Home » date » 2010 » May » 24 »

Classical Deomposition eigen reeks

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 24 May 2010 21:03:14 +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/May/24/t127473545807syqus8nz7zxo6.htm/, Retrieved Mon, 24 May 2010 23:11:05 +0200

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/May/24/t127473545807syqus8nz7zxo6.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 «

81.28 69.39 67.63 51.25 103.97 133.83 162.37 172.91 163.01 151.50 111.73 88.58 74.29 63.98 61.18 76.48 107.98 124.97 145.57 140.20 143.84 138.80 104.06 74.70 60.18 55.16 35.62 56.18 85.44 114.08 133.64 67.14 95.58 89.37 75.24 69.18 54.49 57.50 62.16 76.67 110.04 127.38 156.47 167.56 153.54 124.08 100.97 79.17 68.13 61.77 54.31 60.30 84.18 104.05 114.66 105.55 96.61 70.94 63.91 58.61 44.53 49.58 57.39 76.76 104.57 125.41 143.11 136.35 135.15 131.70 96.87 70.63 66.29 63.49 62.97 66.43 101.49 127.69 133.21 158.72 148.61 134.31 100.99 75.16 59.74 52.87 52.07 57.38 79.43 101.40 120.19 134.38 135.97 113.83 84.38 70.28 65.96 56.36 49.57 68.33 90.32 117.06 134.69 131.67 129.25 118.77 88.44 76.79 75.28 73.89 76.24 88.58 105.83 115.84 127.76 131.75 119.63 93.38 75.55 51.79

