| Opdracht 9: Decompositie van multiplicatieve tijdsreeksen (eigen reeks) - Yesse De Ley | | *Unverified author* | | R Software Module: /rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Wed, 11 May 2011 19:02:20 +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/11/t1305140318rmuq96roof7vpk2.htm/, Retrieved Wed, 11 May 2011 20:58:42 +0200 | | | | Original text written by user: | | | | | IsPrivate? | | No (this computation is public) | | | | User-defined keywords: | | KDGP2W92 | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 101397
97994
94044
91159
87239
89235
118647
125620
125154
117529
109459
108483
107137
104699
100804
96066
91971
93228
120144
127233
127166
118194
109940
106683
102834
99882
96666
92540
88744
89321
115870
122401
122030
113802
105791
103076
98658
96945
92497
90687
88796
90015
113228
118711
117460
106556
97347
92657
93118
89037
83570
81693
75956
73993
97088
102394
96549
89727
82336
82653
82303
79596
74472
73562
66618
69029
89899
93774
90305
83799
80320
82497
84420
84646
84186
83269
77793
81145
101691
107357
104253
95963
91432
94324
93855
92183
87600
83641
78195
79604
100846
105293
102518
93132
87479
85476 | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 101397 | NA | NA | 0.983854734637985 | NA | | 2 | 97994 | NA | NA | 0.963449970065537 | NA | | 3 | 94044 | NA | NA | 0.925032362623144 | NA | | 4 | 91159 | NA | NA | 0.901150444238061 | NA | | 5 | 87239 | NA | NA | 0.851836315164543 | NA | | 6 | 89235 | NA | NA | 0.866964915297973 | NA | | 7 | 118647 | 117967.201266888 | 105735.833333333 | 1.11567855047773 | 1.00576260796062 | | 8 | 125620 | 125012.148209611 | 106254.375 | 1.17653647870604 | 1.00486234177314 | | 9 | 125154 | 123235.035242689 | 106815.416666667 | 1.15371955742365 | 1.01557158444051 | | 10 | 117529 | 114798.563981642 | 107301.541666667 | 1.06986872880415 | 1.02378458339248 | | 11 | 109459 | 107618.304285136 | 107703.166666667 | 0.999212071620945 | 1.01710392787817 | | 12 | 108483 | 107277.375148604 | 108066.708333333 | 0.992695870940248 | 1.0112383888003 | | 13 | 107137 | 106546.999421041 | 108295.458333333 | 0.983854734637985 | 1.00553746780449 | | 14 | 104699 | 104462.103148105 | 108425.041666667 | 0.963449970065537 | 1.00226777792861 | | 15 | 100804 | 100436.390890201 | 108576.083333333 | 0.925032362623144 | 1.00366011867353 | | 16 | 96066 | 97943.9015519298 | 108687.625 | 0.901150444238061 | 0.980826763870192 | | 17 | 91971 | 92624.7411680348 | 108735.375 | 0.851836315164543 | 0.992942045939445 | | 18 | 93228 | 94222.108229965 | 108680.416666667 | 0.866964915297973 | 0.989449310266558 | | 19 | 120144 | 120968.701973917 | 108426.125 | 1.11567855047773 | 0.993182517787992 | | 20 | 127233 | 127120.207445332 | 108046.125 | 1.17653647870604 | 1.00088729051765 | | 21 | 127166 | 124224.445906477 | 107673 | 1.15371955742365 | 1.0236793496808 | | 22 | 118194 | 114854.330889131 | 107353.666666667 | 1.06986872880415 | 1.02907743299722 | | 23 | 109940 | 106987.926369452 | 107072.291666667 | 0.999212071620945 | 1.02759258666584 | | 24 | 106683 | 105995.142981973 | 106775.041666667 | 0.992695870940248 | 1.00648951450675 | | 25 | 102834 | 104715.758802248 | 106434.166666667 | 0.983854734637985 | 0.98202984131737 | | 26 | 99882 | 102178.445712808 | 106054.75 | 0.963449970065537 | 0.977525145378873 | | 27 | 96666 | 97719.8791852974 | 105639.416666667 | 0.925032362623144 | 0.989215304049865 | | 28 | 