| classical decomposition - hondenvoeding - Peter De Klerck | | R Software Module: rwasp_decompose.wasp (opens new window with default values) | | Title produced by software: Classical Decomposition | | Date of computation: Sun, 25 May 2008 04:41:12 -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/25/t1211713167n0cjnhpal669dgs.htm/, Retrieved Sun, 25 May 2008 12:59:31 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 2,02
1,99
1,99
2,01
2,01
2,01
2
2,01
2,02
2,01
2
2,01
2,01
2,01
2
2
1,98
2,01
1,99
1,99
2
2
1,99
1,96
1,98
1,98
1,99
1,99
1,99
1,99
1,98
1,98
1,98
1,98
1,98
1,98
1,97
1,99
2
1,99
1,98
1,98
1,96
1,95
1,94
1,93
1,92
1,91
1,92
1,93
1,94
1,93
1,94
1,93
1,93
1,92
1,92
1,91
1,92
1,92
1,93
1,91
1,95
2,01
1,98
2,01
2
1,99
1,98
1,98
1,99
1,98
1,99
| | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 2.02 | NA | NA | -0.00533854166666672 | NA | | 2 | 1.99 | NA | NA | 0.00382812499999999 | NA | | 3 | 1.99 | NA | NA | 0.0108072916666668 | NA | | 4 | 2.01 | NA | NA | 0.00789062500000007 | NA | | 5 | 2.01 | NA | NA | 0.00476562499999997 | NA | | 6 | 2.01 | NA | NA | 0.0115364583333333 | NA | | 7 | 2 | 2.00705729166667 | 2.00625 | 0.000807291666666686 | -0.00705729166666624 | | 8 | 2.01 | 2.00434895833333 | 2.00666666666667 | -0.00231770833333330 | 0.00565104166666686 | | 9 | 2.02 | 2.00716145833333 | 2.00791666666667 | -0.00075520833333328 | 0.0128385416666665 | | 10 | 2.01 | 2.002578125 | 2.00791666666667 | -0.00533854166666672 | 0.00742187499999991 | | 11 | 2 | 1.99830729166667 | 2.00625 | -0.0079427083333334 | 0.00169270833333313 | | 12 | 2.01 | 1.98705729166667 | 2.005 | -0.0179427083333334 | 0.0229427083333333 | | 13 | 2.01 | 1.99924479166667 | 2.00458333333333 | -0.00533854166666672 | 0.0107552083333333 | | 14 | 2.01 | 2.00716145833333 | 2.00333333333333 | 0.00382812499999999 | 0.00283854166666675 | | 15 | 2 | 2.01247395833333 | 2.00166666666667 | 0.0108072916666668 | -0.0124739583333333 | | 16 | 2 | 2.00830729166667 | 2.00041666666667 | 0.00789062500000007 | -0.00830729166666688 | | 17 | 1.98 | 2.00434895833333 | 1.99958333333333 | 0.00476562499999997 | -0.0243489583333332 | | 18 | 2.01 | 2.00861979166667 | 1.99708333333333 | 0.0115364583333333 | 0.00138020833333319 | | 19 | 1.99 | 1.99455729166667 | 1.99375 | 0.000807291666666686 | -0.00455729166666652 | | 20 | 1.99 | 1.98893229166667 | 1.99125 | -0.00231770833333330 | 0.00106770833333325 | | 21 | 2 | 1.988828125 | 1.98958333333333 | -0.00075520833333328 | 0.0111718750000001 | | 22 | 2 | 1.98341145833333 | 1.98875 | -0.00533854166666672 | 0.0165885416666669 | | 23 | 1.99 | 1.98080729166667 | 1.98875 | -0.0079427083333334 | 0.00919270833333341 | | 24 | 1.96 | 1.970390625 | 1.98833333333333 | -0.0179427083333334 | -0.0103906249999999 | | 25 | 1.98 | 1.98174479166667 | 1.98708333333333 | -0.00533854166666672 | -0.00174479166666686 | | 26 | 1.98 | 1.990078125 | 1.98625 | 0.00382812499999999 | -0.0100781250000002 | | 27 | 1.99 | 1.99580729166667 | 1.985 | 0.0108072916666668 | -0.00580729166666671 | | 28 | 1.99 | 1.99122395833333 | 1.98333333333333 | 0.00789062500000007 | -0.00122395833333311 | | 29 | 1.99 | 1.98684895833333 | 1.98208333333333 | 0.00476562499999997 | 0.00315104166666691 | | 30 | 1.99 | 1.99403645833333 | 1.9825 | 0.0115364583333333 | -0.00403645833333321 | | 31 | 1.98 | 1.98372395833333 | 1.98291666666667 | 0.000807291666666686 | -0.00372395833333306 | | 32 | 1.98 | 1.98059895833333 | 1.98291666666667 | -0.00231770833333330 | -0.000598958333333233 | | 33 | 1.98 | 1.98299479166667 | 1.98375 | -0.00075520833333328 | -0.00299479166666683 | | 34 | 1.98 | 1.978828125 | 1.98416666666667 | -0.00533854166666672 | 0.00117187499999982 | | 35 | 1.98 | 1.97580729166667 | 1.98375 | -0.0079427083333334 | 0.0041927083333333 | | 36 | 1.98 | 1.96497395833333 | 1.98291666666667 | -0.0179427083333334 | 0.0150260416666665 | | 