| Classical decomposition prijsindexcijfer ruwe aardolie_Jan De Cleermaecker | | 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 06:51:54 -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/t1211719981x5kkkizh9pmcqmh.htm/, Retrieved Sun, 25 May 2008 14:53:01 +0200 | | | | User-defined keywords: | | | | | Dataseries X: | | » Textbox « » Textfile « » CSV « | | 68,4
70,6
83,9
90,1
90,6
87,1
90,8
94,1
99,8
96,8
87
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147
145,8
164,4
149,8
137,7
151,7
156,8
180
180,4
170,4
191,6
199,5
218,2
217,5
205
194
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253
218,2
203,7
205,6
215,6
188,5
202,9
214
230,3
230
241
259,6
247,8
270,3
289,7
322,7
315
320,2 | | | | Text written by user: | | | | | Output produced by software: |
| Classical Decomposition by Moving Averages | | t | Observations | Fit | Trend | Seasonal | Random | | 1 | 68.4 | NA | NA | -1.13350694444444 | NA | | 2 | 70.6 | NA | NA | -3.37829861111111 | NA | | 3 | 83.9 | NA | NA | 0.158159722222228 | NA | | 4 | 90.1 | NA | NA | 0.386284722222216 | NA | | 5 | 90.6 | NA | NA | -0.387673611111121 | NA | | 6 | 87.1 | NA | NA | 2.28420138888888 | NA | | 7 | 90.8 | 97.9894097222222 | 89.5708333333333 | 8.4185763888889 | -7.18940972222224 | | 8 | 94.1 | 108.223784722222 | 93.0416666666667 | 15.1821180555556 | -14.1237847222222 | | 9 | 99.8 | 97.3196180555556 | 95.825 | 1.49461805555556 | 2.48038194444445 | | 10 | 96.8 | 95.3039930555555 | 96.725 | -1.42100694444445 | 1.49600694444446 | | 11 | 87 | 86.6467013888889 | 96.7291666666667 | -10.0824652777778 | 0.353298611111128 | | 12 | 96.3 | 85.6748263888889 | 97.1958333333333 | -11.5210069444445 | 10.6251736111111 | | 13 | 107.1 | 96.9123263888889 | 98.0458333333333 | -1.13350694444444 | 10.1876736111111 | | 14 | 115.2 | 95.5175347222222 | 98.8958333333333 | -3.37829861111111 | 19.6824652777778 | | 15 | 106.1 | 99.2789930555556 | 99.1208333333333 | 0.158159722222228 | 6.82100694444443 | | 16 | 89.5 | 99.5029513888889 | 99.1166666666666 | 0.386284722222216 | -10.0029513888889 | | 17 | 91.3 | 99.5831597222222 | 99.9708333333333 | -0.387673611111121 | -8.28315972222221 | | 18 | 97.6 | 103.275868055556 | 100.991666666667 | 2.28420138888888 | -5.67586805555555 | | 19 | 100.7 | 109.918576388889 | 101.5 | 8.4185763888889 | -9.2185763888889 | | 20 | 104.6 | 116.590451388889 | 101.408333333333 | 15.1821180555556 | -11.9904513888889 | | 21 | 94.7 | 103.144618055556 | 101.65 | 1.49461805555556 | -8.44461805555555 | | 22 | 101.8 | 101.916493055556 | 103.3375 | -1.42100694444445 | -0.116493055555566 | | 23 | 102.5 | 96.1425347222222 | 106.225 | -10.0824652777778 | 6.3574652777778 | | 24 | 105.3 | 97.5498263888889 | 109.070833333333 | -11.5210069444445 | 7.75017361111112 | | 25 | 110.3 | 110.466493055556 | 111.6 | -1.13350694444444 | -0.166493055555563 | | 26 | 109.8 | 111.338368055556 | 114.716666666667 | -3.37829861111111 | -1.53836805555557 | | 27 | 117.3 | 118.770659722222 | 118.6125 | 0.158159722222228 | -1.47065972222222 | | 28 | 118.8 | 123.736284722222 | 123.35 | 0.386284722222216 | -4.93628472222224 | | 29 | 131.3 | 127.541493055556 | 127.929166666667 | -0.387673611111121 | 3.75850694444445 | | 30 | 125.9 | 133.534201388889 | 131.25 | 2.28420138888888 | -7.63420138888888 | | 31 | 133.1 | 142.743576388889 | 134.325 | 8.4185763888889 | -9.64357638888893 | | 32 | 147 | 153.190451388889 | 138.008333333333 | 15.1821180555556 | -6.1904513888889 | | 33 | 145.8 | 144.073784722222 | 142.579166666667 | 1.49461805555556 | 1.72621527777781 | | 34 | 164.4 | 146.337326388889 | 147.758333333333 | -1.42100694444445 | 18.0626736111111 | | 35 | 149.8 | 141.871701388889 | 151.954166666667 | -10.0824652777778 | 7.9282986111111 | | 36 | 137.7 | 144.799826388889 | 156.320833333333 | -11.5210069444445 | -7.09982638888891 | | 