Home » date » 2008 » Aug » 12 »

Multiplicatief model - Vanessa Limbourg 2MAR04b

R Software Module: rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Tue, 12 Aug 2008 07:06:41 -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/Aug/12/t1218546472qq0hs7kcjkoo7gt.htm/, Retrieved Tue, 12 Aug 2008 13:07:52 +0000
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
118 132 129 121 135 148 148 136 119 104 118 115 126 141 135 125 149 170 170 158 133 114 140 145 150 178 163 172 178 199 199 184 162 146 166 171 180 193 181 183 218 230 242 209 191 172 194 196 196 236 235 229 243 264 272 237 211 180 201 204 188 235 227 234 264 302 293 259 229 203 229 242 233 267 269 270 315 364 347 312 274 237 278 284 277 317 313 318 374 413 405 355 306 271 306 315 301 356 348 355 422 465 467 404 347 305 336 340 318 362 348 363 435 491 505 404 359 310 337 360 342 406 396 420 472 548 559 463 407 362 405 417 391 419 461 472 535 622 606 508 461 390 432
 
Text written by user:
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1118NANA0.890966652042943NA
2132NANA1.01988324517290NA
3129NANA0.976259257200634NA
4121NANA0.975844274865206NA
5135NANA1.10973973286267NA
6148NANA1.22593071680468NA
7148154.852215059347127.251.216913281409400.95574997066254
8136135.468457504385127.9583333333331.058691950538991.00392373623652
9119118.246347415215128.5833333333330.9196086642790561.00637358025224
10104102.9460200272961290.7980311630022981.01023818086823
11118116.268093718615129.750.8960932078505981.01489580009436
12115119.704968333643131.250.9120378539706150.960695296117288
13126118.572811942715133.0833333333330.8909666520429431.06263820462378
14141137.599247827911134.9166666666671.019883245172901.02471490379324
15135133.178033669786136.4166666666670.9762592572006341.01368068201646
16125134.097267437727137.4166666666670.9758442748652060.932159188538635
17149153.976387934696138.751.109739732862670.967680837293012
18170172.754070176393140.9166666666671.225930716804680.98405785650329
19170174.221418121780143.1666666666671.216913281409400.975769809663534
20158154.260239626452145.7083333333331.058691950538991.02424319048514
21133136.485252590083148.4166666666670.9196086642790560.974464255119557
22114120.934972493307151.5416666666670.7980311630022980.942655359733179
23140138.633086697886154.7083333333330.8960932078505981.00985993556569
24145143.303947805133157.1250.9120378539706151.01183534871749
25150142.146304611351159.5416666666670.8909666520429431.05525078833475
26178165.051105177148161.8333333333331.019883245172901.07845385105997
27163160.228550588054164.1250.9762592572006341.01729685129008
28172162.640712477534166.6666666666670.9758442748652061.05754578530734
29178187.638493164863169.0833333333331.109739732862670.948632644601368
30199209.940635252801171.251.225930716804680.947887005106815
31199211.235863764649173.5833333333331.216913281409400.942074875229133
32184185.756325154987175.4583333333331.058691950538990.990545004841576
33162162.617465466680176.8333333333330.9196086642790560.996202957259802
34146142.082798312868178.0416666666670.7980311630022981.02756985176001
35166161.446126281083180.1666666666670.8960932078505981.02820676979879
36171167.016932008369183.1250.9120378539706151.02384828857610
37180165.905415332496186.2083333333330.8909666520429431.08495554312833
38193192.800428472894189.0416666666671.019883245172901.00103511972814
39181186.750260408671191.2916666666670.9762592572006340.969208822541464
40183188.907187542656193.5833333333330.9758442748652060.96872968350491
41218217.32403101894195.8333333333331.109739732862671.00311041985505
42230242.78536237386198.0416666666671.225930716804680.947338825335887
43242243.078427961529199.751.216913281409400.995563456738748
44209214.076334831905202.2083333333331.058691950538990.97628726764268
45191189.669287007555206.250.9196086642790561.00701596454249
46172167.919057215067210.4166666666670.7980311630022981.02430303535891
47194191.203888225121213.3750.8960932078505981.01462371817244
48196196.848170148658215.8333333333330.9120378539706150.995691246974675
49196194.676213471383218.50.8909666520429431.00679993978212
50236225.309206912781220.9166666666671.019883245172901.04744942842641
51235217.624459417641222.9166666666670.9762592572006341.07984185522554
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54264276.243054853321225.3333333333331.225930716804680.955680135162776
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56237238.161576706667224.9583333333331.058691950538990.99512273674566
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58180179.124744795558224.4583333333330.7980311630022981.00488628863333
59201202.106355587304225.5416666666670.8960932078505980.994525874339336
60204207.9446307053002280.9120378539706150.981030379616338
61188205.330689685396230.4583333333330.8909666520429430.915596203802022
62235236.867883691407232.251.019883245172900.992114238273684
63227228.363311246848233.9166666666670.9762592572006340.994030077601325
64234229.933307265114235.6250.9758442748652061.01768640125807
