Inflatie d=0 & D=0
| 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 | 7.746 | 0 |
| 1 | 0.891282 | 6.9038 | 0 |
| 2 | 0.829418 | 6.4246 | 0 |
| 3 | 0.748515 | 5.798 | 0 |
| 4 | 0.638581 | 4.9464 | 3e-06 |
| 5 | 0.533779 | 4.1346 | 5.6e-05 |
| 6 | 0.39468 | 3.0572 | 0.001667 |
| 7 | 0.279211 | 2.1628 | 0.017278 |
| 8 | 0.167387 | 1.2966 | 0.099871 |
| 9 | 0.071091 | 0.5507 | 0.291953 |
| 10 | 0.016113 | 0.1248 | 0.450545 |
| 11 | -0.072216 | -0.5594 | 0.711009 |
| 12 | -0.127194 | -0.9852 | 0.835769 |
| 13 | -0.094405 | -0.7313 | 0.766267 |
| 14 | -0.092673 | -0.7178 | 0.762179 |
| 15 | -0.066635 | -0.5162 | 0.696178 |
| 16 | -0.038977 | -0.3019 | 0.618121 |
| 17 | -0.019286 | -0.1494 | 0.559127 |
| 18 | 0.012557 | 0.0973 | 0.461418 |
| 19 | 0.047236 | 0.3659 | 0.357866 |
| 20 | 0.067603 | 0.5236 | 0.301226 |
| 21 | 0.079463 | 0.6155 | 0.270271 |
| 22 | 0.057026 | 0.4417 | 0.33014 |
| 23 | 0.069561 | 0.5388 | 0.296004 |
| 24 | 0.035782 | 0.2772 | 0.391303 |
| 25 | -0.005289 | -0.041 | 0.51627 |
| 26 | -0.029211 | -0.2263 | 0.589117 |
| 27 | -0.085269 | -0.6605 | 0.744266 |
| 28 | -0.110811 | -0.8583 | 0.802939 |
| 29 | -0.137704 | -1.0666 | 0.854798 |
| 30 | -0.170807 | -1.3231 | 0.904584 |
| 31 | -0.205532 | -1.592 | 0.941685 |
| 32 | -0.241336 | -1.8694 | 0.966774 |
| 33 | -0.27417 | -2.1237 | 0.981087 |
| 34 | -0.29134 | -2.2567 | 0.98616 |
| 35 | -0.322554 | -2.4985 | 0.992385 |
| 36 | -0.324737 | -2.5154 | 0.992707 |
| 37 | -0.339882 | -2.6327 | 0.994622 |
| 38 | -0.338689 | -2.6235 | 0.99449 |
| 39 | -0.308466 | -2.3894 | 0.989981 |
| 40 | -0.301467 | -2.3352 | 0.988551 |
| 41 | -0.292443 | -2.2653 | 0.98644 |
| 42 | -0.258574 | -2.0029 | 0.975144 |
| 43 | -0.236452 | -1.8316 | 0.964008 |
| 44 | -0.194887 | -1.5096 | 0.931802 |
| 45 | -0.163989 | -1.2703 | 0.89555 |
| 46 | -0.134711 | -1.0435 | 0.84954 |
| 47 | -0.09247 | -0.7163 | 0.761698 |
| 48 | -0.075884 | -0.5878 | 0.720563 |
| 49 | -0.034454 | -0.2669 | 0.604762 |
| 50 | -0.020704 | -0.1604 | 0.563437 |
| 51 | -0.005198 | -0.0403 | 0.515993 |
| 52 | 0.011117 | 0.0861 | 0.465832 |
| 53 | 0.012715 | 0.0985 | 0.460936 |
| 54 | 0.018769 | 0.1454 | 0.442449 |
| 55 | 0.012535 | 0.0971 | 0.461487 |
| 56 | 0.009002 | 0.0697 | 0.472321 |
| 57 | 0.003578 | 0.0277 | 0.48899 |
| 58 | 0.00126 | 0.0098 | 0.496122 |
| 59 | 0.000158 | 0.0012 | 0.499515 |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.891282 | 6.9038 | 0 |
| 1 | 0.170386 | 1.3198 | 0.095957 |
| 2 | -0.083323 | -0.6454 | 0.73944 |
