Home » date » 2010 » Dec » 21 »

*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: Tue, 21 Dec 2010 18:00:25 +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/21/t1292954324z3lgefihh16oxal.htm/, Retrieved Tue, 21 Dec 2010 18:58:45 +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/21/t1292954324z3lgefihh16oxal.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 «
320 324 343 295 301 367 196 182 342 361 333 330 345 323 365 323 316 358 235 169 430 409 407 341 326 374 364 349 300 385 304 196 443 414 325 388 356 386 444 387 327 448 225 182 460 411 342 361 377 331 428 340 352 461 221 198 422 329 320 375 364 351 380 319 322 386 221 187 343 342 365 313 356 337 389 326 343 357 220 218 391 425 332 298 360 336 325 393 301 426 265 210 429 440 357 431 442 422 544 420 396 482 261 211 448 468 464 425
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1320NANA18.0177951388889NA
2324NANA9.27821180555556NA
3343NANA55.9500868055555NA
4295NANA7.09071180555556NA
5301NANA-19.1488715277778NA
6367NANA60.4240451388889NA
7196204.595920138889308.875-104.279079861111-8.59592013888886
8182161.325086805556309.875-148.54991319444420.6749131944445
9342375.392795138889310.7564.6427951388889-33.3927951388889
10361359.653211805556312.83333333333346.81987847222231.3467881944444
11333316.549045138889314.6251.9240451388888916.4509548611111
12330322.705295138889314.8757.83029513888897.29470486111109
13345334.142795138889316.12518.017795138888910.8572048611111
14323326.486545138889317.2083333333339.27821180555556-3.4865451388888
15365376.283420138889320.33333333333355.9500868055555-11.2834201388889
16323333.0907118055553267.09071180555556-10.0907118055555
17316311.934461805556331.083333333333-19.14887152777784.06553819444446
18358395.049045138889334.62560.4240451388889-37.0490451388889
19235230.012586805556334.291666666667-104.2790798611114.9874131944444
20169187.075086805556335.625-148.549913194444-18.0750868055555
21430402.351128472222337.70833333333364.642795138888927.6488715277778
22409385.569878472222338.7546.819878472222323.4301215277778
23407341.090711805555339.1666666666671.9240451388888965.9092881944445
24341347.455295138889339.6257.8302951388889-6.45529513888886
25326361.642795138889343.62518.0177951388889-35.6427951388889
26374356.903211805555347.6259.2782118055555617.0967881944445
27364405.241753472222349.29166666666755.9500868055555-41.2417534722222
28349357.132378472222350.0416666666677.09071180555556-8.13237847222229
29300327.684461805556346.833333333333-19.1488715277778-27.6844618055556
30385405.799045138889345.37560.4240451388889-20.7990451388889
31304244.304253472222348.583333333333-104.27907986111159.6957465277778
32196201.783420138889350.333333333333-148.549913194444-5.7834201388888
33443418.809461805556354.16666666666764.642795138888924.1905381944444
34414405.903211805556359.08333333333346.81987847222238.09678819444446
35325363.715711805555361.7916666666671.92404513888889-38.7157118055555
36388373.371961805556365.5416666666677.830295138888914.6280381944445
37356382.892795138889364.87518.0177951388889-26.8927951388889
38386370.2782118055563619.2782118055555615.7217881944445
39444417.075086805555361.12555.950086805555526.9249131944445
40387368.799045138889361.7083333333337.0907118055555618.2009548611112
41327343.142795138889362.291666666667-19.1488715277778-16.1427951388889
42448422.299045138889361.87560.424045138888925.7009548611111
43225257.345920138889361.625-104.279079861111-32.3459201388889
44182211.658420138889360.208333333333-148.549913194444-29.6584201388889
45460421.892795138889357.2564.642795138888938.1072048611111
46411401.444878472222354.62546.81987847222239.55512152777777
47342355.632378472222353.7083333333331.92404513888889-13.6323784722222
48361363.121961805556355.2916666666677.8302951388889-2.1219618055556
49377373.684461805556355.66666666666718.01779513888893.31553819444446
50331365.444878472222356.1666666666679.27821180555556-34.4448784722222
51428411.200086805556355.2555.950086805555516.7999131944445
52340357.340711805556350.257.09071180555556-17.3407118055555
53352326.767795138889345.916666666667-19.148871527777825.2322048611111
54461406.007378472222345.58333333333360.424045138888954.9926215277778
55221241.345920138889345.625-104.279079861111-20.3459201388888