65264263.8406214881237.751.109739732862671.00060407116615
66302294.836337391525240.51.225930716804681.02429708180428
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69229230.132068235834250.250.9196086642790560.995080788850889
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71229230.407966068585257.1250.8960932078505980.993889247439622
72242238.801911431306261.8333333333330.9120378539706151.01339222349405
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76270271.77263054996278.50.9758442748652060.993477523669794
77315312.900365511737281.9583333333331.109739732862671.00671023341513
78364350.309702326937285.751.225930716804681.03908055524048
79347352.093576087788289.3333333333331.216913281409400.985533459188935
80312310.461414495559293.251.058691950538991.00495580266212
81274273.277041401593297.1666666666670.9196086642790561.00264551531552
82237240.2073800636923010.7980311630022980.986647454117183
83278273.719137781364305.4583333333330.8960932078505981.01563961604342
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85277280.134764846502314.4166666666670.8909666520429430.98880979714096
86317324.960298993217318.6251.019883245172900.975503779945184
87313314.111416004304321.750.9762592572006340.996461714068079
88318316.661467193759324.50.9758442748652061.00422701510892
89374362.977370957166327.0833333333331.109739732862671.03036726232759
90413403.995251633675329.5416666666671.225930716804681.02228924307875
91405403.812390547687331.8333333333331.216913281409401.00294099309509
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93306310.406241221860337.5416666666670.9196086642790560.985804920659729
94271271.762862300741340.5416666666670.7980311630022980.997192911885448
95306308.330737934593344.0833333333330.8960932078505980.992440786312107
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97301314.5112281711593530.8909666520429430.957040553846918
98356364.73574555496357.6251.019883245172900.976049110454836
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100355355.695238188368364.50.9758442748652060.998045410470186
101422407.459438582744367.1666666666671.109739732862671.03568591138257
102465452.930319412795369.4583333333331.225930716804681.02664798550658
103467451.728351003183371.2083333333331.216913281409401.03380715193745
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105347342.477593388592372.4166666666670.9196086642790561.01320497077389
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110362387.045691543117379.51.019883245172900.935290090833301
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112363371.512047476808380.7083333333330.9758442748652060.977088098395142
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114491468.101212033253381.8333333333331.225930716804681.04891845476598
115505466.889062300742383.6666666666671.216913281409401.08162739454948
116404409.18443888332386.51.058691950538990.987329823935953
117359358.953915290258390.3333333333330.9196086642790561.00012838614591
118310314.989550296699394.7083333333330.7980311630022980.984159632305265
119337357.205154979445398.6250.8960932078505980.943435432838007
120360367.133237800421402.5416666666670.9120378539706150.98057043856024
121342362.771921823485407.1666666666670.8909666520429430.942741098266167
122406420.06441160559411.8751.019883245172900.96651844046528
123396406.449270747864416.3333333333330.9762592572006340.974291328586623
124420410.342517580819420.50.9758442748652061.02353517367909
125472472.194256333067425.51.109739732862670.99958860928429
126548528.018575817082430.7083333333331.225930716804681.03784227506011
127559529.509391573267435.1251.216913281409401.05569421221994
128463463.398289183837437.7083333333331.058691950538990.999140503551408
129407405.509103919385440.9583333333330.9196086642790561.00367660322840
130362355.788893505191445.8333333333330.7980311630022981.0174572804497
131405403.802001787676450.6250.8960932078505981.00296679612043
132417416.193274028591456.3333333333330.9120378539706151.00193834456670
133391NA461.375NANA
134419NA465.208333333333NANA
135461NA469.333333333333NANA
136472NA472.75NANA
137535NA475.041666666667NANA
138622NANANANA
139606NANANANA
140508NANANANA
141461NANANANA
142390NANANANA
143432NANANANA
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/1s7fa1218546396.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/1s7fa1218546396.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/2cfav1218546396.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/2cfav1218546396.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/3mpva1218546396.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/3mpva1218546396.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/4i1ul1218546396.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Aug/12/t1218546472qq0hs7kcjkoo7gt/4i1ul1218546396.ps (open in new window)


 
Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
 
Parameters (R input):
par1 = multiplicative ; 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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