37 | 1.97 | 1.976328125 | 1.98166666666667 | -0.00533854166666672 | -0.00632812500000002 | | 38 | 1.99 | 1.98341145833333 | 1.97958333333333 | 0.00382812499999999 | 0.00658854166666667 | | 39 | 2 | 1.98747395833333 | 1.97666666666667 | 0.0108072916666668 | 0.0125260416666666 | | 40 | 1.99 | 1.98080729166667 | 1.97291666666667 | 0.00789062500000007 | 0.00919270833333319 | | 41 | 1.98 | 1.97309895833333 | 1.96833333333333 | 0.00476562499999997 | 0.00690104166666683 | | 42 | 1.98 | 1.974453125 | 1.96291666666667 | 0.0115364583333333 | 0.00554687500000028 | | 43 | 1.96 | 1.95872395833333 | 1.95791666666667 | 0.000807291666666686 | 0.00127604166666684 | | 44 | 1.95 | 1.951015625 | 1.95333333333333 | -0.00231770833333330 | -0.00101562500000019 | | 45 | 1.94 | 1.947578125 | 1.94833333333333 | -0.00075520833333328 | -0.00757812499999977 | | 46 | 1.93 | 1.93799479166667 | 1.94333333333333 | -0.00533854166666672 | -0.00799479166666694 | | 47 | 1.92 | 1.93122395833333 | 1.93916666666667 | -0.0079427083333334 | -0.0112239583333333 | | 48 | 1.91 | 1.91747395833333 | 1.93541666666667 | -0.0179427083333334 | -0.0074739583333332 | | 49 | 1.92 | 1.92674479166667 | 1.93208333333333 | -0.00533854166666672 | -0.0067447916666663 | | 50 | 1.93 | 1.93341145833333 | 1.92958333333333 | 0.00382812499999999 | -0.00341145833333334 | | 51 | 1.94 | 1.93830729166667 | 1.9275 | 0.0108072916666668 | 0.00169270833333335 | | 52 | 1.93 | 1.93372395833333 | 1.92583333333333 | 0.00789062500000007 | -0.00372395833333328 | | 53 | 1.94 | 1.929765625 | 1.925 | 0.00476562499999997 | 0.0102343750000000 | | 54 | 1.93 | 1.936953125 | 1.92541666666667 | 0.0115364583333333 | -0.00695312499999989 | | 55 | 1.93 | 1.92705729166667 | 1.92625 | 0.000807291666666686 | 0.00294270833333332 | | 56 | 1.92 | 1.923515625 | 1.92583333333333 | -0.00231770833333330 | -0.00351562499999991 | | 57 | 1.92 | 1.92466145833333 | 1.92541666666667 | -0.00075520833333328 | -0.00466145833333331 | | 58 | 1.91 | 1.923828125 | 1.92916666666667 | -0.00533854166666672 | -0.0138281249999996 | | 59 | 1.92 | 1.92622395833333 | 1.93416666666667 | -0.0079427083333334 | -0.006223958333333 | | 60 | 1.92 | 1.92122395833333 | 1.93916666666667 | -0.0179427083333334 | -0.00122395833333289 | | 61 | 1.93 | 1.940078125 | 1.94541666666667 | -0.00533854166666672 | -0.0100781249999995 | | 62 | 1.91 | 1.955078125 | 1.95125 | 0.00382812499999999 | -0.0450781249999999 | | 63 | 1.95 | 1.96747395833333 | 1.95666666666667 | 0.0108072916666668 | -0.0174739583333337 | | 64 | 2.01 | 1.96997395833333 | 1.96208333333333 | 0.00789062500000007 | 0.0400260416666669 | | 65 | 1.98 | 1.97268229166667 | 1.96791666666667 | 0.00476562499999997 | 0.00731770833333356 | | 66 | 2.01 | 1.98486979166667 | 1.97333333333333 | 0.0115364583333333 | 0.0251302083333331 | | 67 | 2 | 1.979140625 | 1.97833333333333 | 0.000807291666666686 | 0.0208593750000001 | | 68 | 1.99 | NA | NA | -0.00231770833333330 | NA | | 69 | 1.98 | NA | NA | -0.00075520833333328 | NA | | 70 | 1.98 | NA | NA | -0.00533854166666672 | NA | | 71 | 1.99 | NA | NA | -0.0079427083333334 | NA | | 72 | 1.98 | NA | NA | -0.0179427083333334 | NA | | 73 | 1.99 | NA | NA | NA | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/10z9t1211712066.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/10z9t1211712066.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/2gh2w1211712066.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/2gh2w1211712066.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/360aw1211712066.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/360aw1211712066.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/42ctu1211712066.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211713167n0cjnhpal669dgs/42ctu1211712066.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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