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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	81.28	NA	NA	0.652943450142838	NA
2	69.39	NA	NA	0.617719131561426	NA
3	67.63	NA	NA	0.591834737709433	NA
4	51.25	NA	NA	0.730889134250637	NA
5	103.97	NA	NA	1.01904371711796	NA
6	133.83	NA	NA	1.25045624547342	NA
7	162.37	162.752017763104	112.829583333333	1.44245873249646	0.997652761739276
8	172.91	155.602709011798	112.312916666667	1.38543912516858	1.11122744004983
9	163.01	154.148736587518	111.81875	1.37855893208892	1.05748515108621
10	151.5	137.752636087019	112.60125	1.22336684616751	1.09979746524993
11	111.73	107.553153133681	113.819583333333	0.944944182572692	1.03883518748286
12	88.58	86.6158199833068	113.6175	0.762345765250131	1.02267691995610
13	74.29	73.4876970744929	112.548333333333	0.652943450142838	1.01091751350833
14	63.98	68.2489556335356	110.485416666667	0.617719131561426	0.937450242367694
15	61.18	64.1097581689522	108.32375	0.591834737709433	0.95430090125701
16	76.48	78.2020919934255	106.995833333333	0.730889134250637	0.977978952358842
17	107.98	108.168518361230	106.147083333333	1.01904371711796	0.99825717903799
18	124.97	131.609477789206	105.249166666667	1.25045624547342	0.949551674387462
19	145.57	150.135312049534	104.082916666667	1.44245873249646	0.969592016779981
20	140.2	142.876873380823	103.1275	1.38543912516858	0.98126447396642
21	143.84	140.192550598782	101.695	1.37855893208892	1.02601742664385
22	138.8	122.072641272453	99.7841666666667	1.22336684616751	1.13702790857300
23	104.06	92.6037424386384	97.9991666666667	0.944944182572692	1.12371268438695
24	74.7	73.6473655841955	96.60625	0.762345765250131	1.01429289978609
25	60.18	62.4575777831841	95.6554166666667	0.652943450142838	0.963534003974818
26	55.16	56.9006830378378	92.1141666666667	0.617719131561426	0.969408398196551
27	35.62	51.5246390693685	87.0591666666667	0.591834737709433	0.691319738349728
28	56.18	60.6555756400425	82.98875	0.730889134250637	0.926213285541916
29	85.44	81.2466571596196	79.7283333333333	1.01904371711796	1.05161249689501
30	114.08	97.9075978799549	78.2975	1.25045624547342	1.16518025638699
31	133.64	112.267164174671	77.8304166666667	1.44245873249646	1.19037477237847
32	67.14	107.635920166951	77.6908333333333	1.38543912516858	0.623769461866083
33	95.58	108.760258148045	78.8941666666667	1.37855893208892	0.878813655167093
34	89.37	98.9137971383164	80.85375	1.22336684616751	0.903513994867968
35	75.24	78.1775945846953	82.7325	0.944944182572692	0.96242408582279
36	69.18	64.274642044514	84.3116666666667	0.762345765250131	1.07631871293953
37	54.49	56.0337024728621	85.8170833333333	0.652943450142838	0.972450464546586
38	57.5	56.1830993133406	90.9525	0.617719131561426	1.02343944536265
39	62.16	57.7344650547847	97.5516666666667	0.591834737709433	1.07665325972997
40	76.67	74.121598864332	101.412916666667	0.730889134250637	1.03438135678013
41	110.04	105.910487324716	103.93125	1.01904371711796	1.03899059271272
42	127.38	131.822576374372	105.419583333333	1.25045624547342	0.96629882000064
43	156.47	153.483619382342	106.404166666667	1.44245873249646	1.01945732469482
44	167.56	148.450379528116	107.150416666667	1.38543912516858	1.12872732648194
45	153.54	147.507528932179	107.00125	1.37855893208892	1.04089602145389
46	124.08	129.667200706224	105.992083333333	1.22336684616751	0.95691122600169
47	100.97	98.4938945100081	104.2325	0.944944182572692	1.02513968507703
48	79.17	77.8987138017404	102.182916666667	0.762345765250131	1.01631973284559
49	68.13	64.9474688063955	99.46875	0.652943450142838	1.04900162011073
50	61.77	58.7715998575545	95.1429166666667	0.617719131561426	1.05101784109524
51	54.31	53.3758488093621	90.1870833333333	0.591834737709433	1.01750138333115
52	60.3	62.564718966133	85.6008333333333	0.730889134250637	0.963801979717051
53	84.18	83.4010854182265	81.8425	1.01904371711796	1.00933938183020
54	104.05	99.3383282341507	79.4416666666666	1.25045624547342	1.04743055223099
55	114.66	111.937201739613	77.6016666666667	1.44245873249646	1.02432433737911
56	105.55	105.446349082883	76.1104166666667	1.38543912516858	1.00098297302864
57	96.61	104.399416726204	75.7308333333333	1.37855893208892	0.925388311827143
58	70.94	93.6426152398921	76.545	1.22336684616751	0.757561072149332
59	63.91	73.7816355020186	78.0804166666667	0.944944182572692	0.866204707514941
60	58.61	60.8504389822655	79.82	0.762345765250131	0.96318121907192
61	44.53	53.4730759092187	81.8954166666667	0.652943450142838	0.832755536180463
62	49.58	52.1133597682367	84.3641666666666	0.617719131561426	0.95138751791281
63	57.39	51.639553647607	87.2533333333333	0.591834737709433	1.11135739847084
64	76.76	66.7965670534443	91.3908333333333	0.730889134250637	1.14916085341009