56198197.366753472222345.916666666667-148.5499131944440.633246527777828
57422409.392795138889344.7564.642795138888912.6072048611112
58329388.694878472222341.87546.8198784722223-59.6948784722223
59320341.674045138889339.751.92404513888889-21.674045138889
60375343.205295138889335.3757.830295138888931.7947048611111
61364350.267795138889332.2518.017795138888913.7322048611111
62351341.069878472222331.7916666666679.278211805555569.93012152777777
63380383.991753472222328.04166666666755.9500868055555-3.99175347222223
64319332.382378472222325.2916666666677.09071180555556-13.3823784722222
65322308.559461805556327.708333333333-19.148871527777813.4405381944445
66386387.42404513888932760.4240451388889-1.4240451388888
67221219.804253472222324.083333333333-104.2790798611111.19574652777777
68187174.616753472222323.166666666667-148.54991319444412.3832465277778
69343387.601128472222322.95833333333364.6427951388889-44.6011284722222
70342370.444878472222323.62546.8198784722223-28.4448784722223
71365326.715711805556324.7916666666671.9240451388888938.2842881944443
72313332.288628472222324.4583333333337.8302951388889-19.2886284722222
73356341.226128472222323.20833333333318.017795138888914.7738715277778
74337333.736545138889324.4583333333339.278211805555563.26345486111114
75389383.700086805556327.7555.95008680555555.29991319444446
76326340.299045138889333.2083333333337.09071180555556-14.2990451388889
77343316.142795138889335.291666666667-19.148871527777826.8572048611111
78357393.715711805556333.29166666666760.4240451388889-36.7157118055555
79220228.554253472222332.833333333333-104.279079861111-8.55425347222217
80218184.408420138889332.958333333333-148.54991319444433.5915798611111
81391394.892795138889330.2564.6427951388889-3.89279513888886
82425377.194878472222330.37546.819878472222347.8051215277778
83332333.340711805556331.4166666666671.92404513888889-1.3407118055556
84298340.371961805556332.5416666666677.8302951388889-42.3719618055555
85360355.309461805556337.29166666666718.01779513888894.6905381944444
86336348.111545138889338.8333333333339.27821180555556-12.1115451388889
87325396.033420138889340.08333333333355.9500868055555-71.0334201388889
88393349.382378472222342.2916666666677.0907118055555643.6176215277778
89301324.809461805556343.958333333333-19.1488715277778-23.8094618055555
90426410.965711805556350.54166666666760.424045138888915.0342881944445
91265255.220920138889359.5-104.2790798611119.77907986111114
92210217.950086805555366.5-148.549913194444-7.95008680555549
93429443.851128472222379.20833333333364.6427951388889-14.8511284722222
94440436.278211805556389.45833333333346.81987847222233.72178819444446
95357396.465711805556394.5416666666671.92404513888889-39.4657118055555
96431408.663628472222400.8333333333337.830295138888922.3363715277778
97442421.01779513888940318.017795138888920.982204861111
98422412.153211805556402.8759.278211805555569.84678819444446
99544459.658420138889403.70833333333355.950086805555584.3415798611111
100420412.757378472222405.6666666666677.090711805555567.24262152777783
101396392.142795138889411.291666666667-19.14887152777783.85720486111109
102482475.924045138889415.560.42404513888896.0759548611112
103261NANA-104.279079861111NA
104211NANA-148.549913194444NA
105448NANA64.6427951388889NA
106468NANA46.8198784722223NA
107464NANA1.92404513888889NA
108425NANA7.8302951388889NA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/1bu1r1292954420.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/1bu1r1292954420.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/24l0c1292954420.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/24l0c1292954420.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/34l0c1292954420.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/34l0c1292954420.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/4xvhx1292954420.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/21/t1292954324z3lgefihh16oxal/4xvhx1292954420.ps (open in new window)


 
Parameters (Session):
par2 = blue ; par3 = FALSE ; par4 = Unknown ;
 
Parameters (R input):
par1 = additive ; par2 = 12 ; par3 = FALSE ; par4 = Unknown ;
 
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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