autocorrelatie tot inschr
| 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 | 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 |
| Autocorrelation Function | |||
| Time lag k | ACF(k) | T-STAT | P-value |
| 0 | 1 | 7.746 | 0 |
| 1 | 0.333342 | 2.5821 | 0.00614 |
| 2 | 0.199531 | 1.5456 | 0.063735 |
| 3 | 0.044852 | 0.3474 | 0.364746 |
| 4 | -0.160022 | -1.2395 | 0.890011 |
| 5 | -0.308981 | -2.3934 | 0.99008 |
| 6 | -0.509982 | -3.9503 | 0.999896 |
| 7 | -0.304523 | -2.3588 | 0.989196 |
| 8 | -0.254047 | -1.9678 | 0.973143 |
| 9 | 0.028198 | 0.2184 | 0.413921 |
| 10 | 0.118229 | 0.9158 | 0.181719 |
| 11 | 0.232082 | 1.7977 | 0.038628 |
| 12 | 0.653905 | 5.0651 | 2e-06 |
| 13 | 0.236058 | 1.8285 | 0.036223 |
| 14 | 0.140361 | 1.0872 | 0.140641 |
| 15 | -0.014286 | -0.1107 | 0.543871 |
| 16 | -0.090208 | -0.6987 | 0.756294 |
| 17 | -0.236235 | -1.8299 | 0.963881 |
| 18 | -0.404778 | -3.1354 | 0.998671 |
| 19 | -0.206654 | -1.6007 | 0.942656 |
| 20 | -0.230215 | -1.7832 | 0.960197 |
| 21 | 0.056005 | 0.4338 | 0.332991 |
| 22 | 0.082721 | 0.6408 | 0.262062 |
| 23 | 0.192796 | 1.4934 | 0.070287 |
| 24 | 0.437216 | 3.3867 | 0.000627 |
| 25 | 0.169798 | 1.3153 | 0.096715 |
| 26 | 0.041237 | 0.3194 | 0.375258 |
| 27 | -0.080492 | -0.6235 | 0.732336 |
| 28 | -0.101227 | -0.7841 | 0.781966 |
| 29 | -0.196352 | -1.5209 | 0.933235 |
| 30 | -0.305632 | -2.3674 | 0.989423 |
| 31 | -0.169831 | -1.3155 | 0.903328 |
| 32 | -0.175251 | -1.3575 | 0.910145 |
| 33 | 0.04406 | 0.3413 | 0.36704 |
| 34 | 0.060001 | 0.4648 | 0.321891 |
| 35 | 0.129867 | 1.0059 | 0.159241 |
| 36 | 0.266409 | 2.0636 | 0.021695 |
| 37 | 0.141647 | 1.0972 | 0.138471 |
| 38 | 0.021054 | 0.1631 | 0.435499 |
| 39 | -0.036628 | -0.2837 | 0.611198 |
| 40 | -0.024498 | -0.1898 | 0.57493 |
| 41 | -0.159624 | -1.2364 | 0.889443 |
| 42 | -0.206999 | -1.6034 | 0.942952 |
| 43 | -0.112752 | -0.8734 | 0.80703 |
| 44 | -0.106381 | -0.824 | 0.793405 |
| 45 | -0.003679 | -0.0285 | 0.511321 |
| 46 | 0.024825 | 0.1923 | 0.424081 |
| 47 | 0.03496 | 0.2708 | 0.393738 |
| 48 | 0.107208 | 0.8304 | 0.204793 |
| 49 | 0.087145 | 0.675 | 0.251127 |
| 50 | 0.008492 | 0.0658 | 0.473887 |
| 51 | -0.000313 | -0.0024 | 0.500965 |
| 52 | 0.036522 | 0.2829 | 0.389114 |
| 53 | -0.030109 | -0.2332 | 0.591809 |
| 54 | -0.02329 | -0.1804 | 0.571279 |
| 55 | 0.022769 | 0.1764 | 0.4303 |
| 56 | -0.020637 | -0.1599 | 0.563232 |
| 57 | -0.005576 | -0.0432 | 0.517153 |
| 58 | 0.021316 | 0.1651 | 0.434704 |
