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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: Wed, 08 Dec 2010 16:48:06 +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/08/t1291826782zw6sb7d4y1eqqdx.htm/, Retrieved Wed, 08 Dec 2010 17:46:29 +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/08/t1291826782zw6sb7d4y1eqqdx.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 «
280.7 264.6 240.7 201.4 240.8 241.1 223.8 206.1 174.7 203.3 220.5 299.5 347.4 338.3 327.7 351.6 396.6 438.8 395.6 363.5 378.8 0.357 0.369 464.8 479.1 431.3 366.5 326.3 355.1 331.6 261.3 0.249 205.5 235.6 240.9 264.9 253.8 232.3 193.8 0.177 213.2 207.2 180.6 188.6 175.4 0.199 179.6 225.8 0.234 200.2 183.6 178.2 203.2 208.5 191.8 172.8 0.148 159.4 154.5 213.2 196.4 182.8 176.4 153.6 173.2 0.171 151.2 161.9 157.2 201.7 236.4 356.1 398.3 403.7 384.6 365.8 368.1 367.9 0.347 343.3 292.9 311.5 300.9 366.9 356.9 329.7 316.2 0.269 289.3 266.2 253.6 233.8 228.4 253.6 260.1 306.6 309.2 309.5 0.271 279.9 317.9 298.4 246.7 227.3 209.1 259.9 0.266 320.6 308.5 282.2 262.7 263.5 313.1 284.3 252.6 250.3 246.5 312.7 333.2 446.4 511.6 515.5 506.4 483.2 522.3 509.8 460.7 405.8 0.375 378.5 406.8 467.8 469.8 429.8 355.8 332.7 0.378 360.5 334.7 319.5 323.1 363.6 352.1 411.9 388.6 416.4 36 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'George Udny Yule' @ 72.249.76.132


