Home » date » 2010 » Aug » 03 »

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, 03 Aug 2010 14:28:38 +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/03/t1280845790ri4qo52buokpgg8.htm/, Retrieved Tue, 03 Aug 2010 16:29:56 +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/03/t1280845790ri4qo52buokpgg8.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:

Lisa Bruggeman

Dataseries X:

» Textbox « » Textfile « » CSV «

95 94 93 91 111 110 95 85 86 86 87 89 93 96 99 92 109 110 97 88 93 93 89 89 91 97 99 85 101 105 88 80 87 84 87 87 85 96 102 93 111 117 101 88 98 89 93 93 95 105 109 94 113 125 106 95 109 100 94 94 94 103 103 80 106 117 99 95 116 118 100 100 105 121 131 108 136 149 131 137 164 169 154 160 166 186 197 166 191 207 187 191 222 230 210 224 234 251 258 227 254 281 261 264 286 293 276 292 299 319 329 293 318 346 327 329 353 355 332 346

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	95	NA	NA	-4.21682098765432	NA
2	94	NA	NA	6.02391975308642	NA
3	93	NA	NA	9.54706790123456	NA
4	91	NA	NA	-13.9344135802469	NA
5	111	NA	NA	6.0192901234568	NA
6	110	NA	NA	16.8063271604938	NA
7	95	90.6813271604938	93.4166666666666	-2.73533950617284	4.31867283950619
8	85	84.028549382716	93.4166666666667	-9.38811728395062	0.971450617283963
9	86	97.5609567901234	93.75	3.81095679012345	-11.5609567901234
10	86	95.9359567901235	94.0416666666667	1.89429012345679	-9.93595679012346
11	87	86.0007716049383	94	-7.99922839506173	0.99922839506172
12	89	88.0887345679012	93.9166666666667	-5.82793209876543	0.911265432098773
13	93	89.7831790123457	94	-4.21682098765432	3.21682098765432
14	96	100.232253086420	94.2083333333333	6.02391975308642	-4.23225308641976
15	99	104.172067901235	94.625	9.54706790123456	-5.17206790123454
16	92	81.2739197530864	95.2083333333333	-13.9344135802469	10.7260802469136
17	109	101.602623456790	95.5833333333333	6.0192901234568	7.39737654320987
18	110	112.472993827161	95.6666666666667	16.8063271604938	-2.47299382716049
19	97	92.8479938271605	95.5833333333333	-2.73533950617284	4.15200617283949
20	88	86.153549382716	95.5416666666667	-9.38811728395062	1.84645061728395
21	93	99.3942901234568	95.5833333333333	3.81095679012345	-6.39429012345678
22	93	97.1859567901234	95.2916666666667	1.89429012345679	-4.18595679012344
23	89	86.667438271605	94.6666666666667	-7.99922839506173	2.33256172839506
24	89	88.2970679012346	94.125	-5.82793209876543	0.702932098765444
25	91	89.3248456790124	93.5416666666667	-4.21682098765432	1.67515432098764
26	97	98.8572530864198	92.8333333333333	6.02391975308642	-1.85725308641976
27	99	101.797067901235	92.25	9.54706790123456	-2.79706790123456
28	85	77.6905864197531	91.625	-13.9344135802469	7.30941358024691
29	101	97.1859567901235	91.1666666666667	6.0192901234568	3.81404320987654
30	105	107.806327160494	91	16.8063271604938	-2.80632716049381
31	88	87.9313271604938	90.6666666666667	-2.73533950617284	0.0686728395061778
32	80	80.9868827160494	90.375	-9.38811728395062	-0.98688271604938
33	87	94.2692901234568	90.4583333333333	3.81095679012345	-7.26929012345678
34	84	92.8109567901235	90.9166666666667	1.89429012345679	-8.81095679012346
35	87	83.667438271605	91.6666666666667	-7.99922839506173	3.33256172839505
36	87	86.7554012345679	92.5833333333333	-5.82793209876543	0.244598765432087
37	85	89.4081790123457	93.625	-4.21682098765432	-4.40817901234568
38	96	100.523919753086	94.5	6.02391975308642	-4.5239197530864
39	102	104.838734567901	95.2916666666667	9.54706790123456	-2.83873456790121
40	93	82.0239197530864	95.9583333333333	-13.9344135802469	10.9760802469136
41	111	102.435956790123	96.4166666666667	6.0192901234568	8.56404320987654
42	117	113.722993827160	96.9166666666667	16.8063271604938	3.27700617283952
43	101	94.8479938271605	97.5833333333333	-2.73533950617284	6.15200617283951
44	88	88.9868827160494	98.375	-9.38811728395062	-0.98688271604938
45	98	102.852623456790	99.0416666666667	3.81095679012345	-4.85262345679011
46	89	101.269290123457	99.375	1.89429012345679	-12.2692901234568
47	93	91.5007716049383	99.5	-7.99922839506173	1.49922839506172
48	93	94.0887345679012	99.9166666666667	-5.82793209876543	-1.08873456790124
49	95	96.241512345679	100.458333333333	-4.21682098765432	-1.24151234567903
50	105	106.982253086420	100.958333333333	6.02391975308642	-1.98225308641976
51	109	111.255401234568	101.708333333333	9.54706790123456	-2.25540123456788
52	94	88.6905864197531	102.625	-13.9344135802469	5.30941358024691
53	113	109.144290123457	103.125	6.0192901234568	3.85570987654322
54	125	120.014660493827	103.208333333333	16.8063271604938	4.98533950617286
55	106	100.472993827160	103.208333333333	-2.73533950617284	5.52700617283951
56	95	93.6952160493827	103.083333333333	-9.38811728395062	1.30478395061729
57	109	106.560956790123	102.75	3.81095679012345	2.43904320987654
58	100	103.810956790123	101.916666666667	1.89429012345679	-3.81095679012346
59	94	93.042438271605	101.041666666667	-7.99922839506173	0.957561728395063
