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KDGP2W52

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 12 Jan 2010 09:57:41 -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/12/t1263315578i8wqo482cqqyrjh.htm/, Retrieved Tue, 12 Jan 2010 17:59:44 +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/12/t1263315578i8wqo482cqqyrjh.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:

oef 9 2

Dataseries X:

» Textbox « » Textfile « » CSV «

104,65 109,2 103,93 101,93 101,58 102,63 106,83 105,57 105 104,16 106,93 106,5 106,47 112,33 106,81 103,49 104,13 103,2 105,55 102,8 106,68 105,43 109,01 112,24 112,87 110,98 112,85 112,08 110,72 109,69 112,53 112,99 111,74 111,15 114,82 117,38 117,81 122,85 116,96 119,16 117,74 118,84 123,81 120,33 119,2 117,32 128,58 129,2 126,19 132,1 128,12 122,28 122,36 123,13 125,97 126,14 122,7 122,67 129,19 133,01 123,96 128,96 127,32 131,38 125,25 127,91 130,42 128,44 125,86 125,71 130,63 131,78 125,61 131,84 122,14 127,13 124,49 125,48 129,86 126,32 125,56 125,64 128,26 125,47 134,4 134,5 131,22 121,62 124,16 127,5 132,86 127,87 124,07 124,25 131,16 129,24 129,24 135,51 128,97 126,89 127,52 130,31 132,39 132,69 128,73 129,66 127,72 132,63 129,74 138,46 134,31 128,8 129,95 134,15 136,01 135,1 132,27 132,49 130,06 136,11 131,47 140,61 141,65 126,75 133,9 138,75 141,86 141,13 138,76 138,65 1 etc...

