broodprijs d=1 & 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 | 7.6811 | 0 |
| 1 | 0.068076 | 0.5229 | 0.301501 |
| 2 | -0.066275 | -0.5091 | 0.693698 |
| 3 | -0.057471 | -0.4414 | 0.669748 |
| 4 | -0.065306 | -0.5016 | 0.6911 |
| 5 | 0.035526 | 0.2729 | 0.39295 |
| 6 | 0.037917 | 0.2912 | 0.385943 |
| 7 | -0.040281 | -0.3094 | 0.620949 |
| 8 | 0.040099 | 0.308 | 0.37958 |
| 9 | -0.059763 | -0.459 | 0.676056 |
| 10 | -0.061184 | -0.47 | 0.679944 |
| 11 | 0.04346 | 0.3338 | 0.369849 |
| 12 | 0.0254 | 0.1951 | 0.422991 |
| 13 | -0.047599 | -0.3656 | 0.642019 |
| 14 | 0.032782 | 0.2518 | 0.401034 |
| 15 | -0.06708 | -0.5153 | 0.695848 |
| 16 | -0.068502 | -0.5262 | 0.699629 |
| 17 | -0.066111 | -0.5078 | 0.693258 |
| 18 | -0.053494 | -0.4109 | 0.658681 |
| 19 | 0.026887 | 0.2065 | 0.418548 |
| 20 | -0.066563 | -0.5113 | 0.694468 |
| 21 | -0.067985 | -0.5222 | 0.698257 |
| 22 | -0.065594 | -0.5038 | 0.691873 |
| 23 | -0.0327 | -0.2512 | 0.598723 |
| 24 | -0.034122 | -0.2621 | 0.602919 |
| 25 | -0.035543 | -0.273 | 0.607102 |
| 26 | -0.036965 | -0.2839 | 0.611272 |
| 27 | -0.038387 | -0.2949 | 0.61543 |
| 28 | -0.039808 | -0.3058 | 0.619574 |
| 29 | -0.04123 | -0.3167 | 0.623704 |
| 30 | 0.325459 | 2.4999 | 0.007612 |
| 31 | 0.088855 | 0.6825 | 0.248794 |
| 32 | -0.03527 | -0.2709 | 0.606299 |
| 33 | -0.046917 | -0.3604 | 0.640074 |
| 34 | -0.048339 | -0.3713 | 0.644127 |
| 35 | -0.008859 | -0.0681 | 0.527012 |
| 36 | -5.6e-05 | -4e-04 | 0.50017 |
| 37 | -0.008063 | -0.0619 | 0.524588 |
| 38 | 0.025004 | 0.1921 | 0.424179 |
| 39 | -0.007094 | -0.0545 | 0.521635 |
| 40 | -0.018741 | -0.144 | 0.556986 |
| 41 | 0.020738 | 0.1593 | 0.43699 |
| 42 | 0.033355 | 0.2562 | 0.399342 |
| 43 | -0.005155 | -0.0396 | 0.515726 |
| 44 | 0.024099 | 0.1851 | 0.42689 |
| 45 | -0.004186 | -0.0322 | 0.51277 |
| 46 | -0.015833 | -0.1216 | 0.548191 |
| 47 | -0.017255 | -0.1325 | 0.552494 |
| 48 | -0.014864 | -0.1142 | 0.545254 |
| 49 | 0.028429 | 0.2184 | 0.413949 |
| 50 | -0.003669 | -0.0282 | 0.511194 |
| 51 | -0.011503 | -0.0884 | 0.535054 |
| 52 | -0.012925 | -0.0993 | 0.539373 |
| 53 | 0.000905 | 0.0069 | 0.497239 |
| 54 | 0.003296 | 0.0253 | 0.489944 |
| 55 | 0.001874 | 0.0144 | 0.494282 |
| 56 | 0.004265 | 0.0328 | 0.486988 |
| 57 | 0.002843 | 0.0218 | 0.491324 |
| 58 | 0.001422 | 0.0109 | 0.495662 |
| 59 | NA | NA | NA |
| Partial Autocorrelation Function | |||
| Time lag k | PACF(k) | T-STAT | P-value |
| 0 | 0.068076 | 0.5229 | 0.301501 |
| 1 | -0.071239 | -0.5472 | 0.706848 |
| 2 | -0.048256 | -0.3707 | 0.643891 |
| 3 | -0.063274 | -0.486 | 0.685622 |
| 4 | 0.037728 | 0.2898 | 0.386494 |
| 5 | 0.021966 | 0.1687 | 0.433295 |
