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*The author of this computation has been verified*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Thu, 09 Dec 2010 16:32:57 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y.htm/, Retrieved Thu, 09 Dec 2010 17:31:11 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
240.8 241.1 223.8 206.1 174.7 203.3 220.5 299.5 347.4 338.3 327.7 351.6 396.6 438.8 395.6 363.5 378.8 357 369 464.8 479.1 431.3 366.5 326.3 355.1 331.6 261.3 249 205.5 235.6 240.9 264.9 253.8 232.3 193.8 177 213.2 207.2 180.6 188.6 175.4 199 179.6 225.8 234 200.2 183.6 178.2 203.2 208.5 191.8 172.8 148 159.4 154.5 213.2 196.4 182.8 176.4 153.6 173.2 171 151.2 161.9 157.2 201.7 236.4 356.1 398.3 403.7 384.6 365.8 368.1 367.9 347 343.3 292.9 311.5 300.9 366.9 356.9 329.7 316.2 269 289.3 266.2 253.6 233.8 228.4 253.6 260.1 306.6 309.2 309.5 271 279.9 317.9 298.4 246.7 227.3 209.1 259.9 266 320.6 308.5 282.2 262.7 263.5 313.1 284.3 252.6 250.3 246.5 312.7 333.2 446.4 511.6 515.5 506.4 483.2 522.3 509.8 460.7 405.8 375 378.5 406.8 467.8 469.8 429.8 355.8 332.7 378 360.5 334.7 319.5 323.1 363.6 352.1 411.9 388.6 416.4 360.7 338 417.2 388.4 371.1 331.5 353.7 396.7 447 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1240.8NANA42.5722222222222NA
2241.1NANA16.7456417624521NA
3223.8NANA-15.2323754789272NA
4206.1NANA-33.3601053639847NA
5174.7NANA-48.4134099616858NA
6203.3NANA-27.0145593869732NA
7220.5245.139607279694271.058333333333-25.9187260536398-24.6396072796935
8299.5333.386877394636285.787547.599377394636-33.886877394636
9347.4355.559578544061301.18333333333354.376245210728-8.15957854406133
10338.3345.747365900383314.930.8473659003831-7.44736590038309
11327.7319.841762452107329.9625-10.12073754789277.85823754789277
12351.6312.789894636015344.870833333333-32.08093869731838.8101053639847
13396.6400.034722222222357.462542.5722222222222-3.43472222222215
14438.8387.283141762452370.537516.745641762452151.5168582375479
15395.6367.680124521073382.9125-15.232375478927227.9198754789272
16363.5358.914894636015392.275-33.36010536398474.58510536398461
17378.8349.353256704981397.766666666667-48.413409961685829.4467432950192
18357371.314607279693398.329166666667-27.0145593869732-14.3146072796935
19369369.627107279693395.545833333333-25.9187260536398-0.627107279693462
20464.8436.949377394636389.3547.59937739463627.850622605364
21479.1433.663745210728379.287554.37624521072845.436254789272
22431.3399.768199233716368.92083333333330.847365900383131.5318007662836
23366.5346.808429118774356.929166666667-10.120737547892719.6915708812261
24326.3312.569061302682344.65-32.08093869731813.730938697318
25355.1376.826388888889334.25416666666742.5722222222222-21.7263888888888
26331.6337.333141762452320.587516.7456417624521-5.73314176245214
27261.3287.638457854406302.870833333333-15.2323754789272-26.3384578544061
28249251.831561302682285.191666666667-33.3601053639847-2.83156130268196
29205.5221.290756704981269.704166666667-48.4134099616858-15.7907567049808
30235.6229.272940613027256.2875-27.01455938697326.32705938697319
31240.9218.235440613027244.154166666667-25.918726053639822.6645593869732
32264.9280.657710727969233.05833333333347.599377394636-15.7577107279693
33253.8278.888745210728224.512554.376245210728-25.0887452107279
34232.3249.480699233716218.63333333333330.8473659003831-17.1806992337164
35193.8204.741762452107214.8625-10.1207375478927-10.9417624521072
36177180.002394636015212.083333333333-32.080938697318-3.00239463601528
37213.2250.576388888889208.00416666666742.5722222222222-37.3763888888889
38207.2220.566475095785203.82083333333316.7456417624521-13.3664750957854
39180.6186.134291187739201.366666666667-15.2323754789272-5.53429118773943
40188.6165.844061302682199.204166666667-33.360105363984722.755938697318
41175.4149.028256704981197.441666666667-48.413409961685826.3717432950192
42199170.052107279693197.066666666667-27.014559386973228.9478927203065
43179.6170.78127394636196.7-25.91872605363988.81872605363984
44225.8243.936877394636196.337547.599377394636-18.136877394636
45234251.234578544061196.85833333333354.376245210728-17.2345785440613
46200.2227.51403256705196.66666666666730.8473659003831-27.3140325670498
47183.6184.745929118774194.866666666667-10.1207375478927-1.14592911877392
48178.2159.994061302682192.075-32.08093869731818.205938697318
49203.2231.951388888889189.37916666666742.5722222222222-28.7513888888889
50208.5204.553975095785187.80833333333316.74564176245213.94602490421457
51191.8170.484291187739185.716666666667-15.232375478927221.3157088122605
52172.8150.064894636015183.425-33.360105363984722.7351053639847
53148133.986590038314182.4-48.413409961685814.0134099616858
54159.4154.060440613027181.075-27.01455938697325.33955938697318
55154.5152.88127394636178.8-25.91872605363981.61872605363985
56213.2223.586877394636175.987547.599377394636-10.386877394636
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58182.8201.434865900383170.587530.8473659003831-18.6348659003831
59176.4160.395929118774170.516666666667-10.120737547892716.0040708812261
60153.6140.581561302682172.6625-32.08093869731813.018438697318
61173.2220.409722222222177.837542.5722222222222-47.2097222222222
62171203.949808429119187.20416666666716.7456417624521-32.9498084291187
63151.2186.338457854406201.570833333333-15.2323754789272-35.1384578544061
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65157.2188.653256704981237.066666666667-48.4134099616858-31.4532567049808
66201.7227.56877394636254.583333333333-27.0145593869732-25.8687739463602
67236.4245.627107279693271.545833333333-25.9187260536398-9.22710727969343
68356.1335.470210727969287.87083333333347.59937739463620.6297892720307
69398.3358.609578544061304.23333333333354.37624521072839.6904214559387
