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R Software Module: /rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Wed, 13 Jan 2010 07:10:20 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi.htm/, Retrieved Wed, 13 Jan 2010 15:20:43 +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/Jan/13/t1263392437dix72nj5voa4ywi.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:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

23,98 24,24 24,92 25,46 25,84 26,08 26,18 26,34 26,42 26,38 26,04 25,58 25,65 25,56 25,62 25,62 25,69 25,68 25,68 25,83 25,93 26,11 24,72 24,62 24,65 25,24 25,56 25,9 25,87 25,78 25,78 25,74 25,78 25,73 24,67 24,31 24,56 25 25,38 25,99 26,22 26,19 26,22 26,22 26,61 26,72 25,46 25,48 25,59 25,88 26 26,97 27,2 27,19 27,19 27,19 27,26 26,9 26,11 25,87 26,02 26,31 26,37 26,52 26,86 26,92 26,98 26,98 27,03 26,75 26,39 26,3 26,3 26,52 26,53 26,98 27,22 27,34 27,41 27,47 27,46 27,53 27,21 26,91 26,95 26,91 27,39 27,62 27,79 27,88 27,9 28,09 28,46 28,73 27,93 27,61 27,65 28,19 28,98 28,99 29,02 29 29,04 29,19 29,23 29,26 29,02 28,47 28,53 28,48 28,68 28,89 29,2 29,21 29,15 29,22 29,34 29,13 28,84 28,76

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	23.98	NA	NA	-0.612912808641977	NA
2	24.24	NA	NA	-0.396662808641977	NA
3	24.92	NA	NA	-0.154625771604939	NA
4	25.46	NA	NA	0.149124228395063	NA
5	25.84	NA	NA	0.300096450617284	NA
6	26.08	NA	NA	0.285744598765433	NA
7	26.18	25.9990779320988	25.69125	0.307827932098767	0.180922067901232
8	26.34	26.1574112654321	25.8158333333333	0.341577932098766	0.182588734567904
9	26.42	26.3300964506173	25.9	0.430096450617286	0.0899035493827256
10	26.38	26.3248649691358	25.9358333333333	0.389031635802468	0.0551350308642
11	26.04	25.5649575617284	25.93625	-0.371292438271605	0.475042438271604
12	25.58	25.2453279320988	25.9133333333333	-0.668005401234569	0.334672067901234
13	25.65	25.2629205246914	25.8758333333333	-0.612912808641977	0.387079475308642
14	25.56	25.4370871913580	25.83375	-0.396662808641977	0.122912808641974
15	25.62	25.6374575617284	25.7920833333333	-0.154625771604939	-0.0174575617283956
16	25.62	25.9095408950617	25.7604166666667	0.149124228395063	-0.289540895061723
17	25.69	25.9942631172839	25.6941666666667	0.300096450617284	-0.304263117283945
18	25.68	25.8849112654321	25.5991666666667	0.285744598765433	-0.204911265432099
19	25.68	25.8253279320988	25.5175	0.307827932098767	-0.145327932098763
20	25.83	25.8040779320988	25.4625	0.341577932098766	0.0259220679012380
21	25.93	25.8767631172839	25.4466666666667	0.430096450617286	0.0532368827160532
22	26.11	25.8448649691358	25.4558333333333	0.389031635802468	0.265135030864201
23	24.72	25.1037075617284	25.475	-0.371292438271605	-0.383707561728393
24	24.62	24.8186612654321	25.4866666666667	-0.668005401234569	-0.198661265432094
25	24.65	24.8820871913580	25.495	-0.612912808641977	-0.232087191358023
26	25.24	25.0987538580247	25.4954166666667	-0.396662808641977	0.141246141975312
27	25.56	25.3307908950617	25.4854166666667	-0.154625771604939	0.229209104938271
28	25.9	25.6124575617284	25.4633333333333	0.149124228395063	0.287542438271604
29	25.87	25.7455131172840	25.4454166666667	0.300096450617284	0.124486882716049
30	25.78	25.7161612654321	25.4304166666667	0.285744598765433	0.0638387345679021
31	25.78	25.7215779320988	25.41375	0.307827932098767	0.0584220679012404
32	25.74	25.7415779320988	25.4	0.341577932098766	-0.00157793209876544
33	25.78	25.8125964506173	25.3825	0.430096450617286	-0.0325964506172873
34	25.73	25.7677816358025	25.37875	0.389031635802468	-0.0377816358024639
