| Sarah Geerts - decompositie - inschrijving nieuwe personenwagens | | *Unverified author* | | R Software Module: /rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Fri, 20 May 2011 00:38:57 +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/20/t130585178678vly1qyl70yy4y.htm/, Retrieved Fri, 20 May 2011 02:36:32 +0200 | | | | Original text written by user: | | | | | IsPrivate? | | No (this computation is public) | | | | User-defined keywords: | | KDGP2W92 | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 31.514
27.071
29.462
26.105
22.397
23.843
21.705
18.089
20.764
25.316
17.704
15.548
28.029
29.383
36.438
32.034
22.679
24.319
18.004
17.537
20.366
22.782
19.169
13.807
29.743
25.591
29.096
26.482
22.405
27.044
17.970
18.730
19.684
19.785
18.479
10.698
31.956
29.506
34.506
27.165
26.736
23.691
18.157
17.328
18.205
20.995
17.382
9.367
31.124
26.551
30.651
25.859
25.100
25.778
20.418
18.688
20.424
24.776
19.814
12.738
31.566
30.111
30.019
31.934
25.826
26.835
20.205
17.789
20.520
22.518
15.572
11.509
25.447
24.090
27.786
26.195
20.516
22.759
19.028
16.971
20.036
22.485
18.730
14.538
27.561
25.985
34.670
32.066
27.186
29.586
21.359
21.553
19.573
24.256
22.380
16.167
27.297
28.287 | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 31.514 | NA | NA | 6.01641369047619 | NA | | 2 | 27.071 | NA | NA | 3.96799702380952 | NA | | 3 | 29.462 | NA | NA | 8.51861011904762 | NA | | 4 | 26.105 | NA | NA | 5.4704375 | NA | | 5 | 22.397 | NA | NA | 0.97934226190476 | NA | | 6 | 23.843 | NA | NA | 2.31411011904762 | NA | | 7 | 21.705 | 19.0525982142857 | 23.1479583333333 | -4.09536011904762 | 2.65240178571429 | | 8 | 18.089 | 18.0796041666667 | 23.0990833333333 | -5.01947916666667 | 0.00939583333333616 | | 9 | 20.764 | 20.5638005952381 | 23.4860833333333 | -2.92228273809524 | 0.200199404761911 | | 10 | 25.316 | 22.6173958333333 | 24.0237916666667 | -1.40639583333333 | 2.69860416666667 | | 11 | 17.704 | 19.7195982142857 | 24.2825833333333 | -4.56298511904762 | -2.01559821428571 | | 12 | 15.548 | 15.0537589285714 | 24.3141666666667 | -9.26040773809524 | 0.494241071428569 | | 13 | 28.029 | 30.1962053571429 | 24.1797916666667 | 6.01641369047619 | -2.16720535714285 | | 14 | 29.383 | 27.9705803571429 | 24.0025833333333 | 3.96799702380952 | 1.41241964285715 | | 15 | 36.438 | 32.4816101190476 | 23.963 | 8.51861011904762 | 3.95638988095238 | | 16 | 32.034 | 29.3112708333333 | 23.8408333333333 | 5.4704375 | 2.72272916666667 | | 17 | 22.679 | 24.7756339285714 | 23.7962916666667 | 0.97934226190476 | -2.09663392857142 | | 18 | 24.319 | 26.0989017857143 | 23.7847916666667 | 2.31411011904762 | -1.77990178571428 | | 19 | 18.004 | 19.688306547619 | 23.7836666666667 | -4.09536011904762 | -1.68430654761904 | | 20 | 17.537 | 18.6776041666667 | 23.6970833333333 | -5.01947916666667 | -1.14060416666667 | | 21 | 20.366 | 20.3108839285714 | 23.2331666666667 | -2.92228273809524 | 0.0551160714285714 | | 22 | 22.782 | 21.2895208333333 | 22.6959166666667 | -1.40639583333333 | 1.49247916666667 | | 23 | 19.169 | 17.890181547619 | 22.4531666666667 | -4.56298511904762 | 1.27881845238095 | | 24 | 13.807 | 13.2948839285714 | 22.5552916666667 | -9.26040773809524 | 0.512116071428569 | | 25 | 29.743 | 28.6838303571429 | 22.6674166666667 | 6.01641369047619 | 1.05916964285715 | | 26 | 25.591 | 26.6837053571429 | 22.7157083333333 | 3.96799702380952 | -1.09270535714285 | | 27 | 29.096 | 31.2556101190476 | 22.737 | 8.51861011904762 | -2.15961011904762 | | 28 | 26.482 | 28.0541458333333 | 22.5837083333333 | 5.4704375 | -1.57214583333333 | | 29 | 22.405 | 23.4094255952381 | 22.4300833333333 | 0.97934226190476 | -1.00442559523809 | | 30 | 27.044 | 24.5859017857143 | 22.2717916666667 | 2.31411011904762 | 2.45809821428572 | | 31 | 17.97 | 18.1390982142857 | 22.2344583333333 | -4.09536011904762 | -0.169098214285714 | | 32 | 18.73 | 17.4703125 | 22.4897916666667 | -5.01947916666667 | 1.2596875 | | 33 | 19.684 | 19.9560505952381 | 22.8783333333333 | -2.92228273809524 | -0.272050595238092 | | 34 | 19.785 | 21.7258125 | 23.1322083333333 | -1.40639583333333 | -1.9408125 | | 35 | 18.479 | 18.7781398809524 | 23.341125 | -4.56298511904762 | -0.299139880952385 | | 36 | 10.698 | 14.1214672619048 | 23.381875 | -9.26040773809524 | -3.42346726190477 | | 37 | 31.956 | 29.2663720238095 | 23.2499583333333 | 6.01641369047619 | 2.68962797619048 | | 38 | 29.506 | 27.1673303571429 | 23.1993333333333 | 3.96799702380952 | 2.33866964285714 | | 39 | 34.506 | 31.5979017857143 | 23.0792916666667 | 8.51861011904762 | 2.90809821428572 | | 40 | 27.165 | 28.5385208333333 | 23.0680833333333 | 5.4704375 | -1.37352083333333 | | 41 | 26.736 | 24.0521339285714 | 23.0727916666667 | 0.97934226190476 | 2.68386607142857 | | 42 | 23.691 | 25.2857351190476 | 22.971625 | 2.31411011904762 | -1.59473511904762 | | 43 | 18.157 | 18.7861398809524 | 22.8815 | -4.09536011904762 | -0.629139880952376 | | 44 | 17.328 | 17.7042291666667 | 22.7237083333333 | -5.01947916666667 | -0.376229166666661 | | 45 | 18.205 | 19.5176755952381 | 22.4399583333333 | -2.92228273809524 | -1.3126755952381 | | 46 | 20.995 | 20.8185208333333 | 22.2249166666667 | -1.40639583333333 | 0.176479166666667 | | 47 | 17.382 | 17.5393482142857 | 22.1023333333333 | -4.56298511904762 | -0.157348214285715 | | 48 | 9.367 | 12.8607172619048 | 22.121125 | -9.26040773809524 | -3.49371726190476 | | 49 | 31.124 | 28.3187053571429 | 22.3022916666667 | 6.01641369047619 | 2.80529464285715 | | 50 | 26.551 | 26.4211636904762 | 22.4531666666667 | 3.96799702380952 | 0.12983630952381 | | 51 | 30.651 | 31.1209017857143 | 22.6022916666667 | 8.51861011904762 | -0.469901785714281 | | 52 | 25.859 | 28.3227291666667 | 22.8522916666667 | 5.4704375 | -2.46372916666666 | | 53 | 25.1 | 24.0905089285714 | 23.1111666666667 | 0.97934226190476 | 1.00949107142857 | | 54 | 25.778 | 25.667068452381 | 23.3529583333333 | 2.31411011904762 | 0.110931547619046 | | 55 | 20.418 | 19.4164732142857 | 23.5118333333333 | -4.09536011904762 | 1.00152678571429 | | 56 | 18.688 | 18.6591041666667 | 23.6785833333333 | -5.01947916666667 | 0.0288958333333369 | | 57 | 20.424 | 20.8783005952381 | 23.8005833333333 | -2.92228273809524 | -0.454300595238092 | | 58 | 24.776 | 22.6209791666667 | 24.027375 | -1.40639583333333 | 2.15502083333334 | | 59 | 19.814 | 19.7477648809524 | 24.31075 | -4.56298511904762 | 0.0662351190476222 | | 60 | 12.738 | 15.1246339285714 | 24.3850416666667 | -9.26040773809524 | -2.38663392857143 | | 61 | 31.566 | 30.4366220238095 | 24.4202083333333 | 6.01641369047619 | 1.12937797619048 | | 62 | 30.111 | 28.3418720238095 | 24.373875 | 3.96799702380952 | 1.76912797619048 | | 63 | 30.019 | 32.8590267857143 | 24.3404166666667 | 8.51861011904762 | -2.84002678571429 | | 64 | 31.934 | 29.7207708333333 | 24.2503333333333 | 5.4704375 | 2.21322916666667 | | 65 | 25.826 | 24.9588422619048 | 23.9795 | 0.97934226190476 | 0.867157738095237 | | 66 | 26.835 | 26.0656517857143 | 23.7515416666667 | 2.31411011904762 | 0.769348214285714 | | 67 | 20.205 | 19.3500148809524 | 23.445375 | -4.09536011904762 | 0.854985119047619 | | 68 | 17.789 | 17.9200625 | 22.9395416666667 | -5.01947916666667 | -0.131062499999999 | | 69 | 20.52 | 19.6733422619048 | 22.595625 | -2.92228273809524 | 0.846657738095239 | | 70 | 22.518 | 20.8570625 | 22.2634583333333 | -1.40639583333333 | 1.66093750000001 | | 71 | 15.572 | 17.2400982142857 | 21.8030833333333 | -4.56298511904762 | -1.66809821428571 | | 72 | 11.509 | 12.1515922619048 | 21.412 | -9.26040773809524 | -0.64259226190476 | | 73 | 25.447 | 27.2095386904762 | 21.193125 | 6.01641369047619 | -1.76253869047618 | | 74 | 24.09 | 25.0779970238095 | 21.11 | 3.96799702380952 | -0.987997023809523 | | 75 | 27.786 | 29.5743601190476 | 21.05575 | 8.51861011904762 | -1.78836011904762 | | 76 | 26.195 | 26.5046458333333 | 21.0342083333333 | 5.4704375 | -0.309645833333335 | | 77 | 20.516 | 22.1437589285714 | 21.1644166666667 | 0.97934226190476 | -1.62775892857143 | | 78 | 22.759 | 23.7363184523809 | 21.4222083333333 | 2.31411011904762 | -0.977318452380953 | | 79 | 19.028 | 17.5411398809524 | 21.6365 | -4.09536011904762 | 1.48686011904762 | | 80 | 16.971 | 16.7840625 | 21.8035416666667 | -5.01947916666667 | 0.186937500000003 | | 81 | 20.036 | 19.2470505952381 | 22.1693333333333 | -2.92228273809524 | 0.788949404761908 | | 82 | 22.485 | 21.2943958333333 | 22.7007916666667 | -1.40639583333333 | 1.19060416666667 | | 83 | 18.73 | 18.6603482142857 | 23.2233333333333 | -4.56298511904762 | 0.0696517857142922 | | 84 | 14.538 | 14.5253005952381 | 23.7857083333333 | -9.26040773809524 | 0.0126994047619036 | | 85 | 27.561 | 30.1837053571429 | 24.1672916666667 | 6.01641369047619 | -2.62270535714286 | | 86 | 25.985 | 28.4233303571429 | 24.4553333333333 | 3.96799702380952 | -2.43833035714286 | | 87 | 34.67 | 33.145568452381 | 24.6269583333333 | 8.51861011904762 | 1.52443154761905 | | 88 | 32.066 | 30.1518958333333 | 24.6814583333333 | 5.4704375 | 1.91410416666667 | | 89 | 27.186 | 25.8866755952381 | 24.9073333333333 | 0.97934226190476 | 1.2993244047619 | | 90 | 29.586 | 27.4414017857143 | 25.1272916666667 | 2.31411011904762 | 2.14459821428571 | | 91 | 21.359 | 21.0888065476191 | 25.1841666666667 | -4.09536011904762 | 0.270193452380951 | | 92 | 21.553 | 20.2496041666667 | 25.2690833333333 | -5.01947916666667 | 1.30339583333334 | | 93 | 19.573 | NA | NA | -2.92228273809524 | NA | | 94 | 24.256 | NA | NA | -1.40639583333333 | NA | | 95 | 22.38 | NA | NA | -4.56298511904762 | NA | | 96 | 16.167 | NA | NA | -9.26040773809524 | NA | | 97 | 27.297 | NA | NA | NA | NA | | 98 | 28.287 | NA | NA | NA | NA |
| | | | Charts produced by software: |  | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/13tje1305851933.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/13tje1305851933.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/27n7f1305851933.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/27n7f1305851933.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/3lzt21305851933.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/3lzt21305851933.ps (open in new window) |
 | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/47sgt1305851933.png (open in new window) | | http://www.freestatistics.org/blog/date/2011/May/20/t130585178678vly1qyl70yy4y/47sgt1305851933.ps (open in new window) |
| | | | Parameters (Session): | | par1 = 4 ; | | | | 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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