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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	104.65	NA	NA	0.313829861111111	NA
2	109.2	NA	NA	5.05770486111112	NA
3	103.93	NA	NA	0.989871527777777	NA
4	101.93	NA	NA	-2.37150347222222	NA
5	101.58	NA	NA	-2.58312847222222	NA
6	102.63	NA	NA	-1.01017013888889	NA
7	106.83	106.895288194444	104.985	1.91028819444445	-0.0652881944444346
8	105.57	105.049246527778	105.19125	-0.142003472222227	0.520753472222225
9	105	103.153746527778	105.441666666667	-2.28792013888889	1.84625347222223
10	104.16	102.773454861111	105.626666666667	-2.85321180555556	1.38654513888889
11	106.93	106.145413194444	105.797916666667	0.347496527777776	0.784586805555563
12	106.5	108.556663194444	105.927916666667	2.62874652777778	-2.05666319444444
13	106.47	106.212163194444	105.898333333333	0.313829861111111	0.25783680555557
14	112.33	110.787288194444	105.729583333333	5.05770486111112	1.54271180555556
15	106.81	106.674038194444	105.684166666667	0.989871527777777	0.135961805555553
16	103.49	103.435579861111	105.807083333333	-2.37150347222222	0.0544201388888723
17	104.13	103.363538194444	105.946666666667	-2.58312847222222	0.76646180555555
18	103.2	105.262329861111	106.2725	-1.01017013888889	-2.06232986111111
19	105.55	108.688621527778	106.778333333333	1.91028819444445	-3.13862152777777
20	102.8	106.846746527778	106.98875	-0.142003472222227	-4.04674652777776
21	106.68	104.896246527778	107.184166666667	-2.28792013888889	1.78375347222224
22	105.43	104.940538194444	107.79375	-2.85321180555556	0.489461805555578
23	109.01	108.773746527778	108.42625	0.347496527777776	0.236253472222231
24	112.24	111.599996527778	108.97125	2.62874652777778	0.640003472222233
25	112.87	109.846329861111	109.5325	0.313829861111111	3.02367013888890
26	110.98	115.305621527778	110.247916666667	5.05770486111112	-4.32562152777778
27	112.85	111.873204861111	110.883333333333	0.989871527777777	0.976795138888889
28	112.08	108.960996527778	111.3325	-2.37150347222222	3.11900347222223
29	110.72	109.229788194444	111.812916666667	-2.58312847222222	1.49021180555557
30	109.69	111.258996527778	112.269166666667	-1.01017013888889	-1.56899652777777
31	112.53	114.599454861111	112.689166666667	1.91028819444445	-2.06945486111110
32	112.99	113.247579861111	113.389583333333	-0.142003472222227	-0.257579861111125
33	111.74	111.767496527778	114.055416666667	-2.28792013888889	-0.027496527777771
34	111.15	111.668454861111	114.521666666667	-2.85321180555556	-0.518454861111096
35	114.82	115.456663194444	115.109166666667	0.347496527777776	-0.636663194444438
36	117.38	118.411663194444	115.782916666667	2.62874652777778	-1.03166319444442
37	117.81	116.947996527778	116.634166666667	0.313829861111111	0.862003472222227
38	122.85	122.467704861111	117.41	5.05770486111112	0.382295138888892
39	116.96	119.016538194444	118.026666666667	0.989871527777777	-2.05653819444444
40	119.16	116.223079861111	118.594583333333	-2.37150347222222	2.93692013888889
41	117.74	116.841871527778	119.425	-2.58312847222222	0.898128472222226
42	118.84	119.480663194444	120.490833333333	-1.01017013888889	-0.640663194444443
43	123.81	123.242788194444	121.3325	1.91028819444445	0.567211805555559
44	120.33	121.925079861111	122.067083333333	-0.142003472222227	-1.59507986111110
45	119.2	120.629579861111	122.9175	-2.28792013888889	-1.42957986111109
46	117.32	120.659288194444	123.5125	-2.85321180555556	-3.33928819444446
47	128.58	124.182496527778	123.835	0.347496527777776	4.39750347222224
48	129.2	126.834996527778	124.20625	2.62874652777778	2.36500347222221
49	126.19	124.788829861111	124.475	0.313829861111111	1.40117013888887
50	132.1	129.864788194444	124.807083333333	5.05770486111112	2.23521180555555
51	128.12	126.184871527778	125.195	0.989871527777777	1.93512847222223
52	122.28	123.192246527778	125.56375	-2.37150347222222	-0.912246527777768
53	122.36	123.228954861111	125.812083333333	-2.58312847222222	-0.868954861111092
54	123.13	124.986079861111	125.99625	-1.01017013888889	-1.85607986111111
55	125.97	127.972371527778	126.062083333333	1.91028819444445	-2.00237152777778
56	126.14	125.696329861111	125.838333333333	-0.142003472222227	0.443670138888905
57	122.7	123.386246527778	125.674166666667	-2.28792013888889	-0.686246527777783
58	122.67	123.166788194444	126.02	-2.85321180555556	-0.49678819444442
59	129.19	126.867079861111	126.519583333333	0.347496527777776	2.32292013888892
60	133.01	129.467913194444	126.839166666667	2.62874652777778	3.54208680555556
61	123.96	127.537579861111	127.22375	0.313829861111111	-3.5775798611111
62	128.96	132.562704861111	127.505	5.05770486111112	-3.60270486111108
63	127.32	128.722371527778	127.7325	0.989871527777777	-1.40237152777777
64	131.38	125.619329861111	127.990833333333	-2.37150347222222	5.7606701388889
65	125.25	125.594371527778	128.1775	-2.58312847222222	-0.344371527777753
66	127.91	127.176079861111	128.18625	-1.01017013888889	0.733920138888891
67	130.42	130.114038194444	128.20375	1.91028819444445	0.305961805555540
68	128.44	128.250496527778	128.3925	-0.142003472222227	0.189503472222214
69	125.86	126.008746527778	128.296666666667	-2.28792013888889	-0.148746527777774
70	125.71	125.050538194444	127.90375	-2.85321180555556	0.659461805555566
71	130.63	128.042496527778	127.695	0.347496527777776	2.58750347222224
72	131.78	130.190829861111	127.562083333333	2.62874652777778	1.58917013888889
73	125.61	127.751329861111	127.4375	0.313829861111111	-2.14132986111112
74	131.84	132.383538194444	127.325833333333	5.05770486111112	-0.543538194444437
