Home » date » 2011 » May » 12 »

Decompositie Additief Model Australische Chocoladeproductie

*Unverified author*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Thu, 12 May 2011 14:36:41 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh.htm/, Retrieved Thu, 12 May 2011 16:34:35 +0200
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W92
 
Dataseries X:
» Textbox « » Textfile « » CSV «
7992 6114 5965 8460 8323 6333 5675 10090 9035 6976 6459 10896 9978 7466 7199 10977 9412 6341 7784 11911 10079 7721 8197 12038 11963 8033 8618 13625 11734 8895 8727 13974 12583 9525 9662 15490 13839 10047 9788 14978 13045 9489 8741 13149 14106 9998 10034 15081 13266 9997 9027 14324 13149 11209 10332 15354 13800 11786 10550 16114 13255 11403 10269 14009 15847 12967 11328 15814 18626 13219 13818 18062 15722 12111 11702 15589 14852 13612 12380 15501 16322 12157 11124 14621 14035 11159 10944 15824 14378 11816 12233 17344 16812 12181 13275 18458 17375 14609 13323 18327 16053 15070 13806 18245 17461 14999 16022 20564 16372 15854 15115 18207 19488 16644 18631 21093 22212 19762 19403 21227 23176 20823 20647 21336 23458 22003 21647 26416 25226 24723 19945 24040 25034 24885 21168 23541 26019 24657 20599 24534 28717 26138 22968 26577 28660 30430 27356 25454 30194
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ www.wessa.org