| 6 | -0.046658 | -0.3584 | 0.639333 |
| 7 | 0.050391 | 0.3871 | 0.350051 |
| 8 | -0.065742 | -0.505 | 0.692272 |
| 9 | -0.049038 | -0.3767 | 0.646115 |
| 10 | 0.040777 | 0.3132 | 0.377611 |
| 11 | 0.01426 | 0.1095 | 0.456575 |
| 12 | -0.060163 | -0.4621 | 0.677154 |
| 13 | 0.040953 | 0.3146 | 0.377101 |
| 14 | -0.062511 | -0.4802 | 0.683555 |
| 15 | -0.06768 | -0.5199 | 0.697446 |
| 16 | -0.073215 | -0.5624 | 0.712003 |
| 17 | -0.048809 | -0.3749 | 0.645465 |
| 18 | 0.001364 | 0.0105 | 0.495838 |
| 19 | -0.099211 | -0.7621 | 0.775469 |
| 20 | -0.049264 | -0.3784 | 0.646754 |
| 21 | -0.087927 | -0.6754 | 0.748963 |
| 22 | -0.041985 | -0.3225 | 0.625891 |
| 23 | -0.063556 | -0.4882 | 0.686386 |
| 24 | -0.070263 | -0.5397 | 0.704282 |
| 25 | -0.064894 | -0.4985 | 0.689994 |
| 26 | -0.069285 | -0.5322 | 0.701702 |
| 27 | -0.068003 | -0.5223 | 0.698306 |
| 28 | -0.079213 | -0.6084 | 0.727386 |
| 29 | 0.311176 | 2.3902 | 0.010026 |
| 30 | 0.012232 | 0.094 | 0.46273 |
| 31 | -0.018958 | -0.1456 | 0.55764 |
| 32 | -0.034592 | -0.2657 | 0.604303 |
| 33 | -0.015083 | -0.1159 | 0.545919 |
| 34 | -0.061396 | -0.4716 | 0.680522 |
| 35 | -0.062913 | -0.4832 | 0.684645 |
| 36 | -0.015565 | -0.1196 | 0.547379 |
| 37 | -0.062092 | -0.4769 | 0.682417 |
| 38 | -0.016085 | -0.1235 | 0.548954 |
| 39 | -0.02663 | -0.2045 | 0.580684 |
| 40 | -0.032258 | -0.2478 | 0.597418 |
| 41 | -0.05206 | -0.3999 | 0.654657 |
| 42 | -0.017986 | -0.1382 | 0.554705 |
| 43 | -0.052894 | -0.4063 | 0.657 |
| 44 | -0.028501 | -0.2189 | 0.586267 |
| 45 | -0.004868 | -0.0374 | 0.514852 |
| 46 | -0.014828 | -0.1139 | 0.545147 |
| 47 | -0.005052 | -0.0388 | 0.515411 |
| 48 | -0.022167 | -0.1703 | 0.567309 |
| 49 | 0.001122 | 0.0086 | 0.496577 |
| 50 | -0.020897 | -0.1605 | 0.563488 |
| 51 | 0.011707 | 0.0899 | 0.464328 |
| 52 | -0.013289 | -0.1021 | 0.540479 |
| 53 | -0.002051 | -0.0158 | 0.506259 |
| 54 | 0.010274 | 0.0789 | 0.468684 |
| 55 | 0.001851 | 0.0142 | 0.494352 |
| 56 | -0.000445 | -0.0034 | 0.501357 |
| 57 | -0.005063 | -0.0389 | 0.515444 |
| 58 | NA | NA | NA |
| 59 | NA | NA | NA |
 |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196365922g197vw7mwh2la32/125561196366341.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196365922g197vw7mwh2la32/125561196366341.ps (open in new window) |
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| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196365922g197vw7mwh2la32/2y7my1196366341.png (open in new window) |
| http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/29/t1196365922g197vw7mwh2la32/2y7my1196366341.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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