Home » date » 2010 » Aug » 17 »

TIJDREEKS A - STAP 29

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 17 Aug 2010 14:31:20 +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/Aug/17/t1282055448oqhsto063wbk3ms.htm/, Retrieved Tue, 17 Aug 2010 16:30:55 +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/Aug/17/t1282055448oqhsto063wbk3ms.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:

Schrauwen Nathalie

Dataseries X:

» Textbox « » Textfile « » CSV «

125 124 123 121 141 140 125 115 116 116 117 119 114 110 108 111 124 125 118 108 107 103 113 116 113 105 102 107 119 116 113 102 96 95 101 110 103 88 79 96 118 116 114 102 98 98 101 117 109 98 93 98 114 115 112 112 103 107 104 117 123 113 97 90 109 104 92 102 90 97 99 108 106 86 72 71 96 88 83 90 85 100 108 118 124 99 92 86 112 104 93 104 96 109 113 123 127 96 100 95 133 130 117 129 122 134 141 152 161 122 126 119 160 162 145 161 151 166 169 185

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	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	125	NA	NA	11.3314043209877	NA
2	124	NA	NA	-7.08526234567902	NA
3	123	NA	NA	-12.7935956790123	NA
4	121	NA	NA	-12.7426697530864	NA
5	141	NA	NA	10.3406635802469	NA
6	140	NA	NA	7.01658950617284	NA
7	125	122.447145061728	123.041666666667	-0.594521604938272	2.55285493827162
8	115	120.914737654321	122	-1.08526234567901	-5.91473765432099
9	116	114.035108024691	120.791666666667	-6.75655864197531	1.96489197530866
10	116	118.099922839506	119.75	-1.65007716049382	-2.09992283950618
11	117	121.118441358025	118.625	2.49344135802469	-4.11844135802468
12	119	128.817515432099	117.291666666667	11.5258487654321	-9.81751543209877
13	114	127.706404320988	116.375	11.3314043209877	-13.7064043209877
14	110	108.706404320988	115.791666666667	-7.08526234567902	1.29359567901233
15	108	102.331404320988	115.125	-12.7935956790123	5.66859567901236
16	111	101.465663580247	114.208333333333	-12.7426697530864	9.5343364197531
17	124	123.840663580247	113.5	10.3406635802469	0.159336419753075
18	125	120.224922839506	113.208333333333	7.01658950617284	4.77507716049384
19	118	112.447145061728	113.041666666667	-0.594521604938272	5.55285493827159
20	108	111.706404320988	112.791666666667	-1.08526234567901	-3.70640432098764
21	107	105.576774691358	112.333333333333	-6.75655864197531	1.42322530864199
22	103	110.266589506173	111.916666666667	-1.65007716049382	-7.26658950617283
23	113	114.035108024691	111.541666666667	2.49344135802469	-1.03510802469135
24	116	122.484182098765	110.958333333333	11.5258487654321	-6.48418209876542
25	113	121.706404320988	110.375	11.3314043209877	-8.70640432098766
26	105	102.831404320988	109.916666666667	-7.08526234567902	2.16859567901234
27	102	96.414737654321	109.208333333333	-12.7935956790123	5.58526234567903
28	107	95.6739969135803	108.416666666667	-12.7426697530864	11.3260030864197
29	119	117.923996913580	107.583333333333	10.3406635802469	1.07600308641975
30	116	113.849922839506	106.833333333333	7.01658950617284	2.15007716049384
31	113	105.572145061728	106.166666666667	-0.594521604938272	7.4278549382716
32	102	103.956404320988	105.041666666667	-1.08526234567901	-1.95640432098766
33	96	96.6184413580247	103.375	-6.75655864197531	-0.618441358024697
34	95	100.308256172840	101.958333333333	-1.65007716049382	-5.30825617283952
35	101	103.951774691358	101.458333333333	2.49344135802469	-2.95177469135801
36	110	112.942515432099	101.416666666667	11.5258487654321	-2.94251543209876
37	103	112.789737654321	101.458333333333	11.3314043209877	-9.78973765432099
38	88	94.414737654321	101.5	-7.08526234567902	-6.414737654321
39	79	88.789737654321	101.583333333333	-12.7935956790123	-9.78973765432099
40	96	89.0489969135802	101.791666666667	-12.7426697530864	6.95100308641976
41	118	112.257330246914	101.916666666667	10.3406635802469	5.74266975308643
42	116	109.224922839506	102.208333333333	7.01658950617284	6.77507716049385
43	114	102.155478395062	102.75	-0.594521604938272	11.8445216049383
44	102	102.331404320988	103.416666666667	-1.08526234567901	-0.331404320987644
45	98	97.6601080246914	104.416666666667	-6.75655864197531	0.339891975308646
46	98	103.433256172839	105.083333333333	-1.65007716049382	-5.43325617283949
47	101	107.493441358025	105	2.49344135802469	-6.49344135802468
48	117	116.317515432099	104.791666666667	11.5258487654321	0.682484567901227
49	109	115.998070987654	104.666666666667	11.3314043209877	-6.99807098765433
50	98	97.914737654321	105	-7.08526234567902	0.0852623456790127
51	93	92.8314043209876	105.625	-12.7935956790123	0.168595679012370
52	98	93.4656635802469	106.208333333333	-12.7426697530864	4.5343364197531
53	114	117.048996913580	106.708333333333	10.3406635802469	-3.04899691358025
54	115	113.849922839506	106.833333333333	7.01658950617284	1.15007716049384
55	112	106.822145061728	107.416666666667	-0.594521604938272	5.17785493827161
56	112	107.539737654321	108.625	-1.08526234567901	4.46026234567903
57	103	102.660108024691	109.416666666667	-6.75655864197531	0.339891975308674
58	107	107.599922839506	109.25	-1.65007716049382	-0.599922839506149