35	24.67	25.0257908950617	25.3970833333333	-0.371292438271605	-0.355790895061723
36	24.31	24.7607445987654	25.42875	-0.668005401234569	-0.450744598765432
37	24.56	24.8512538580247	25.4641666666667	-0.612912808641977	-0.291253858024692
38	25	25.105837191358	25.5025	-0.396662808641977	-0.105837191358020
39	25.38	25.4024575617284	25.5570833333333	-0.154625771604939	-0.0224575617283946
40	25.99	25.7820408950617	25.6329166666667	0.149124228395063	0.207959104938276
41	26.22	26.0071797839506	25.7070833333333	0.300096450617284	0.212820216049387
42	26.19	26.0744945987654	25.78875	0.285744598765433	0.115505401234575
43	26.22	26.1882445987654	25.8804166666667	0.307827932098767	0.0317554012345731
44	26.22	26.3015779320988	25.96	0.341577932098766	-0.0815779320987602
45	26.61	26.4525964506173	26.0225	0.430096450617286	0.157403549382721
46	26.72	26.4781983024691	26.0891666666667	0.389031635802468	0.241801697530871
47	25.46	25.7995408950617	26.1708333333333	-0.371292438271605	-0.339540895061724
48	25.48	25.5853279320988	26.2533333333333	-0.668005401234569	-0.105327932098760
49	25.59	25.7225038580247	26.3354166666667	-0.612912808641977	-0.132503858024691
50	25.88	26.0195871913580	26.41625	-0.396662808641977	-0.139587191358025
51	26	26.3291242283951	26.48375	-0.154625771604939	-0.329124228395060
52	26.97	26.6674575617284	26.5183333333333	0.149124228395063	0.302542438271605
53	27.2	26.8530131172840	26.5529166666667	0.300096450617284	0.346986882716045
54	27.19	26.8819945987654	26.59625	0.285744598765433	0.308005401234571
55	27.19	26.9382445987654	26.6304166666667	0.307827932098767	0.251755401234568
56	27.19	27.0078279320988	26.66625	0.341577932098766	0.182172067901238
57	27.26	27.1296797839506	26.6995833333333	0.430096450617286	0.130320216049387
58	26.9	27.0852816358025	26.69625	0.389031635802468	-0.185281635802468
59	26.11	26.2920408950617	26.6633333333333	-0.371292438271605	-0.182040895061728
60	25.87	25.9699112654321	26.6379166666667	-0.668005401234569	-0.0999112654320982
61	26.02	26.0050038580247	26.6179166666667	-0.612912808641977	0.0149961419753097
62	26.31	26.2037538580247	26.6004166666667	-0.396662808641977	0.106246141975308
63	26.37	26.4274575617284	26.5820833333333	-0.154625771604939	-0.0574575617283948
64	26.52	26.7153742283951	26.56625	0.149124228395063	-0.195374228395060
65	26.86	26.8717631172840	26.5716666666667	0.300096450617284	-0.0117631172839516
66	26.92	26.8869945987654	26.60125	0.285744598765433	0.0330054012345684
67	26.98	26.9386612654321	26.6308333333333	0.307827932098767	0.0413387345679048
68	26.98	26.9928279320988	26.65125	0.341577932098766	-0.0128279320987659
69	27.03	27.0967631172839	26.6666666666667	0.430096450617286	-0.0667631172839478
70	26.75	27.0815316358025	26.6925	0.389031635802468	-0.33153163580247
71	26.39	26.3553742283951	26.7266666666667	-0.371292438271605	0.0346257716049401
72	26.3	26.0911612654321	26.7591666666667	-0.668005401234569	0.208838734567902
73	26.3	26.1816705246914	26.7945833333333	-0.612912808641977	0.118329475308641
74	26.52	26.4362538580247	26.8329166666667	-0.396662808641977	0.0837461419753076
75	26.53	26.7166242283951	26.87125	-0.154625771604939	-0.186624228395061
76	26.98	27.0707908950617	26.9216666666667	0.149124228395063	-0.0907908950617262
77	27.22	27.2884297839506	26.9883333333333	0.300096450617284	-0.0684297839506165
78	27.34	27.3336612654321	27.0479166666667	0.285744598765433	0.00633873456790113
79	27.41	27.4082445987654	27.1004166666667	0.307827932098767	0.00175540123456486
80	27.47	27.4853279320988	27.14375	0.341577932098766	-0.0153279320987671
81	27.46	27.6259297839506	27.1958333333333	0.430096450617286	-0.16592978395062