92540 | 94839.2505318538 | 105242.416666667 | 0.901150444238061 | 0.97575634013386 | | 29 | 88744 | 89346.1651636856 | 104886.541666667 | 0.851836315164543 | 0.993260313270498 | | 30 | 89321 | 90652.7775501452 | 104563.375 | 0.866964915297973 | 0.985309026528078 | | 31 | 115870 | 116297.30939646 | 104239.083333333 | 1.11567855047773 | 0.996325715541676 | | 32 | 122401 | 122292.388049668 | 103942.708333333 | 1.17653647870604 | 1.00088813336679 | | 33 | 122030 | 119579.138323455 | 103646.625 | 1.15371955742365 | 1.02049572953031 | | 34 | 113802 | 110619.835038388 | 103395.708333333 | 1.06986872880415 | 1.02876667607132 | | 35 | 105791 | 103239.257381257 | 103320.666666667 | 0.999212071620945 | 1.02471678587651 | | 36 | 103076 | 102596.855479449 | 103351.75 | 0.992695870940248 | 1.0046701676997 | | 37 | 98658 | 101603.252361327 | 103270.583333333 | 0.983854734637985 | 0.97101222359642 | | 38 | 96945 | 99241.8502040483 | 103006.75 | 0.963449970065537 | 0.976856032013452 | | 39 | 92497 | 94966.2120138287 | 102662.583333333 | 0.925032362623144 | 0.973999047014014 | | 40 | 90687 | 92070.7661754138 | 102170.25 | 0.901150444238061 | 0.98497062387015 | | 41 | 88796 | 86475.4412884013 | 101516.5 | 0.851836315164543 | 1.02683488718906 | | 42 | 90015 | 87329.8455239606 | 100730.541666667 | 0.866964915297973 | 1.03074727156482 | | 43 | 113228 | 111641.024966042 | 100065.583333333 | 1.11567855047773 | 1.01421498086784 | | 44 | 118711 | 117071.556447764 | 99505.25 | 1.17653647870604 | 1.0140037734355 | | 45 | 117460 | 113991.866793445 | 98803.7916666667 | 1.15371955742365 | 1.03042439170541 | | 46 | 106556 | 104908.207096076 | 98057.0833333333 | 1.06986872880415 | 1.01570699709333 | | 47 | 97347 | 97070.7881924504 | 97147.3333333333 | 0.999212071620945 | 1.00284546785591 | | 48 | 92657 | 95243.9571633944 | 95944.75 | 0.992695870940248 | 0.972838621573058 | | 49 | 93118 | 93077.2492188484 | 94604.6666666667 | 0.983854734637985 | 1.00043781677578 | | 50 | 89037 | 89843.9176147928 | 93252.2916666667 | 0.963449970065537 | 0.991018672869404 | | 51 | 83570 | 84826.5083139503 | 91701.125 | 0.925032362623144 | 0.985187315393204 | | 52 | 81693 | 81219.4504573156 | 90128.625 | 0.901150444238061 | 1.00583049429685 | | 53 | 75956 | 75644.732966062 | 88801.9583333333 | 0.851836315164543 | 1.0041148540253 | | 54 | 73993 | 76084.551978245 | 87759.6666666667 | 0.866964915297973 | 0.972510162393503 | | 55 | 97088 | 96943.773041142 | 86892.2083333333 | 1.11567855047773 | 1.00148773824593 | | 56 | 102394 | 101238.856031463 | 86048.2083333333 | 1.17653647870604 | 1.0114100851572 | | 57 | 96549 | 98384.3005489698 | 85275.75 | 1.15371955742365 | 0.981345595397547 | | 58 | 89727 | 90465.8262366301 | 84557.875 | 1.06986872880415 | 0.991833090268832 | | 59 | 82336 | 83763.9479639838 | 83830 | 0.999212071620945 | 0.982952714160539 | | 60 | 82653 | 82626.1308464966 | 83234.0833333333 | 0.992695870940248 | 1.00032518954026 | | 61 | 82303 | 81392.0475295003 | 82727.7083333333 | 0.983854734637985 | 1.01119215572221 | | 62 | 79596 | 79069.3755933086 | 82069 | 0.963449970065537 | 1.00666028285591 | | 63 | 74472 | 75343.5775915342 | 81449.6666666667 | 0.925032362623144 | 0.98843195904156 | | 64 | 73562 | 72941.3698327393 | 80942.5 | 0.901150444238061 | 1.00850861683409 | | 65 | 66618 | 68667.8031198866 | 80611.5 | 0.851836315164543 | 0.970148992296902 | | 66 | 69029 | 69808.8819447081 | 