Workshop 4 Q2 Autocorrelation function 2
| 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 | 7.8102 | 0 |
| 1 | 0.559893 | 4.3729 | 2.4e-05 |
| 2 | 0.474245 | 3.704 | 0.000229 |
| 3 | 0.564688 | 4.4104 | 2.1e-05 |
| 4 | 0.525114 | 4.1013 | 6.2e-05 |
| 5 | 0.45451 | 3.5498 | 0.000375 |
| 6 | 0.587149 | 4.5858 | 1.1e-05 |
| 7 | 0.368589 | 2.8788 | 0.002749 |
| 8 | 0.442734 | 3.4579 | 0.000499 |
| 9 | 0.35207 | 2.7498 | 0.003918 |
| 10 | 0.191212 | 1.4934 | 0.070242 |
| 11 | 0.306525 | 2.394 | 0.009877 |
| 12 | 0.510076 | 3.9838 | 9.2e-05 |
| 13 | 0.188566 | 1.4728 | 0.07298 |
| 14 | 0.158398 | 1.2371 | 0.110391 |
| 15 | 0.179498 | 1.4019 | 0.083003 |
| 16 | 0.129079 | 1.0081 | 0.158684 |
| 17 | 0.103556 | 0.8088 | 0.210886 |
| 18 | 0.19112 | 1.4927 | 0.070335 |
| 19 | 0.023487 | 0.1834 | 0.427531 |
| 20 | 0.079051 | 0.6174 | 0.269631 |
| 21 | -0.006155 | -0.0481 | 0.519091 |
| 22 | -0.145772 | -1.1385 | 0.870321 |
| 23 | -0.022859 | -0.1785 | 0.570553 |
| 24 | 0.089615 | 0.6999 | 0.243321 |
| 25 | -0.129389 | -1.0106 | 0.84189 |
| 26 | -0.124106 | -0.9693 | 0.831888 |
| 27 | -0.117826 | -0.9203 | 0.819467 |
| 28 | -0.158617 | -1.2388 | 0.889925 |
| 29 | -0.148552 | -1.1602 | 0.874761 |
| 30 | -0.133441 | -1.0422 | 0.849286 |
| 31 | -0.210425 | -1.6435 | 0.947285 |
| 32 | -0.132163 | -1.0322 | 0.846979 |
| 33 | -0.236687 | -1.8486 | 0.965317 |
| 34 | -0.308532 | -2.4097 | 0.990501 |
| 35 | -0.225493 | -1.7612 | 0.958389 |
| 36 | -0.170675 | -1.333 | 0.906258 |
| 37 | -0.287837 | -2.2481 | 0.985902 |
| 38 | -0.288443 | -2.2528 | 0.98606 |
| 39 | -0.274535 | -2.1442 | 0.981994 |
| 40 | -0.277406 | -2.1666 | 0.98291 |
| 41 | -0.280015 | -2.187 | 0.983706 |
| 42 | -0.272736 | -2.1301 | 0.981399 |
| 43 | -0.286772 | -2.2398 | 0.985619 |
| 44 | -0.239756 | -1.8726 | 0.967038 |
| 45 | -0.277657 | -2.1686 | 0.982988 |
| 46 | -0.298 | -2.3275 | 0.988362 |
| 47 | -0.242246 | -1.892 | 0.96838 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.559893 | 4.3729 | 2.4e-05 |
| 1 | 0.234174 | 1.829 | 0.036148 |
| 2 | 0.354813 | 2.7712 | 0.003697 |
| 3 | 0.162808 | 1.2716 | 0.104176 |
| 4 | 0.057594 | 0.4498 | 0.327216 |
| 5 | 0.300865 | 2.3498 | 0.011017 |
| 6 | -0.252115 | -1.9691 | 0.973254 |
| 7 | 0.201509 | 1.5738 | 0.060349 |
| 8 | -0.293922 | -2.2956 | 0.987425 |
| 9 | -0.25271 | -1.9737 | 0.973527 |
| 10 | 0.197025 | 1.5388 | 0.064511 |
| 11 | 0.308823 | 2.412 | 0.009445 |
| 12 | -0.178959 | -1.3977 | 0.916369 |
| 13 | -0.198128 | -1.5474 | 0.936534 |
| 14 | -0.071463 | -0.5581 | 0.710607 |
| 15 | 0.003719 | 0.029 | 0.488461 |
| 16 | -0.068302 | -0.5335 | 0.702173 |
| 17 | 0.09528 | 0.7442 | 0.229818 |
| 18 | -0.080587 | -0.6294 | 0.734282 |
| 19 | -0.078153 | -0.6104 | 0.728067 |
| 20 | 0.032897 | 0.2569 | 0.399048 |
| 21 | -0.093652 | -0.7314 | 0.766347 |
| 22 | 0.044433 | 0.347 | 0.36488 |
| 23 | -0.058713 | -0.4586 | 0.67591 |
| 24 | 0.039274 | 0.3067 | 0.380043 |
| 25 | -0.039107 | -0.3054 | 0.619464 |
| 26 | -0.019057 | -0.1488 | 0.558915 |
| 27 | 0.085532 | 0.668 | 0.253318 |
| 28 | -0.125766 | -0.9823 | 0.835075 |
| 29 | -0.098623 | -0.7703 | 0.777945 |
| 30 | 0.002451 | 0.0191 | 0.492394 |
| 31 | 0.039793 | 0.3108 | 0.37851 |
| 32 | -0.026506 | -0.207 | 0.581657 |
| 33 | -0.002258 | -0.0176 | 0.507006 |
| 34 | -0.099949 | -0.7806 | 0.780979 |
| 35 | -0.069388 | -0.5419 | 0.705081 |
| 36 | 0.020025 | 0.1564 | 0.438118 |
| 37 | -0.034084 | -0.2662 | 0.604512 |
| 38 | 0.023181 | 0.181 | 0.428465 |
| 39 | -0.012273 | -0.0959 | 0.538026 |
| 40 | -0.002488 | -0.0194 | 0.507722 |
| 41 | 0.002939 | 0.023 | 0.49088 |
| 42 | -0.027236 | -0.2127 | 0.583873 |
| 43 | -0.043558 | -0.3402 | 0.632563 |
| 44 | 0.030869 | 0.2411 | 0.405144 |
| 45 | 0.041021 | 0.3204 | 0.374885 |
| 46 | 0.006433 | 0.0502 | 0.480047 |
| 47 | -0.043205 | -0.3374 | 0.631528 |
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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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