0.045233 | -0.3134 | 0.622327 |
| 9 | 0.00046 | 0.0032 | 0.498736 |
| 10 | -0.021705 | -0.1504 | 0.559451 |
| 11 | -0.212296 | -1.4708 | 0.926069 |
| 12 | -0.030578 | -0.2119 | 0.58344 |
| 13 | 0.090153 | 0.6246 | 0.267597 |
| 14 | 0.04964 | 0.3439 | 0.366207 |
| 15 | -0.231533 | -1.6041 | 0.942375 |
| 16 | 0.126941 | 0.8795 | 0.191763 |
| 17 | 0.147342 | 1.0208 | 0.15623 |
| 18 | -0.167801 | -1.1626 | 0.874622 |
| 19 | -0.069028 | -0.4782 | 0.682674 |
| 20 | 0.15784 | 1.0935 | 0.139806 |
| 21 | -0.052172 | -0.3615 | 0.640329 |
| 22 | -0.006471 | -0.0448 | 0.517787 |
| 23 | -0.108733 | -0.7533 | 0.772534 |
| 24 | -0.102315 | -0.7089 | 0.759081 |
| 25 | 0.038306 | 0.2654 | 0.395921 |
| 26 | -0.057303 | -0.397 | 0.653438 |
| 27 | -0.102829 | -0.7124 | 0.760173 |
| 28 | 0.029307 | 0.203 | 0.419978 |
| 29 | 0.037367 | 0.2589 | 0.398414 |
| 30 | 0.002369 | 0.0164 | 0.493487 |
| 31 | -0.124145 | -0.8601 | 0.802996 |
| 32 | -0.073387 | -0.5084 | 0.693263 |
| 33 | -0.071828 | -0.4976 | 0.689494 |
| 34 | 0.00969 | 0.0671 | 0.473378 |
| 35 | 0.089975 | 0.6234 | 0.267997 |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/30/t119642256870m9iz05o3vbpj0/2cpri1196423209.ps (open in new window) |
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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