80521 | 0.866964915297973 | 0.988828327814707 | | 67 | 89899 | 89926.7127979124 | 80602.7083333333 | 1.11567855047773 | 0.999691829078923 | | 68 | 93774 | 95183.3698426232 | 80901.3333333333 | 1.17653647870604 | 0.985193108365953 | | 69 | 90305 | 94047.180302725 | 81516.5 | 1.15371955742365 | 0.960209542798844 | | 70 | 83799 | 88077.7009224844 | 82325.7083333333 | 1.06986872880415 | 0.951421291908493 | | 71 | 80320 | 83130.2393413945 | 83195.7916666667 | 0.999212071620945 | 0.966194740161236 | | 72 | 82497 | 83551.4888475247 | 84166.25 | 0.992695870940248 | 0.987379173464532 | | 73 | 84420 | 83787.4468507129 | 85162.4166666667 | 0.983854734637985 | 1.00754949784321 | | 74 | 84646 | 83068.3754128094 | 86219.7083333333 | 0.963449970065537 | 1.0189918796335 | | 75 | 84186 | 80817.1482532358 | 87366.8333333333 | 0.925032362623144 | 1.041684862923 | | 76 | 83269 | 79711.112353337 | 88454.8333333333 | 0.901150444238061 | 1.04463477602586 | | 77 | 77793 | 76175.1785381509 | 89424.6666666667 | 0.851836315164543 | 1.02123817092255 | | 78 | 81145 | 78356.6864035504 | 90380.4583333333 | 0.866964915297973 | 1.03558488400198 | | 79 | 101691 | 101823.936967357 | 91266.375 | 1.11567855047773 | 0.998694442865637 | | 80 | 107357 | 108210.226846623 | 91973.5416666667 | 1.17653647870604 | 0.992115099732374 | | 81 | 104253 | 106638.106406075 | 92429.8333333333 | 1.15371955742365 | 0.977633638795192 | | 82 | 95963 | 99056.5600838815 | 92587.5833333333 | 1.06986872880415 | 0.968769760616946 | | 83 | 91432 | 92546.8555381866 | 92619.8333333333 | 0.999212071620945 | 0.987953609750397 | | 84 | 94324 | 91896.2144256323 | 92572.375 | 0.992695870940248 | 1.026418776764 | | 85 | 93855 | 90979.9578822311 | 92472.9583333333 | 0.983854734637985 | 1.03160082928913 | | 86 | 92183 | 88976.290773 | 92351.75 | 0.963449970065537 | 1.03604004166887 | | 87 | 87600 | 85281.9325804817 | 92193.4583333333 | 0.925032362623144 | 1.02718122525343 | | 88 | 83641 | 82908.7320609102 | 92003.2083333333 | 0.901150444238061 | 1.00883221731761 | | 89 | 78195 | 78130.8882382293 | 91720.5416666667 | 0.851836315164543 | 1.00082056870485 | | 90 | 79604 | 79056.0742254289 | 91187.1666666667 | 0.866964915297973 | 1.00693084977896 | | 91 | 100846 | NA | NA | 1.11567855047773 | NA | | 92 | 105293 | NA | NA | 1.17653647870604 | NA | | 93 | 102518 | NA | NA | 1.15371955742365 | NA | | 94 | 93132 | NA | NA | 1.06986872880415 | NA | | 95 | 87479 | NA | NA | 0.999212071620945 | NA | | 96 | 85476 | NA | NA | 0.992695870940248 | NA |
| | | | Charts produced by software: |  | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/1ao1f1305140536.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/1ao1f1305140536.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/2wad51305140536.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/2wad51305140536.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/3y17p1305140536.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/3y17p1305140536.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/426aw1305140536.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/11/t1305140318rmuq96roof7vpk2/426aw1305140536.ps (open in new window) |
| | | | Parameters (Session): | | par1 = multiplicative ; par2 = 12 ; | | | | Parameters (R input): | | par1 = multiplicative ; 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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