59	104	111.201774691358	108.708333333333	2.49344135802469	-7.201774691358
60	117	119.567515432099	108.041666666667	11.5258487654321	-2.56751543209876
61	123	118.081404320988	106.75	11.3314043209877	4.91859567901234
62	113	98.414737654321	105.5	-7.08526234567902	14.585262345679
63	97	91.7480709876543	104.541666666667	-12.7935956790123	5.25192901234568
64	90	90.8406635802469	103.583333333333	-12.7426697530864	-0.840663580246911
65	109	113.298996913580	102.958333333333	10.3406635802469	-4.29899691358025
66	104	109.391589506173	102.375	7.01658950617284	-5.39158950617282
67	92	100.697145061728	101.291666666667	-0.594521604938272	-8.6971450617284
68	102	98.3730709876543	99.4583333333333	-1.08526234567901	3.6269290123457
69	90	90.5351080246914	97.2916666666667	-6.75655864197531	-0.535108024691354
70	97	93.8082561728395	95.4583333333333	-1.65007716049382	3.19174382716049
71	99	96.6184413580247	94.125	2.49344135802469	2.38155864197530
72	108	104.442515432099	92.9166666666667	11.5258487654321	3.55748456790124
73	106	103.206404320988	91.875	11.3314043209877	2.79359567901236
74	86	83.914737654321	91	-7.08526234567902	2.08526234567903
75	72	77.4980709876543	90.2916666666667	-12.7935956790123	-5.4980709876543
76	71	77.4656635802469	90.2083333333333	-12.7426697530864	-6.46566358024691
77	96	101.048996913580	90.7083333333333	10.3406635802469	-5.04899691358025
78	88	98.5165895061728	91.5	7.01658950617284	-10.5165895061728
79	83	92.0721450617284	92.6666666666667	-0.594521604938272	-9.0721450617284
80	90	92.8730709876543	93.9583333333333	-1.08526234567901	-2.87307098765432
81	85	88.576774691358	95.3333333333333	-6.75655864197531	-3.57677469135801
82	100	95.1415895061728	96.7916666666667	-1.65007716049382	4.85841049382717
83	108	100.576774691358	98.0833333333333	2.49344135802469	7.423225308642
84	118	110.942515432099	99.4166666666667	11.5258487654321	7.05748456790124
85	124	111.831404320988	100.5	11.3314043209877	12.1685956790124
86	99	94.414737654321	101.5	-7.08526234567902	4.58526234567903
87	92	89.7480709876543	102.541666666667	-12.7935956790123	2.25192901234571
88	86	90.6323302469136	103.375	-12.7426697530864	-4.63233024691357
89	112	114.298996913580	103.958333333333	10.3406635802469	-2.29899691358024
90	104	111.391589506173	104.375	7.01658950617284	-7.39158950617283
91	93	104.113811728395	104.708333333333	-0.594521604938272	-11.1138117283951
92	104	103.623070987654	104.708333333333	-1.08526234567901	0.37692901234567
93	96	98.1601080246914	104.916666666667	-6.75655864197531	-2.16010802469135
94	109	103.974922839506	105.625	-1.65007716049382	5.02507716049382
95	113	109.368441358025	106.875	2.49344135802469	3.6315586419753
96	123	120.359182098765	108.833333333333	11.5258487654321	2.64081790123457
97	127	122.248070987654	110.916666666667	11.3314043209877	4.75192901234568
98	96	105.873070987654	112.958333333333	-7.08526234567902	-9.8730709876543
99	100	102.289737654321	115.083333333333	-12.7935956790123	-2.28973765432097
100	95	104.465663580247	117.208333333333	-12.7426697530864	-9.4656635802469
101	133	129.757330246914	119.416666666667	10.3406635802469	3.24266975308643
102	130	128.808256172839	121.791666666667	7.01658950617284	1.19174382716051
103	117	123.822145061728	124.416666666667	-0.594521604938272	-6.8221450617284
104	129	125.831404320988	126.916666666667	-1.08526234567901	3.16859567901236
105	122	122.326774691358	129.083333333333	-6.75655864197531	-0.326774691358025
106	134	129.516589506173	131.166666666667	-1.65007716049382	4.48341049382717
107	141	135.785108024691	133.291666666667	2.49344135802469	5.21489197530866
108	152	147.275848765432	135.75	11.5258487654321	4.7241512345679
109	161	149.581404320988	138.25	11.3314043209877	11.4185956790124
110	122	133.664737654321	140.75	-7.08526234567902	-11.6647376543210
111	126	130.498070987654	143.291666666667	-12.7935956790123	-4.49807098765433
112	119	133.090663580247	145.833333333333	-12.7426697530864	-14.0906635802469
113	160	158.673996913580	148.333333333333	10.3406635802469	1.32600308641977
114	162	157.891589506173	150.875	7.01658950617284	4.10841049382717
115	145	NA	NA	-0.594521604938272	NA
116	161	NA	NA	-1.08526234567901	NA
117	151	NA	NA	-6.75655864197531	NA
118	166	NA	NA	-1.65007716049382	NA
119	169	NA	NA	2.49344135802469	NA
120	185	NA	NA	11.5258487654321	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/1xxrn1282055478.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/1xxrn1282055478.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/287qq1282055478.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/287qq1282055478.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/387qq1282055478.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/387qq1282055478.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/40gps1282055478.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/17/t1282055448oqhsto063wbk3ms/40gps1282055478.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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