| Wisselkoersen - Referentiewisselkoersen voor de euro in nationale munteenheden - Dollar van de Verenigde Staten | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Sat, 31 May 2008 00:46:30 -0600 | | | | Cite this page as follows: | | Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr.htm/, Retrieved Sat, 31 May 2008 06:47:07 +0000 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 0,9383
0,9217
0,9095
0,892
0,8742
0,8532
0,8607
0,9005
0,9111
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
1,4227
1,4684
1,457
| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 0.9383 | NA | NA | 0.0184368055555556 | NA | | 2 | 0.9217 | NA | NA | 0.00748763888888876 | NA | | 3 | 0.9095 | NA | NA | 0.000842638888888973 | NA | | 4 | 0.892 | NA | NA | -0.00809069444444444 | NA | | 5 | 0.8742 | NA | NA | 0.0120776388888889 | NA | | 6 | 0.8532 | NA | NA | 0.00411180555555547 | NA | | 7 | 0.8607 | 0.892644305555556 | 0.893358333333333 | -0.000714027777777767 | -0.0319443055555556 | | 8 | 0.9005 | 0.879381805555556 | 0.8889125 | -0.00953069444444442 | 0.0211181944444444 | | 9 | 0.9111 | 0.869141805555556 | 0.885354166666667 | -0.0162123611111111 | 0.0419581944444445 | | 10 | 0.9059 | 0.867620972222222 | 0.883691666666667 | -0.0160706944444444 | 0.0382790277777777 | | 11 | 0.8883 | 0.876746805555556 | 0.885216666666667 | -0.00846986111111106 | 0.0115531944444444 | | 12 | 0.8924 | 0.907390138888889 | 0.891258333333333 | 0.0161318055555556 | -0.014990138888889 | | 13 | 0.8833 | 0.919432638888889 | 0.900995833333333 | 0.0184368055555556 | -0.0361326388888890 | | 14 | 0.87 | 0.917183472222222 | 0.909695833333333 | 0.00748763888888876 | -0.0471834722222222 | | 15 | 0.8758 | 0.916663472222222 | 0.915820833333333 | 0.000842638888888973 | -0.0408634722222223 | | 16 | 0.8858 | 0.913767638888889 | 0.921858333333333 | -0.00809069444444444 | -0.0279676388888888 | | 17 | 0.917 | 0.941781805555556 | 0.929704166666667 | 0.0120776388888889 | -0.0247818055555555 | | 18 | 0.9554 | 0.943774305555555 | 0.9396625 | 0.00411180555555547 | 0.0116256944444447 | | 19 | 0.9922 | 0.951648472222222 | 0.9523625 | -0.000714027777777767 | 0.0405515277777778 | | 20 | 0.9778 | 0.958923472222222 | 0.968454166666667 | -0.00953069444444442 | 0.0188765277777779 | | 21 | 0.9808 | 0.969416805555556 | 0.985629166666667 | -0.0162123611111111 | 0.0113831944444445 | | 22 | 0.9811 | 0.98638763888889 | 1.00245833333333 | -0.0160706944444444 | -0.00528763888888906 | | 23 | 1.0014 | 1.01233013888889 | 1.0208 | -0.00846986111111106 | -0.0109301388888887 | | 24 | 1.0183 | 1.05576930555556 | 1.0396375 | 0.0161318055555556 | -0.0374693055555555 | | 25 | 1.0622 | 1.07290347222222 | 1.05446666666667 | 0.0184368055555556 | -0.0107034722222221 | | 26 | 1.0773 | 1.07366680555556 | 1.06617916666667 | 0.00748763888888876 | 0.00363319444444432 | | 27 | 1.0807 | 1.07858430555556 | 1.07774166666667 | 0.000842638888888973 | 0.00211569444444448 | | 28 | 1.0848 | 1.08338013888889 | 1.09147083333333 | -0.00809069444444444 | 0.00141986111111114 | | 29 | 1.1582 | 1.11841930555556 | 1.10634166666667 | 0.0120776388888889 | 0.0397806944444443 | | 30 | 1.1663 | 1.12624930555556 | 1.1221375 | 0.00411180555555547 | 0.0400506944444443 | | 31 | 1.1372 | 1.13848180555556 | 1.13919583333333 | -0.000714027777777767 | -0.00128180555555546 | | 32 | 1.1139 | 1.14576513888889 | 1.15529583333333 | -0.00953069444444442 | -0.0318651388888891 | | 33 | 1.1222 | 1.15295013888889 | 1.1691625 | -0.0162123611111111 | -0.0307501388888889 | | 34 | 1.1692 | 1.16389180555556 | 1.1799625 | -0.0160706944444444 | 0.00530819444444464 | | 35 | 1.1702 | 1.17800097222222 | 1.18647083333333 | -0.00846986111111106 | -0.00780097222222231 | | 36 | 1.2286 | 1.20635263888889 | 1.19022083333333 | 0.0161318055555556 | 0.0222473611111109 | | 37 | 1.2613 | 1.21436180555556 | 1.195925 | 0.0184368055555556 | 0.0469381944444447 | | 38 | 1.2646 | 1.21145847222222 | 1.20397083333333 | 0.00748763888888876 | 0.053141527777778 | | 39 | 1.2262 | 1.21328430555556 | 1.21244166666667 | 0.000842638888888973 | 0.0129156944444446 | | 40 | 1.1985 | 1.21182597222222 | 1.21991666666667 | -0.00809069444444444 | -0.0133259722222223 | | 41 | 1.2007 | 1.24069013888889 | 1.2286125 | 0.0120776388888889 | -0.0399901388888886 | | 42 | 1.2138 | 1.24277013888889 | 1.23865833333333 | 0.00411180555555547 | -0.028970138888889 | | 43 | 1.2266 | 1.24472763888889 | 1.24544166666667 | -0.000714027777777767 | -0.0181276388888889 | | 44 | 1.2176 | 1.23955263888889 | 1.24908333333333 | -0.00953069444444442 | -0.0219526388888887 | | 45 | 1.2218 | 1.23831680555556 | 1.25452916666667 | -0.0162123611111111 | -0.0165168055555556 | | 46 | 1.249 | 1.24634180555556 | 1.2624125 | -0.0160706944444444 | 0.00265819444444437 | | 47 | 1.2991 | 1.26077597222222 | 1.26924583333333 | -0.00846986111111106 | 0.0383240277777779 | | 48 | 1.3408 | 1.28835263888889 | 1.27222083333333 | 0.0161318055555556 | 0.0524473611111114 | | 49 | 1.3119 | 1.28981597222222 | 1.27137916666667 | 0.0184368055555556 | 0.0220840277777781 | | 50 | 1.3014 | 1.27839597222222 | 1.27090833333333 | 0.00748763888888876 | 0.0230040277777779 | | 51 | 1.3201 | 1.27239263888889 | 1.27155 | 0.000842638888888973 | 0.0477073611111112 | | 52 | 1.2938 | 1.26163847222222 | 1.26972916666667 | -0.00809069444444444 | 0.0321615277777778 | | 53 | 1.2694 | 1.27480680555556 | 1.26272916666667 | 0.0120776388888889 | -0.00540680555555517 | | 54 | 1.2165 | 1.25535347222222 | 1.25124166666667 | 0.00411180555555547 | -0.0388534722222222 | | 55 | 1.2037 | 1.23982763888889 | 1.24054166666667 | -0.000714027777777767 | -0.0361276388888889 | | 56 | 1.2292 | 1.22229430555556 | 1.231825 | -0.00953069444444442 | 0.00690569444444455 | | 57 | 1.2256 | 1.20620847222222 | 1.22242083333333 | -0.0162123611111111 | 0.0193915277777776 | | 58 | 1.2015 | 1.19865013888889 | 1.21472083333333 | -0.0160706944444444 | 0.00284986111111118 | | 59 | 1.1786 | 1.20378847222222 | 1.21225833333333 | -0.00846986111111106 | -0.025188472222222 | | 60 | 1.1856 | 1.23072763888889 | 1.21459583333333 | 0.0161318055555556 | -0.0451276388888886 | | 61 | 1.2103 | 1.23774930555556 | 1.2193125 | 0.0184368055555556 | -0.0274493055555558 | | 62 | 1.1938 | 1.23165847222222 | 1.22417083333333 | 0.00748763888888876 | -0.0378584722222222 | | 63 | 1.202 | 1.22913847222222 | 1.22829583333333 | 0.000842638888888973 | -0.0271384722222221 | | 64 | 1.2271 | 1.22465097222222 | 1.23274166666667 | -0.00809069444444444 | 0.00244902777777822 | | 65 | 1.277 | 1.25186513888889 | 1.2397875 | 0.0120776388888889 | 0.0251348611111111 | | 66 | 1.265 | 1.25411597222222 | 1.25000416666667 | 0.00411180555555547 | 0.0108840277777775 | | 67 | 1.2684 | 1.25867763888889 | 1.25939166666667 | -0.000714027777777767 | 0.00972236111111102 | | 68 | 1.2811 | 1.25832763888889 | 1.26785833333333 | -0.00953069444444442 | 0.0227723611111110 | | 69 | 1.2727 | 1.26147097222222 | 1.27768333333333 | -0.0162123611111111 | 0.011229027777778 | | 70 | 1.2611 | 1.27189180555556 | 1.2879625 | -0.0160706944444444 | -0.0107918055555554 | | 71 | 1.2881 | 1.28776763888889 | 1.2962375 | -0.00846986111111106 | 0.000332361111111235 | | 72 | 1.3213 | 1.31866097222222 | 1.30252916666667 | 0.0161318055555556 | 0.00263902777777791 | | 73 | 1.2999 | 1.32847013888889 | 1.31003333333333 | 0.0184368055555556 | -0.0285701388888888 | | 74 | 1.3074 | 1.32520013888889 | 1.3177125 | 0.00748763888888876 | -0.0178001388888889 | | 75 | 1.3242 | 1.32680513888889 | 1.3259625 | 0.000842638888888973 | -0.00260513888888880 | | 76 | 1.3516 | 1.32947597222222 | 1.33756666666667 | -0.00809069444444444 | 0.0221240277777779 | | 77 | 1.3511 | 1.36389013888889 | 1.3518125 | 0.0120776388888889 | -0.0127901388888885 | | 78 | 1.3419 | 1.36909097222222 | 1.36497916666667 | 0.00411180555555547 | -0.0271909722222221 | | 79 | 1.3716 | NA | NA | -0.000714027777777767 | NA | | 80 | 1.3622 | NA | NA | -0.00953069444444442 | NA | | 81 | 1.3896 | NA | NA | -0.0162123611111111 | NA | | 82 | 1.4227 | NA | NA | -0.0160706944444444 | NA | | 83 | 1.4684 | NA | NA | -0.00846986111111106 | NA | | 84 | 1.457 | NA | NA | 0.0161318055555556 | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/11no91212216385.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/11no91212216385.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/2zgvw1212216385.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/2zgvw1212216385.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/355s81212216385.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/355s81212216385.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/43jro1212216385.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212216427qecenfzzcdmqefr/43jro1212216385.ps (open in new window) |
| | | | Parameters (Session): | | par1 = additive ; par2 = 12 ; | | | | Parameters (R input): | | par1 = additive ; par2 = 12 ; | | | | R code (references can be found in the software module): | par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
| | |
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