| 3 | -0.220265 | -1.7062 | 0.953426 |
| 4 | -0.105498 | -0.8172 | 0.791471 |
| 5 | -0.233667 | -1.81 | 0.962346 |
| 6 | -0.029317 | -0.2271 | 0.589436 |
| 7 | -0.007502 | -0.0581 | 0.523074 |
| 8 | 0.053898 | 0.4175 | 0.338905 |
| 9 | 0.171086 | 1.3252 | 0.09506 |
| 10 | -0.147733 | -1.1443 | 0.871486 |
| 11 | -0.062195 | -0.4818 | 0.684137 |
| 12 | 0.411009 | 3.1837 | 0.001153 |
| 13 | 0.021759 | 0.1685 | 0.433361 |
| 14 | -0.076174 | -0.59 | 0.72131 |
| 15 | -0.039046 | -0.3025 | 0.618323 |
| 16 | -0.151074 | -1.1702 | 0.876728 |
| 17 | -0.113698 | -0.8807 | 0.809002 |
| 18 | 0.149238 | 1.156 | 0.126133 |
| 19 | -0.060052 | -0.4652 | 0.678249 |
| 20 | 0.056148 | 0.4349 | 0.332591 |
| 21 | -0.106275 | -0.8232 | 0.793174 |
| 22 | -0.068211 | -0.5284 | 0.700401 |
| 23 | -0.092563 | -0.717 | 0.761919 |
| 24 | 0.131519 | 1.0187 | 0.156208 |
| 25 | 0.033842 | 0.2621 | 0.397057 |
| 26 | -0.064438 | -0.4991 | 0.690246 |
| 27 | 0.014921 | 0.1156 | 0.454186 |
| 28 | -0.066992 | -0.5189 | 0.697136 |
| 29 | -0.088713 | -0.6872 | 0.752687 |
| 30 | -0.025886 | -0.2005 | 0.579121 |
| 31 | -0.065743 | -0.5092 | 0.693776 |
| 32 | -0.18304 | -1.4178 | 0.919293 |
| 33 | 0.002346 | 0.0182 | 0.492781 |
| 34 | -0.04376 | -0.339 | 0.63209 |
| 35 | -0.024458 | -0.1895 | 0.574811 |
| 36 | 0.085923 | 0.6656 | 0.254122 |
| 37 | 0.063455 | 0.4915 | 0.312427 |
| 38 | 0.060145 | 0.4659 | 0.321494 |
| 39 | 0.010709 | 0.083 | 0.467082 |
| 40 | -0.152353 | -1.1801 | 0.878696 |
| 41 | 0.008096 | 0.0627 | 0.475103 |
| 42 | 0.005135 | 0.0398 | 0.484201 |
| 43 | -0.035102 | -0.2719 | 0.606683 |
| 44 | -0.036234 | -0.2807 | 0.610034 |
| 45 | 0.017434 | 0.135 | 0.446515 |
| 46 | 0.034845 | 0.2699 | 0.394079 |
| 47 | -0.029749 | -0.2304 | 0.590732 |
| 48 | 0.014348 | 0.1111 | 0.45594 |
| 49 | 0.050585 | 0.3918 | 0.348287 |
| 50 | 0.102609 | 0.7948 | 0.21493 |
| 51 | -0.082261 | -0.6372 | 0.736788 |
| 52 | -0.094741 | -0.7339 | 0.767055 |
| 53 | 0.073207 | 0.5671 | 0.286395 |
| 54 | -0.064994 | -0.5034 | 0.69175 |
| 55 | 0.085785 | 0.6645 | 0.254461 |
| 56 | -0.016042 | -0.1243 | 0.549237 |
| 57 | -0.009016 | -0.0698 | 0.527724 |
| 58 | -0.035996 | -0.2788 | 0.60933 |
| 59 | NA | NA | NA |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196366352rrxkp4bcka6cye0/2pfqr1196366968.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196366352rrxkp4bcka6cye0/2pfqr1196366968.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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