82	27.53	27.6473649691358	27.2583333333333	0.389031635802468	-0.117364969135803
83	27.21	26.9374575617284	27.30875	-0.371292438271605	0.272542438271607
84	26.91	26.6869945987654	27.355	-0.668005401234569	0.223005401234566
85	26.95	26.7850038580247	27.3979166666667	-0.612912808641977	0.164996141975312
86	26.91	27.0475038580247	27.4441666666667	-0.396662808641977	-0.137503858024683
87	27.39	27.3570408950617	27.5116666666667	-0.154625771604939	0.0329591049382749
88	27.62	27.7524575617284	27.6033333333333	0.149124228395063	-0.132457561728394
89	27.79	27.9834297839506	27.6833333333333	0.300096450617284	-0.193429783950616
90	27.88	28.0282445987654	27.7425	0.285744598765433	-0.148244598765430
91	27.9	28.1086612654321	27.8008333333333	0.307827932098767	-0.208661265432099
92	28.09	28.2249112654321	27.8833333333333	0.341577932098766	-0.134911265432095
93	28.46	28.4330131172839	28.0029166666667	0.430096450617286	0.0269868827160522
94	28.73	28.5152816358025	28.12625	0.389031635802468	0.214718364197530
95	27.93	27.8632908950617	28.2345833333333	-0.371292438271605	0.0667091049382762
96	27.61	27.6644945987654	28.3325	-0.668005401234569	-0.0544945987654266
97	27.65	27.8137538580247	28.4266666666667	-0.612912808641977	-0.163753858024691
98	28.19	28.123337191358	28.52	-0.396662808641977	0.0666628086419792
99	28.98	28.4432908950617	28.5979166666667	-0.154625771604939	0.536709104938272
100	28.99	28.8012075617284	28.6520833333333	0.149124228395063	0.188792438271605
101	29.02	29.0196797839506	28.7195833333333	0.300096450617284	0.000320216049384925
102	29	29.0865779320988	28.8008333333333	0.285744598765433	-0.0865779320987627
103	29.04	29.1811612654321	28.8733333333333	0.307827932098767	-0.141161265432096
104	29.19	29.2636612654321	28.9220833333333	0.341577932098766	-0.0736612654320936
105	29.23	29.3517631172839	28.9216666666667	0.430096450617286	-0.121763117283948
106	29.26	29.2940316358025	28.905	0.389031635802468	-0.0340316358024637
107	29.02	28.5370408950617	28.9083333333333	-0.371292438271605	0.482959104938274
108	28.47	28.2565779320988	28.9245833333333	-0.668005401234569	0.213422067901242
109	28.53	28.3250038580247	28.9379166666667	-0.612912808641977	0.204996141975315
110	28.48	28.547087191358	28.94375	-0.396662808641977	-0.06708719135802
111	28.68	28.7949575617284	28.9495833333333	-0.154625771604939	-0.114957561728396
112	28.89	29.0978742283951	28.94875	0.149124228395063	-0.207874228395063
113	29.2	29.2359297839506	28.9358333333333	0.300096450617284	-0.0359297839506212
114	29.21	29.2261612654321	28.9404166666667	0.285744598765433	-0.0161612654320997
115	29.15	NA	NA	0.307827932098767	NA
116	29.22	NA	NA	0.341577932098766	NA
117	29.34	NA	NA	0.430096450617286	NA
118	29.13	NA	NA	0.389031635802468	NA
119	28.84	NA	NA	-0.371292438271605	NA
120	28.76	NA	NA	-0.668005401234569	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/10ypg1263391816.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/10ypg1263391816.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/2boqk1263391816.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/2boqk1263391816.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/3qdeu1263391816.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/3qdeu1263391816.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/491jl1263391816.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/13/t1263392437dix72nj5voa4ywi/491jl1263391816.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')

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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