37 | 151.7 | 160.691493055556 | 161.825 | -1.13350694444444 | -8.99149305555554 | | 38 | 156.8 | 164.180034722222 | 167.558333333333 | -3.37829861111111 | -7.38003472222218 | | 39 | 180 | 173.670659722222 | 173.5125 | 0.158159722222228 | 6.32934027777785 | | 40 | 180.4 | 178.577951388889 | 178.191666666667 | 0.386284722222216 | 1.82204861111114 | | 41 | 170.4 | 181.337326388889 | 181.725 | -0.387673611111121 | -10.9373263888889 | | 42 | 191.6 | 188.417534722222 | 186.133333333333 | 2.28420138888888 | 3.18246527777779 | | 43 | 199.5 | 199.935243055556 | 191.516666666667 | 8.4185763888889 | -0.435243055555532 | | 44 | 218.2 | 211.777951388889 | 196.595833333333 | 15.1821180555556 | 6.42204861111111 | | 45 | 217.5 | 201.819618055556 | 200.325 | 1.49461805555556 | 15.6803819444445 | | 46 | 205 | 202.862326388889 | 204.283333333333 | -1.42100694444445 | 2.13767361111115 | | 47 | 194 | 199.684201388889 | 209.766666666667 | -10.0824652777778 | -5.68420138888891 | | 48 | 199.3 | 203.283159722222 | 214.804166666667 | -11.5210069444445 | -3.98315972222221 | | 49 | 219.3 | 218.045659722222 | 219.179166666667 | -1.13350694444444 | 1.25434027777777 | | 50 | 211.1 | 219.580034722222 | 222.958333333333 | -3.37829861111111 | -8.48003472222223 | | 51 | 215.2 | 224.595659722222 | 224.4375 | 0.158159722222228 | -9.39565972222223 | | 52 | 240.2 | 224.798784722222 | 224.4125 | 0.386284722222216 | 15.4012152777777 | | 53 | 242.2 | 224.453993055556 | 224.841666666667 | -0.387673611111121 | 17.7460069444444 | | 54 | 240.7 | 228.288368055556 | 226.004166666667 | 2.28420138888888 | 12.4116319444445 | | 55 | 255.4 | 233.818576388889 | 225.4 | 8.4185763888889 | 21.5814236111111 | | 56 | 253 | 238.957118055556 | 223.775 | 15.1821180555556 | 14.0428819444445 | | 57 | 218.2 | 224.877951388889 | 223.383333333333 | 1.49461805555556 | -6.67795138888891 | | 58 | 203.7 | 221.499826388889 | 222.920833333333 | -1.42100694444445 | -17.7998263888889 | | 59 | 205.6 | 211.917534722222 | 222 | -10.0824652777778 | -6.31753472222223 | | 60 | 215.6 | 209.983159722222 | 221.504166666667 | -11.5210069444445 | 5.61684027777778 | | 61 | 188.5 | 220.558159722222 | 221.691666666667 | -1.13350694444444 | -32.0581597222222 | | 62 | 202.9 | 218.271701388889 | 221.65 | -3.37829861111111 | -15.3717013888889 | | 63 | 214 | 223.762326388889 | 223.604166666667 | 0.158159722222228 | -9.76232638888888 | | 64 | 230.3 | 229.744618055556 | 229.358333333333 | 0.386284722222216 | 0.555381944444434 | | 65 | 230 | 237.433159722222 | 237.820833333333 | -0.387673611111121 | -7.4331597222222 | | 66 | 241 | 249.125868055556 | 246.841666666667 | 2.28420138888888 | -8.12586805555554 | | 67 | 259.6 | 264.889409722222 | 256.470833333333 | 8.4185763888889 | -5.28940972222225 | | 68 | 247.8 | NA | NA | 15.1821180555556 | NA | | 69 | 270.3 | NA | NA | 1.49461805555556 | NA | | 70 | 289.7 | NA | NA | -1.42100694444445 | NA | | 71 | 322.7 | NA | NA | -10.0824652777778 | NA | | 72 | 315 | NA | NA | -11.5210069444445 | NA | | 73 | 320.2 | NA | NA | NA | NA |
| | | Charts produced by software: |  | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/1vm2q1211719900.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/1vm2q1211719900.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/210jx1211719900.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/210jx1211719900.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/3xjn61211719900.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/3xjn61211719900.ps (open in new window) |
 | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/4g3e91211719900.png (open in new window) | | http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211719981x5kkkizh9pmcqmh/4g3e91211719900.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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