75	122.14	128.214871527778	127.225	0.989871527777777	-6.07487152777777
76	127.13	124.838079861111	127.209583333333	-2.37150347222222	2.29192013888890
77	124.49	124.524788194444	127.107916666667	-2.58312847222222	-0.0347881944444310
78	125.48	125.736079861111	126.74625	-1.01017013888889	-0.256079861111076
79	129.86	128.759871527778	126.849583333333	1.91028819444445	1.10012847222225
80	126.32	127.184663194444	127.326666666667	-0.142003472222227	-0.864663194444447
81	125.56	125.527913194444	127.815833333333	-2.28792013888889	0.0320868055555508
82	125.64	125.111371527778	127.964583333333	-2.85321180555556	0.528628472222209
83	128.26	128.068746527778	127.72125	0.347496527777776	0.191253472222201
84	125.47	130.420413194444	127.791666666667	2.62874652777778	-4.95041319444447
85	134.4	128.314663194444	128.000833333333	0.313829861111111	6.08533680555556
86	134.5	133.248121527778	128.190416666667	5.05770486111112	1.25187847222222
87	131.22	129.182788194444	128.192916666667	0.989871527777777	2.03721180555556
88	121.62	125.701413194444	128.072916666667	-2.37150347222222	-4.08141319444444
89	124.16	125.552704861111	128.135833333333	-2.58312847222222	-1.3927048611111
90	127.5	127.403579861111	128.41375	-1.01017013888889	0.0964201388889023
91	132.86	130.266121527778	128.355833333333	1.91028819444445	2.59387847222226
92	127.87	128.040913194444	128.182916666667	-0.142003472222227	-0.170913194444438
93	124.07	125.843329861111	128.13125	-2.28792013888889	-1.77332986111111
94	124.25	125.403871527778	128.257083333333	-2.85321180555556	-1.15387152777777
95	131.16	128.964163194444	128.616666666667	0.347496527777776	2.19583680555556
96	129.24	131.502496527778	128.87375	2.62874652777778	-2.26249652777777
97	129.24	129.285079861111	128.97125	0.313829861111111	-0.0450798611111338
98	135.51	134.210204861111	129.1525	5.05770486111112	1.29979513888887
99	128.97	130.537371527778	129.5475	0.989871527777777	-1.56737152777779
100	126.89	127.595579861111	129.967083333333	-2.37150347222222	-0.705579861111119
101	127.52	127.466038194444	130.049166666667	-2.58312847222222	0.0539618055555593
102	130.31	129.036913194444	130.047083333333	-1.01017013888889	1.27308680555555
103	132.39	132.119454861111	130.209166666667	1.91028819444445	0.270545138888878
104	132.69	130.210913194444	130.352916666667	-0.142003472222227	2.47908680555557
105	128.73	128.410413194444	130.698333333333	-2.28792013888889	0.319586805555559
106	129.66	128.147204861111	131.000416666667	-2.85321180555556	1.51279513888889
107	127.72	131.528746527778	131.18125	0.347496527777776	-3.80874652777776
108	132.63	134.071246527778	131.4425	2.62874652777778	-1.44124652777779
109	129.74	132.067163194444	131.753333333333	0.313829861111111	-2.32716319444444
110	138.46	137.062288194444	132.004583333333	5.05770486111112	1.39771180555556
111	134.31	133.242371527778	132.2525	0.989871527777777	1.06762847222222
112	128.8	130.146413194444	132.517916666667	-2.37150347222222	-1.34641319444441
113	129.95	130.150204861111	132.733333333333	-2.58312847222222	-0.200204861111132
114	134.15	131.965663194444	132.975833333333	-1.01017013888889	2.18433680555557
115	136.01	135.103204861111	133.192916666667	1.91028819444445	0.906795138888896
116	135.1	133.212579861111	133.354583333333	-0.142003472222227	1.8874201388889
117	132.27	131.462079861111	133.75	-2.28792013888889	0.807920138888932
118	132.49	131.117204861111	133.970416666667	-2.85321180555556	1.37279513888890
119	130.06	134.397079861111	134.049583333333	0.347496527777776	-4.33707986111108
120	136.11	137.034579861111	134.405833333333	2.62874652777778	-0.924579861111113
121	131.47	135.155079861111	134.84125	0.313829861111111	-3.68507986111112
122	140.61	140.393954861111	135.33625	5.05770486111112	0.216045138888887
123	141.65	136.847788194444	135.857916666667	0.989871527777777	4.80221180555557
124	126.75	134.013496527778	136.385	-2.37150347222222	-7.26349652777776
125	133.9	134.413954861111	136.997083333333	-2.58312847222222	-0.513954861111102
126	138.75	136.799829861111	137.81	-1.01017013888889	1.95017013888889
127	141.86	140.540288194444	138.63	1.91028819444445	1.31971180555558
128	141.13	139.340913194444	139.482916666667	-0.142003472222227	1.78908680555557
129	138.76	137.784163194444	140.072083333333	-2.28792013888889	0.97583680555553
130	138.65	137.850954861111	140.704166666667	-2.85321180555556	0.799045138888886
131	138.59	141.884996527778	141.5375	0.347496527777776	-3.29499652777778
132	147.09	144.762079861111	142.133333333333	2.62874652777778	2.32792013888889
133	140.17	NA	142.68	NA	NA
134	152.38	NA	143.099166666667	NA	NA
135	144.02	NA	NA	NA	NA
136	139.55	NA	NA	NA	NA
137	141.1	NA	NA	NA	NA
138	145.85	NA	NA	NA	NA
139	147.88	NA	NA	NA	NA
140	145.17	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/1xwqb1263315458.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/1xwqb1263315458.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/2j5601263315458.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/2j5601263315458.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/3aiup1263315458.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/3aiup1263315458.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/4bpml1263315458.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263315578i8wqo482cqqyrjh/4bpml1263315458.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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FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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