60	94	94.5887345679012	100.416666666667	-5.82793209876543	-0.588734567901227
61	94	95.5748456790123	99.7916666666667	-4.21682098765432	-1.57484567901234
62	103	105.523919753086	99.5	6.02391975308642	-2.52391975308639
63	103	109.338734567901	99.7916666666666	9.54706790123456	-6.3387345679012
64	80	86.8989197530864	100.833333333333	-13.9344135802469	-6.8989197530864
65	106	107.852623456790	101.833333333333	6.0192901234568	-1.85262345679011
66	117	119.139660493827	102.333333333333	16.8063271604938	-2.13966049382714
67	99	100.306327160494	103.041666666667	-2.73533950617284	-1.30632716049382
68	95	94.8618827160494	104.25	-9.38811728395062	0.138117283950621
69	116	109.977623456790	106.166666666667	3.81095679012345	6.02237654320989
70	118	110.394290123457	108.5	1.89429012345679	7.60570987654323
71	100	102.917438271605	110.916666666667	-7.99922839506173	-2.91743827160495
72	100	107.672067901235	113.5	-5.82793209876543	-7.67206790123456
73	105	111.949845679012	116.166666666667	-4.21682098765432	-6.94984567901234
74	121	125.273919753086	119.25	6.02391975308642	-4.2739197530864
75	131	132.547067901235	123	9.54706790123456	-1.54706790123453
76	108	113.190586419753	127.125	-13.9344135802469	-5.19058641975307
77	136	137.519290123457	131.5	6.0192901234568	-1.51929012345676
78	149	153.056327160494	136.25	16.8063271604938	-4.05632716049379
79	131	138.556327160494	141.291666666667	-2.73533950617284	-7.55632716049382
80	137	137.153549382716	146.541666666667	-9.38811728395062	-0.153549382716051
81	164	155.810956790123	152	3.81095679012345	8.18904320987653
82	169	159.060956790123	157.166666666667	1.89429012345679	9.93904320987656
83	154	153.875771604938	161.875	-7.99922839506173	0.124228395061778
84	160	160.755401234568	166.583333333333	-5.82793209876543	-0.755401234567842
85	166	167.116512345679	171.333333333333	-4.21682098765432	-1.11651234567896
86	186	181.940586419753	175.916666666667	6.02391975308642	4.05941358024694
87	197	190.130401234568	180.583333333333	9.54706790123456	6.86959876543207
88	166	171.607253086420	185.541666666667	-13.9344135802469	-5.60725308641977
89	191	196.435956790123	190.416666666667	6.0192901234568	-5.43595679012344
90	207	212.222993827160	195.416666666667	16.8063271604938	-5.22299382716048
91	187	198.181327160494	200.916666666667	-2.73533950617284	-11.1813271604938
92	191	197.070216049383	206.458333333333	-9.38811728395062	-6.07021604938271
93	222	215.519290123457	211.708333333333	3.81095679012345	6.48070987654322
94	230	218.685956790123	216.791666666667	1.89429012345679	11.3140432098766
95	210	213.959104938272	221.958333333333	-7.99922839506173	-3.95910493827159
96	224	221.838734567901	227.666666666667	-5.82793209876543	2.16126543209882
97	234	229.616512345679	233.833333333333	-4.21682098765432	4.38348765432104
98	251	245.982253086420	239.958333333333	6.02391975308642	5.01774691358028
99	258	255.213734567901	245.666666666667	9.54706790123456	2.78626543209882
100	227	237.023919753086	250.958333333333	-13.9344135802469	-10.0239197530864
101	254	262.35262345679	256.333333333333	6.0192901234568	-8.35262345679004
102	281	278.722993827160	261.916666666667	16.8063271604938	2.27700617283955
103	261	264.722993827160	267.458333333333	-2.73533950617284	-3.72299382716045
104	264	263.611882716049	273	-9.38811728395062	0.388117283950692
105	286	282.60262345679	278.791666666667	3.81095679012345	3.39737654320993
106	293	286.394290123457	284.5	1.89429012345679	6.60570987654324
107	276	281.917438271605	289.916666666667	-7.99922839506173	-5.91743827160491
108	292	289.463734567901	295.291666666667	-5.82793209876543	2.53626543209873
109	299	296.533179012346	300.75	-4.21682098765432	2.46682098765433
110	319	312.23225308642	306.208333333333	6.02391975308642	6.76774691358025
111	329	321.255401234568	311.708333333333	9.54706790123456	7.74459876543204
112	293	303.148919753086	317.083333333333	-13.9344135802469	-10.1489197530864
113	318	328.019290123457	322	6.0192901234568	-10.0192901234568
114	346	343.389660493827	326.583333333333	16.8063271604938	2.61033950617286
115	327	NA	NA	-2.73533950617284	NA
116	329	NA	NA	-9.38811728395062	NA
117	353	NA	NA	3.81095679012345	NA
118	355	NA	NA	1.89429012345679	NA
119	332	NA	NA	-7.99922839506173	NA
120	346	NA	NA	-5.82793209876543	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/1wqec1280845715.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/1wqec1280845715.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/2wqec1280845715.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/2wqec1280845715.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/37hdx1280845715.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/37hdx1280845715.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/47hdx1280845715.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/03/t1280845790ri4qo52buokpgg8/47hdx1280845715.ps (open in new window)

Parameters (Session):

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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