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
17992NANA1403.328125NA
26114NANA-1184.78645833333NA
359655117.112847222227174.125-2057.01215277778847.887152777777
484609081.345486111117242.8751838.47048611111-621.345486111111
583238637.32812572341403.328125-314.328125
663336216.713541666677401.5-1184.78645833333116.286458333333
756755637.237847222227694.25-2057.0121527777837.7621527777774
8100909702.095486111117863.6251838.47048611111387.904513888889
990359445.32812580421403.328125-410.328125
1069767055.963541666678240.75-1184.78645833333-79.963541666667
1164596402.362847222228459.375-2057.0121527777856.6371527777774
121089610476.97048611118638.51838.47048611111419.029513888889
13997810195.5781258792.251403.328125-217.578125
1474667710.088541666678894.875-1184.78645833333-244.088541666666
1571996777.237847222228834.25-2057.01215277778421.762152777777
161097710461.34548611118622.8751838.47048611111515.654513888889
1794129958.7031258555.3751403.328125-546.703125
1863417560.463541666678745.25-1184.78645833333-1219.46354166667
1977846888.362847222228945.375-2057.01215277778895.637152777777
201191111039.72048611119201.251838.47048611111871.279513888889
211007910828.7031259425.3751403.328125-749.703125
2277218308.088541666679492.875-1184.78645833333-587.088541666666
2381977687.237847222229744.25-2057.01215277778509.762152777777
241203811857.220486111110018.751838.47048611111180.779513888889
251196311513.70312510110.3751403.328125449.296875
2680339176.5885416666710361.375-1184.78645833333-1143.58854166667
2786188474.1128472222210531.125-2057.01215277778143.887152777777
281362512448.720486111110610.251838.470486111111176.27951388889
291173412134.95312510731.6251403.328125-400.953125
3088959604.0885416666710788.875-1184.78645833333-709.088541666666
3187278881.6128472222210938.625-2057.01215277778-154.612847222223
321397412961.970486111111123.51838.470486111111012.02951388889
331258312722.45312511319.1251403.328125-139.453125
34952510440.713541666711625.5-1184.78645833333-915.713541666666
3596629914.9878472222211972-2057.01215277778-252.987847222223
361549014032.720486111112194.251838.470486111111457.27951388889
371383913678.57812512275.251403.328125160.421875
381004711042.213541666712227-1184.78645833333-995.213541666666
39978810006.737847222212063.75-2057.01215277778-218.737847222223
401497813733.220486111111894.751838.470486111111244.77951388889
411304513097.45312511694.1251403.328125-52.453125
42948910149.838541666711334.625-1184.78645833333-660.838541666666
4387419181.6128472222211238.625-2057.01215277778-440.612847222223
441314913273.345486111111434.8751838.47048611111-124.345486111111
451410613063.45312511660.1251403.3281251042.546875
46999810878.463541666712063.25-1184.78645833333-880.463541666666
471003410142.737847222212199.75-2057.01215277778-108.737847222223
481508113933.095486111112094.6251838.470486111111147.90451388889
491326613371.95312511968.6251403.328125-105.953125
50999710563.338541666711748.125-1184.78645833333-566.338541666666
5190279581.8628472222211638.875-2057.01215277778-554.862847222223
521432413614.220486111111775.751838.47048611111709.779513888889
531314913493.70312512090.3751403.328125-344.703125
541120911197.463541666712382.25-1184.7864583333311.5364583333339
551033210535.362847222212592.375-2057.01215277778-203.362847222223
561535414584.345486111112745.8751838.47048611111769.654513888889
571380014248.57812512845.251403.328125-448.578125
581178611782.713541666712967.5-1184.786458333333.28645833333394
591055010937.362847222212994.375-2057.01215277778-387.362847222223
601611414716.845486111112878.3751838.470486111111397.15451388889
611325514198.70312512795.3751403.328125-943.703125
621140311312.338541666712497.125-1184.7864583333390.661458333334
631026910500.987847222212558-2057.01215277778-231.987847222223
641400914915.970486111113077.51838.47048611111-906.970486111111
651584714808.70312513405.3751403.3281251038.296875
661296712578.588541666713763.375-1184.78645833333388.411458333334
671132812279.362847222214336.375-2057.01215277778-951.362847222223
681581416553.720486111114715.251838.47048611111-739.720486111111
691862616461.328125150581403.3281252164.671875
701321914465.463541666715650.25-1184.78645833333-1246.46354166667
711381813511.237847222215568.25-2057.01215277778306.762152777777
721806216905.220486111115066.751838.470486111111156.77951388889
731572216067.07812514663.751403.328125-345.078125
741211112905.338541666714090.125-1184.78645833333-794.338541666666
751170211615.237847222213672.25-2057.0121527777886.7621527777774
761558915589.595486111113751.1251838.47048611111-0.595486111111313
771485215426.82812514023.51403.328125-574.828125
781361212912.463541666714097.25-1184.78645833333699.536458333334
791238012212.987847222214270-2057.01215277778167.012152777777
801550116110.345486111114271.8751838.47048611111-609.345486111111
811632215336.328125139331403.328125985.671875
821215712481.213541666713666-1184.78645833333-324.213541666666
831112411213.112847222213270.125-2057.01215277778-89.1128472222226
841462114697.970486111112859.51838.47048611111-76.9704861111113
851403514115.57812512712.251403.328125-80.578125
861115911655.338541666712840.125-1184.78645833333-496.338541666666
871094410976.362847222213033.375-2057.01215277778-32.3628472222226
881582414996.845486111113158.3751838.47048611111827.154513888889
891437814804.95312513401.6251403.328125-426.953125
901181612567.963541666713752.75-1184.78645833333-751.963541666666
911223312189.987847222214247-2057.0121527777843.0121527777774
921734416435.345486111114596.8751838.47048611111908.654513888889
931681216176.07812514772.751403.328125635.921875
941218113857.463541666715042.25-1184.78645833333-1676.46354166667
951327513194.862847222215251.875-2057.0121527777880.1371527777774
961845817464.220486111115625.751838.47048611111993.77951388889
971737517338.57812515935.251403.32812536.421875
981460914740.088541666715924.875-1184.78645833333-131.088541666666
991332313686.237847222215743.25-2057.01215277778-363.237847222223
1001832717474.095486111115635.6251838.47048611111852.90451388889
1011605317156.95312515753.6251403.328125-1103.953125
1021507014618.963541666715803.75-1184.78645833333451.036458333334
1031380613912.487847222215969.5-2057.01215277778-106.487847222223
1041824517975.095486111116136.6251838.47048611111269.904513888891
1051746117808.07812516404.751403.328125-347.078125
1061499915786.838541666716971.625-1184.78645833333-787.838541666666
1071602215068.362847222217125.375-2057.01215277778953.637152777777
1082056418934.595486111117096.1251838.470486111111629.40451388889
1091637218492.95312517089.6251403.328125-2120.953125
1101585415496.838541666716681.625-1184.78645833333357.161458333332
1111511514719.487847222216776.5-2057.01215277778395.512152777777
1121820719103.220486111117264.751838.47048611111-896.220486111111
1131948819206.328125178031403.328125281.671875
1141664417418.463541666718603.25-1184.78645833333-774.463541666668
1151863117247.487847222219304.5-2057.012152777781383.51215277778
1162109321873.220486111120034.751838.47048611111-780.22048611111
1172221221924.328125205211403.328125287.671875
1181976219449.463541666720634.25-1184.78645833333312.536458333332
1191940318714.487847222220771.5-2057.01215277778688.512152777777
1202122722863.095486111121024.6251838.47048611111-1636.09548611111
1212317622716.07812521312.751403.328125459.921875
1222082320297.088541666721481.875-1184.78645833333525.911458333332
1232064719473.737847222221530.75-2057.012152777781173.26215277778
1242133623551.970486111121713.51838.47048611111-2215.97048611111
1252345823389.328125219861403.32812568.671875
1262200321561.213541666722746-1184.78645833333441.786458333332
1272164721544.987847222223602-2057.01215277778102.012152777777
1282641626001.4704861111241631838.47048611111414.529513888891
1292522625693.57812524290.251403.328125-467.578125
1302472322595.713541666723780.5-1184.786458333332127.28645833333
1311994521402.487847222223459.5-2057.01215277778-1457.48784722222
1322404025294.220486111123455.751838.47048611111-1254.22048611111
1332503425032.20312523628.8751403.3281251.796875
1342488522534.588541666723719.375-1184.786458333332350.41145833333
1352116821723.112847222223780.125-2057.01215277778-555.112847222223
1362354125713.220486111123874.751838.47048611111-2172.22048611111
1372601925178.45312523775.1251403.328125840.546875
1382465722643.338541666723828.125-1184.786458333332013.66145833333
1392059922232.487847222224289.5-2057.01215277778-1633.48784722222
1402453426650.345486111124811.8751838.47048611111-2116.34548611111
1412871726696.45312525293.1251403.3281252020.546875
1422613824659.838541666725844.625-1184.786458333331478.16145833333
1432296824035.862847222226092.875-2057.01215277778-1067.86284722222
1442657728460.720486111126622.251838.47048611111-1883.72048611111
1452866029110.57812527707.251403.328125-450.578125
1463043026930.588541666728115.375-1184.786458333333499.41145833333
1472735626109.737847222228166.75-2057.012152777781246.26215277778
14825454NANA1838.47048611111NA
14930194NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/1yt6c1305210997.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/1yt6c1305210997.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/277wx1305210997.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/277wx1305210997.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/3vcz01305210997.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/3vcz01305210997.ps (open in new window)


http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/4m9351305210997.png (open in new window)
http://www.freestatistics.org/blog/date/2011/May/12/t13052108710tuemrhjevta7nh/4m9351305210997.ps (open in new window)


 
Parameters (Session):
par1 = additive ; par2 = 4 ;
 
Parameters (R input):
par1 = additive ; par2 = 4 ;
 
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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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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