65	104.57	97.1106202258534	95.2958333333333	1.01904371711796	1.07681322348470
66	125.41	121.506833372652	97.17	1.25045624547342	1.03212302155367
67	143.11	142.193975702670	98.5775	1.44245873249646	1.00644207529049
68	136.35	138.632234261088	100.06375	1.38543912516858	0.983537492032412
69	135.15	139.063281073580	100.875833333333	1.37855893208892	0.971859709886257
70	131.7	123.166025391215	100.677916666667	1.22336684616751	1.06928838193550
71	96.87	94.6070241056925	100.119166666667	0.944944182572692	1.02391974502632
72	70.63	76.3000112031971	100.085833333333	0.762345765250131	0.92568793747491
73	66.29	65.1430797816674	99.7683333333333	0.652943450142838	1.01760617124914
74	63.49	61.949764789438	100.287916666667	0.617719131561426	1.02486264824083
75	62.97	60.2374327996809	101.780833333333	0.591834737709433	1.04536327451746
76	66.43	74.879896341117	102.450416666667	0.730889134250637	0.887154005894675
77	101.49	104.687210262625	102.730833333333	1.01904371711796	0.969459399533098
78	127.69	128.911097416161	103.09125	1.25045624547342	0.990527600488735
79	133.21	148.583466863157	103.007083333333	1.44245873249646	0.896533125873851
80	158.72	141.718877178703	102.291666666667	1.38543912516858	1.11996371379558
81	148.61	139.778982919156	101.395	1.37855893208892	1.06317843281169
82	134.31	123.026357676278	100.56375	1.22336684616751	1.09171727536154
83	100.99	93.8022466435347	99.2675	0.944944182572692	1.07662666528425
84	75.16	74.1403491790572	97.2529166666667	0.762345765250131	1.01375298109913
85	59.74	62.4311879854075	95.615	0.652943450142838	0.956893532347382
86	52.87	58.1016319827818	94.0583333333333	0.617719131561426	0.909957228321363
87	52.07	54.7550703460325	92.5175	0.591834737709433	0.950962160598758
88	57.38	66.6114084727674	91.1375	0.730889134250637	0.861414002729855
89	79.43	91.2982496243418	89.5920833333333	1.01904371711796	0.87000572658101
90	101.4	110.911300786007	88.6966666666667	1.25045624547342	0.91424407865923
91	120.19	128.021818655892	88.7525	1.44245873249646	0.938824344645947
92	134.38	123.521711535916	89.1570833333333	1.38543912516858	1.08790591005474
93	135.97	122.965159144111	89.1983333333333	1.37855893208892	1.10576037103850
94	113.83	109.553010810486	89.5504166666667	1.22336684616751	1.03904036190217
95	84.38	85.4800444822685	90.4604166666667	0.944944182572692	0.987130979061473
96	70.28	69.8054605714037	91.5666666666667	0.762345765250131	1.00679802732783
97	65.96	60.6083875204254	92.8233333333333	0.652943450142838	1.0882982157836
98	56.36	57.642203378683	93.3145833333333	0.617719131561426	0.977755822929608
99	49.57	54.99427021919	92.9216666666667	0.591834737709433	0.901366629694865
100	68.33	67.861228892336	92.8475	0.730889134250637	1.00690778984282
101	90.32	94.9978029190288	93.2225	1.01904371711796	0.950758830464574
102	117.06	117.121379115090	93.6629166666666	1.25045624547342	0.999475935857712
103	134.69	136.056313795897	94.3225	1.44245873249646	0.989957733251932
104	131.67	132.228041904996	95.44125	1.38543912516858	0.995779700758204
105	129.25	134.110233710495	97.2829166666667	1.37855893208892	0.963759412119236
106	118.77	121.404377132734	99.2379166666666	1.22336684616751	0.978300805992736
107	88.44	95.1822588768336	100.727916666667	0.944944182572692	0.929164752377246
108	76.79	77.2434140876941	101.323333333333	0.762345765250131	0.994130061532763
109	75.28	65.9366781333619	100.98375	0.652943450142838	1.14170143433281
110	73.89	62.2032870163497	100.698333333333	0.617719131561426	1.18787934760712
111	76.24	59.3615173878709	100.300833333333	0.591834737709433	1.28433374608409
112	88.58	72.2426047150293	98.8420833333333	0.730889134250637	1.22614626575849
113	105.83	99.0990292788798	97.2470833333333	1.01904371711796	1.06792166149457
114	115.84	119.629064910699	95.6683333333333	1.25045624547342	0.968326552468433
115	127.76	NA	NA	1.44245873249646	NA
116	131.75	NA	NA	1.38543912516858	NA
117	119.63	NA	NA	1.37855893208892	NA
118	93.38	NA	NA	1.22336684616751	NA
119	75.55	NA	NA	0.944944182572692	NA
120	51.79	NA	NA	0.762345765250131	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/18b2u1274734990.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/18b2u1274734990.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/28b2u1274734990.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/28b2u1274734990.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/3132x1274734990.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/3132x1274734990.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/4132x1274734990.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/24/t127473545807syqus8nz7zxo6/4132x1274734990.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')

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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