70403.7350.797365900383319.9530.847365900383152.9026340996169
71384.6323.041762452107333.1625-10.120737547892761.5582375478928
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73368.1393.226388888889350.65416666666742.5722222222222-25.1263888888889
74367.9370.537308429119353.79166666666716.7456417624521-2.63730842911878
75347337.284291187739352.516666666667-15.23237547892729.71570881226052
76343.3314.348227969349347.708333333333-33.360105363984728.9517720306513
77292.9293.361590038314341.775-48.4134099616858-0.461590038314171
78311.5307.877107279694334.891666666667-27.01455938697323.62289272030648
79300.9301.65627394636327.575-25.9187260536398-0.756273946360125
80366.9367.653544061303320.05416666666747.599377394636-0.753544061302705
81356.9366.301245210728311.92554.376245210728-9.401245210728
82329.7334.318199233716303.47083333333330.8473659003831-4.61819923371644
83316.2286.100095785441296.220833333333-10.120737547892730.0999042145594
84269259.039894636015291.120833333333-32.0809386973189.96010536398467
85289.3329.580555555556287.00833333333342.5722222222222-40.2805555555556
86266.2299.541475095785282.79583333333316.7456417624521-33.3414750957855
87253.6263.063457854406278.295833333333-15.2323754789272-9.46345785440616
88233.8242.106561302682275.466666666667-33.3601053639847-8.30656130268198
89228.4224.328256704981272.741666666667-48.41340996168584.07174329501913
90253.6244.297940613027271.3125-27.01455938697329.30205938697321
91260.1247.039607279693272.958333333333-25.918726053639813.0603927203065
92306.6323.091044061303275.49166666666747.599377394636-16.4910440613026
93309.2330.922078544061276.54583333333354.376245210728-21.7220785440613
94309.5306.834865900383275.987530.84736590038312.66513409961692
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96279.9242.289894636015274.370833333333-32.08093869731837.6101053639846
97317.9317.451388888889274.87916666666742.57222222222220.448611111111177
98298.4292.453975095785275.70833333333316.74564176245215.94602490421454
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100227.3241.735727969349275.095833333333-33.3601053639847-14.4357279693486
101209.1225.199090038314273.6125-48.4134099616858-16.0990900383142
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103266245.78127394636271.7-25.918726053639820.2187260536398
104320.6318.511877394636270.912547.5993773946362.08812260536405
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108263.5245.969061302682278.05-32.08093869731817.530938697318
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117511.6470.588745210728416.212554.37624521072841.0112547892721
118515.5462.209865900383431.362530.847365900383153.2901340996169
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120483.2419.210727969349451.291666666667-32.08093869731863.9892720306515
121522.3499.672222222222457.142.572222222222222.6277777777779
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124405.8421.535727969349454.895833333333-33.3601053639847-15.7357279693487
125375396.636590038314445.05-48.4134099616858-21.6365900383141
126378.5405.489607279693432.504166666667-27.0145593869732-26.9896072796934
127406.8394.302107279693420.220833333333-25.918726053639812.4978927203065
128467.8455.586877394636407.987547.59937739463612.213122605364
129469.8450.892911877395396.51666666666754.37624521072818.9070881226054
130429.8418.518199233716387.67083333333330.847365900383111.2818007662835
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134360.5388.366475095785371.62083333333316.7456417624521-27.8664750957854
135334.7350.675957854406365.908333333333-15.2323754789272-15.9759578544061
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189446.1444.826245210728390.4554.3762452107281.273754789272
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193445.3422.726388888889380.15416666666742.572222222222222.5736111111111
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197319.8317.149090038314365.5625-48.41340996168582.65090996168584
198331.8335.827107279694362.841666666667-27.0145593869732-4.0271072796935
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200394.1404.807710727969357.20833333333347.599377394636-10.7077107279692
201417.2408.951245210728354.57554.3762452107288.24875478927208
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203349.2337.308429118774347.429166666667-10.120737547892711.8915708812261
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208284.2285.652394636015319.0125-33.3601053639847-1.45239463601541
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210288.8280.939607279693307.954166666667-27.01455938697327.86039272030655
211278.8278.34377394636304.2625-25.91872605363980.456226053639909
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360545.7576.914894636015608.995833333333-32.080938697318-31.2148946360153
361632.6NA605.3625NANA
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363593.1NANANANA
364579.7NANANANA
365546NANANANA
366562.9NANANANA
367572.5NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/19s1s1291912369.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/19s1s1291912369.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/29s1s1291912369.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/29s1s1291912369.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/32jid1291912369.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/32jid1291912369.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/4da0y1291912369.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/09/t1291912269kqj8xbtsv09vq9y/4da0y1291912369.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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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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