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1280.7NANA61.3300828544061NA
2264.6NANA69.9439276819923NA
3240.7NANA-28.4960378352490NA
4201.4NANA-15.0792619731801NA
5240.8NANA30.7890886015326NA
6241.1NANA-30.3986470306514NA
7223.8220.179916187739235.879166666667-15.69925047892723.62008381226053
8206.1222.370462164751241.729166666667-19.3587045019157-16.270462164751
9174.7183.629611590038248.425-64.7953884099617-8.92961159003835
10203.3254.010588601533258.308333333333-4.29774473180077-50.7105886015325
11220.5216.494042624521271.058333333333-54.56429070881234.00595737547894
12299.5356.413726532567285.787570.626226532567-56.913726532567
13347.4362.513416187739301.18333333333361.3300828544061-15.1134161877395
14338.3384.843927681992314.969.9439276819923-46.5439276819923
15327.7301.466462164751329.9625-28.496037835249026.2335378352491
16351.6314.931446360153330.010708333333-15.079261973180136.6685536398468
17396.6343.171713601533312.38262530.789088601532653.4282863984675
18438.8279.699352969349310.098-30.3986470306514159.100647030651
19395.6306.773749521073322.473-15.699250478927288.8262504789272
20363.5312.476795498084331.8355-19.358704501915751.0232045019157
21378.8272.531778256705337.327166666667-64.7953884099617106.268221743295
220.357333.591921934866337.889666666667-4.29774473180077-333.234921934866
230.369280.542042624521335.106333333333-54.5642907088123-280.173042624521
24464.8399.536726532567328.910570.62622653256765.263273467433
25479.1380.178082854406318.84861.330082854406198.9219171455938
26431.3368.060636015326298.11670833333369.943927681992363.2393639846744
27366.5247.264378831418275.760416666667-28.4960378352490119.235621168582
28326.3263.26211302682278.341375-15.079261973180163.0378869731801
29355.1328.954380268199298.16529166666730.789088601532626.1456197318008
30331.6269.459602969349299.85825-30.398647030651462.1403970306514
31261.3266.442332854406282.141583333333-15.6992504789272-5.14233285440611
320.249245.103712164751264.462416666667-19.3587045019157-244.854712164751
33205.5184.179528256705248.974916666667-64.795388409961721.320471743295
34235.6223.892880268199228.190625-4.2977447318007711.7071197318008
35240.9154.125375957854208.689666666667-54.564290708812386.7746240421456
36264.9268.220059865900197.59383333333370.626226532567-3.32005986590039
37253.8250.378082854406189.04861.33008285440613.42191714559394
38232.3263.477386015326193.53345833333369.9439276819923-31.1773860153256
39193.8171.631212164751200.12725-28.496037835249022.1687878352491
400.177173.985446360153189.064708333333-15.0792619731801-173.808446360153
41213.2207.491255268199176.70216666666730.78908860153265.70874473180078
42207.2142.120186302682172.518833333333-30.398647030651465.079813697318
43180.6144.625166187739160.324416666667-15.699250478927235.9748338122605
44188.6129.062962164751148.421666666667-19.358704501915759.537037835249
45175.481.863778256705146.659166666667-64.795388409961793.536221743295
460.199149.354046934866153.651791666667-4.29774473180077-149.155046934866
47179.6106.088459291188160.65275-54.564290708812373.5115407088123
48225.8230.916476532567160.2902570.626226532567-5.11647653256702
490.234222.141166187739160.81108333333361.3300828544061-221.907166187739
50200.2230.563344348659160.61941666666769.9439276819923-30.363344348659
51183.6124.162878831418152.658916666667-28.496037835249059.4371211685824
52178.2136.91086302682151.990125-15.079261973180141.2891369731801
53203.2188.366755268199157.57766666666730.789088601532614.8332447318008
54208.5125.608186302682156.006833333333-30.398647030651482.891813697318
55191.8147.956166187739163.655416666667-15.699250478927243.8438338122605
56172.8151.745295498084171.104-19.358704501915721.0547045019157
570.148105.283611590038170.079-64.7953884099617-105.135611590038
58159.4164.456255268199168.754-4.29774473180077-5.05625526819924
59154.5111.914709291188166.479-54.564290708812342.5852907088122
60213.2227.174851532567156.54862570.626226532567-13.9748515325671
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62182.8213.974677681992144.0307569.9439276819923-31.1746776819923
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64153.6143.34748802682158.42675-15.079261973180110.2525119731801
65173.2194.390838601533163.6017530.7890886015326-21.1908386015326
660.171142.569769636015172.968416666667-30.3986470306514-142.398769636015
67151.2171.635832854406187.335083333333-15.6992504789272-20.4358328544062
68161.9185.593045498084204.95175-19.3587045019157-23.6930454980843
69157.2158.035528256705222.830916666667-64.7953884099617-0.835528256705004
70201.7236.049838601533240.347583333333-4.29774473180077-34.3498386015326
71236.4202.745792624521257.310083333333-54.564290708812333.6542073754790
72356.1351.3791848659280.75295833333370.6262265325674.72081513409967
73398.3351.119541187740289.78945833333361.330082854406147.1804588122605
74403.7361.006177681992291.0622569.943927681992342.6938223180077
75384.6275.778712164751304.27475-28.4960378352490108.821287835249
76365.8299.424654693487314.503916666667-15.079261973180166.3753453065135
77368.1352.555505268199321.76641666666730.789088601532615.5444947318008
78367.9294.505269636015324.903916666667-30.398647030651473.3947303639847
790.347307.929666187739323.628916666667-15.6992504789272-307.582666187740
80343.3299.461878831418318.820583333333-19.358704501915743.8381211685823
81292.9248.091861590038312.88725-64.795388409961744.8081384099617
82311.5290.509046934866294.806791666667-4.2977447318007720.9909530651341
83300.9221.728709291188276.293-54.564290708812379.1712907088123
84366.9339.398393199234268.77216666666770.62622653256727.5016068007662
85356.9336.416957854406275.08687561.330082854406120.4830421455939
86329.7351.020511015326281.07658333333369.9439276819923-21.3205110153257
87316.2245.330545498084273.826583333333-28.496037835249070.8694545019158
880.269253.647321360153268.726583333333-15.0792619731801-253.378321360153
89289.3295.403171934866264.61408333333330.7890886015326-6.10317193486588
90266.2230.002936302682260.401583333333-30.398647030651436.197063697318
91253.6240.202332854406255.901583333333-15.699250478927213.3976671455939
92233.8233.713712164751253.072416666667-19.35870450191570.0862878352490668
93228.4174.271653256705239.067041666667-64.795388409961754.1283467432951
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990.271223.855712164751252.35175-28.4960378352490-223.584712164751
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101317.9272.035255268199241.24616666666730.789088601532645.8647447318008
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105209.1175.392236590038240.187625-64.795388409961733.7077634099617
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110282.2319.574427681992249.630569.9439276819923-37.3744276819924
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112263.5240.82623802682255.9055-15.079261973180122.6737619731801
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122515.5501.306427681992431.362569.943927681992314.1935723180077
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125522.3456.670338601532425.8812530.789088601532665.6296613984675
126509.8399.440936302682429.839583333333-30.3986470306514110.359063697318
127460.7413.290332854406428.989583333333-15.699250478927247.4096671455939
128405.8404.318378831418423.677083333333-19.35870450191571.48162116858242
1290.375349.035861590038413.83125-64.7953884099617-348.660861590038
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131406.8318.703542624521373.267833333333-54.564290708812388.096457375479
132467.8415.926476532567345.3002570.62622653256751.873523467433
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177323.4262.393194923372327.188583333333-64.795388409961761.0068050766283
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195383.1358.553962164751387.05-28.496037835249024.5460378352491
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197445.3410.943255268199380.15416666666730.789088601532634.3567447318007
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200326.2349.807962164751369.166666666667-19.3587045019157-23.6079621647510
201319.8300.767111590038365.5625-64.795388409961719.0328884099617
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205417.2415.905082854406354.57561.33008285440611.2949171455939
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207349.2318.933128831418347.429166666667-28.496037835249030.2668711685824
208321.4328.52073802682343.6-15.0792619731801-7.12073802681988
209405.7370.009921934866339.22083333333330.789088601532635.6900780651341
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361673.9NA578.149NANA
362647.9NA572.040666666667NANA
363568.8NA543.475916666667NANA
364545.7NA514.590333333333NANA
365632.6NA535.4325NANA
366643.8NANANANA
367593.1NANANANA
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3690.546NANANANA
370562.9NANANANA
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Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/1b3bc1291826874.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/1b3bc1291826874.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/2b3bc1291826874.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/2b3bc1291826874.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/3mb9f1291826874.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/3mb9f1291826874.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/4mb9f1291826874.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/08/t1291826782zw6sb7d4y1eqqdx/4mb9f1291826874.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')
 





Copyright

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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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