| 59 | 0.006594 | 0.0511 | 0.479717 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.333342 | 2.5821 | 0.00614 |
| 1 | 0.099466 | 0.7705 | 0.222025 |
| 2 | -0.054768 | -0.4242 | 0.663543 |
| 3 | -0.203545 | -1.5767 | 0.939933 |
| 4 | -0.239864 | -1.858 | 0.96596 |
| 5 | -0.387064 | -2.9982 | 0.998026 |
| 6 | -0.042035 | -0.3256 | 0.627072 |
| 7 | -0.102694 | -0.7955 | 0.785259 |
| 8 | 0.156612 | 1.2131 | 0.114921 |
| 9 | -8.2e-05 | -6e-04 | 0.500253 |
| 10 | 0.01276 | 0.0988 | 0.460797 |
| 11 | 0.502373 | 3.8914 | 0.000126 |
| 12 | -0.218547 | -1.6929 | 0.952165 |
| 13 | -0.121711 | -0.9428 | 0.82521 |
| 14 | -0.04592 | -0.3557 | 0.638342 |
| 15 | 0.051849 | 0.4016 | 0.344696 |
| 16 | 0.073178 | 0.5668 | 0.28647 |
| 17 | -0.012434 | -0.0963 | 0.538203 |
| 18 | 0.036475 | 0.2825 | 0.389254 |
| 19 | -0.065806 | -0.5097 | 0.693945 |
| 20 | 0.023057 | 0.1786 | 0.429427 |
| 21 | -0.00466 | -0.0361 | 0.514337 |
| 22 | 0.030715 | 0.2379 | 0.406377 |
| 23 | 0.004522 | 0.035 | 0.486087 |
| 24 | -0.026098 | -0.2022 | 0.57976 |
| 25 | -0.167664 | -1.2987 | 0.900496 |
| 26 | -0.011193 | -0.0867 | 0.534401 |
| 27 | -0.066362 | -0.514 | 0.695443 |
| 28 | 0.074792 | 0.5793 | 0.282265 |
| 29 | 0.021668 | 0.1678 | 0.433637 |
| 30 | -0.092756 | -0.7185 | 0.762378 |
| 31 | -0.051786 | -0.4011 | 0.655126 |
| 32 | -0.120448 | -0.933 | 0.822717 |
| 33 | -0.03298 | -0.2555 | 0.60038 |
| 34 | -0.044407 | -0.344 | 0.633968 |
| 35 | -0.038252 | -0.2963 | 0.615989 |
| 36 | 0.059312 | 0.4594 | 0.323792 |
| 37 | -0.041046 | -0.3179 | 0.624184 |
| 38 | 0.051766 | 0.401 | 0.344929 |
| 39 | 0.01389 | 0.1076 | 0.45734 |
| 40 | -0.149981 | -1.1617 | 0.87503 |
| 41 | 0.015877 | 0.123 | 0.451266 |
| 42 | 0.023583 | 0.1827 | 0.427836 |
| 43 | 0.02778 | 0.2152 | 0.415179 |
| 44 | -0.058038 | -0.4496 | 0.672676 |
| 45 | -0.088616 | -0.6864 | 0.752453 |
| 46 | -0.099272 | -0.769 | 0.777533 |
| 47 | -0.102832 | -0.7965 | 0.785568 |
| 48 | 0.031165 | 0.2414 | 0.405033 |
| 49 | 0.064478 | 0.4994 | 0.309645 |
| 50 | 0.007852 | 0.0608 | 0.475852 |
| 51 | -0.012132 | -0.094 | 0.537278 |
| 52 | -0.009445 | -0.0732 | 0.529038 |
| 53 | 0.084354 | 0.6534 | 0.257997 |
| 54 | 0.07663 | 0.5936 | 0.277515 |
| 55 | -0.064533 | -0.4999 | 0.690502 |
| 56 | 0.040611 | 0.3146 | 0.377088 |
| 57 | -0.000238 | -0.0018 | 0.500731 |
| 58 | 0.076161 | 0.5899 | 0.278722 |
| 59 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Dec/18/t1197971414tnx8wd0sjsa2qji/2ihb01197972424.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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