Decompositie van registratie personenwagens

R Software Module: rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Mon, 28 Apr 2008 11:32:48 -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/Apr/28/t1209404196s8zi9sqfmbug3gm.htm/, Retrieved Mon, 28 Apr 2008 19:36:42 +0200

User-defined keywords:

registratie personenwagens

Dataseries X:

» Textbox « » Textfile « » CSV «

56421 53152 53536 52408 41454 38271 35306 26414 31917 38030 27534 18387 50556 43901 48572 43899 37532 40357 35489 29027 34485 42598 30306 26451 47460 50104 61465 53726 39477 43895 31481 29896 33842 39120 33702 25094 51442 45594 52518 48564 41745 49585 32747 33379 35645 37034 35681 20972 58552 54955 65540 51570 51145 46641 35704 33253 35193 41668 34865 21210 56126 49231 59723 48103 47472 50497 40059 34149 36860 46356 36577

Text written by user:

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 56421 NA NA 1.05652718304453 NA 2 53152 NA NA 0.962620027736693 NA 3 53536 NA NA 1.11324708193407 NA 4 52408 47448.5517582813 47447.4166666667 1.13509161463066 0.973092441836521 5 41454 43460.5915993225 43459.6666666667 0.924932655870504 1.03126419395612 6 38271 39430.7242481034 39429.9166666667 0.807581436783536 1.20187035583239 7 35306 36431.2231938497 36430.1666666667 1.05652718304453 0.917290051531516 8 26414 34072.9626200277 34072 0.962620027736693 0.805344418862695 9 31917 31256.1132470819 31255 1.11324708193407 0.917299158177987 10 38030 30869.9684249480 30868.8333333333 1.13509161463066 1.08536345408572 11 27534 33597.8415993225 33596.9166666667 0.924932655870504 0.886053148053118 12 18387 36442.8909147701 36442.0833333333 0.807581436783536 0.624771703279478 13 50556 38320.1398605164 38319.0833333333 1.05652718304453 1.24875407501718 14 43901 39642.2959533611 39641.3333333333 0.962620027736693 1.15045931889062 15 48572 42306.4465804153 42305.3333333333 1.11324708193407 1.03133391507909 16 43899 42881.718424948 42880.5833333333 1.13509161463066 0.901909636538223 17 37532 40386.4249326559 40385.5 0.924932655870504 1.00476877595169 18 40357 37972.8909147701 37972.0833333333 0.807581436783536 1.31603706782893 19 35489 36690.8065271830 36689.75 1.05652718304453 0.915521049966866 20 29027 35980.1292866944 35979.1666666667 0.962620027736693 0.838100615515146 21 34485 34219.2799137486 34218.1666666667 1.11324708193407 0.905277919332233 22 42598 34058.0517582813 34056.9166666667 1.13509161463066 1.10192736192465 23 30306 36811.8415993225 36810.9166666667 0.924932655870504 0.890106297107267 24 26451 40816.4742481034 40815.6666666667 0.807581436783536 0.802470125552593 25 47460 43992.3898605164 43991.3333333333 1.05652718304453 1.02112740825216 26 50104 45683.8792866944 45682.9166666667 0.962620027736693 1.13936711776855 27 61465 47901.9465804153 47900.8333333333 1.11324708193407 1.15263884497464 28 53726 48024.0517582813 48022.9166666667 1.13509161463066 0.985609904270118 29 39477 45008.2582659892 45007.3333333333 0.924932655870504 0.94831090935973 30 43895 41022.2242481034 41021.4166666667 0.807581436783536 1.32500669041608 31 31481 37503.3898605164 37502.3333333333 1.05652718304453 0.794528635811915 32 29896 35804.8792866944 35803.9166666667 0.962620027736693 0.867416450134902 33 33842 33757.0299137486 33755.9166666667 1.11324708193407 0.90056393273928 34 39120 33853.718424948 33852.5833333333 1.13509161463066 1.01806642472741 35 33702 36825.0915993225 36824.1666666667 0.924932655870504 0.989492789306081 36 25094 39689.4742481034 39688.6666666667 0.807581436783536 0.782919404200835 37 51442 42033.0565271830 42032 1.05652718304453 1.15839617352141 38 45594 43490.2126200277 43489.25 0.962620027736693 1.08910783844668 39 52518 46201.5299137486 46200.4166666667 1.11324708193407 1.02110574839075 40 48564 46684.5517582813 46683.4166666667 1.13509161463066 0.916475588301709 41 41745 44108.5082659892 44107.5833333333 0.924932655870504 1.02324843493854 42 49585 41684.3909147701 41683.5833333333 0.807581436783536 1.47298710156047 43 32747 39317.7231938497 39316.6666666667 1.05652718304453 0.788341072668806 44 33379 37851.4626200277 37850.5 0.962620027736693 0.91610827819591 45 35645 34961.8632470819 34960.75 1.11324708193407 0.915854139739551 46 37034 34727.8850916146 34726.75 1.13509161463066 0.9395189978152 47 35681 38676.0915993225 38675.1666666667 0.924932655870504 0.997458212768892 48 20972 42965.2242481034 42964.4166666667 0.807581436783536 0.604428037574278 49 58552 46668.0565271830 46667 1.05652718304453 1.18754800864980 50 54955 49167.9626200277 49167 0.962620027736693 1.16112401942874 51 65540 52595.8632470819 52594.75 1.11324708193407 1.1193669411544 52 51570 52830.968424948 52829.8333333333 1.13509161463066 0.859977275649264 53 51145 49118.2582659892 49117.3333333333 0.924932655870504 1.12579234109258 54 46641 44780.7242481034 44779.9166666667 0.807581436783536 1.28972834494204 55 35704 41426.8898605164 41425.8333333333 1.05652718304453 0.815764768446142 56 33253 39244.9626200277 39244 0.962620027736693 0.880243186622555 57 35193 35769.1965804153 35768.0833333333 1.11324708193407 0.883830644277849 58 41668 35351.8017582813 35350.6666666667 1.13509161463066 1.03842260055349 59 34865 38384.9249326559 38384 0.924932655870504 0.982040335287889 60 21210 41760.4742481034 41759.6666666667 0.807581436783536 0.628922768511082 61 56126 44341.1398605164 44340.0833333333 1.05652718304453 1.19808301576961 62 49231 45927.8792866944 45926.9166666667 0.962620027736693 1.11356731330583 63 59723 49419.1965804153 49418.0833333333 1.11324708193407 1.08558579578297 64 48103 50520.8850916146 50519.75 1.13509161463066 0.838841782370323 65 47472 47924.9249326559 47924 0.924932655870504 1.07096272758835 66 50497 44762.7242481034 44761.9166666667 0.807581436783536 1.39691691347589 67 40059 NA 42711.0833333333 NA NA 68 34149 NA 41657.5833333333 NA NA 69 36860 NA NA NA NA 70 46356 NA NA NA NA 71 36577 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/1l6ae1209403965.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/1l6ae1209403965.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/224671209403965.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/224671209403965.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/36kho1209403965.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/36kho1209403965.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/4yonl1209403965.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Apr/28/t1209404196s8zi9sqfmbug3gm/4yonl1209403965.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 6 ;

Parameters (R input):

par1 = multiplicative ; par2 = 6 ;

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$trend)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) a<-table.element(a,m$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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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