Home » date » 2010 » Aug » 19 »

tijdreeks 1 - 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: Thu, 19 Aug 2010 20:31:32 +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/19/t1282251454xt7eqq9xb0veza7.htm/, Retrieved Thu, 19 Aug 2010 22:57:39 +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/19/t1282251454xt7eqq9xb0veza7.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:

Aerts Ellen

Dataseries X:

» Textbox « » Textfile « » CSV «

25 24 23 21 41 40 25 15 16 16 17 19 18 19 20 21 46 47 30 16 15 18 30 31 32 36 30 31 61 57 45 33 31 36 46 49 34 40 41 48 75 77 71 54 50 56 66 66 48 63 71 70 88 92 91 80 81 81 98 106 85 93 96 92 115 109 119 107 107 106 132 143 120 123 132 136 158 151 155 138 143 139 168 182 154 158 167 170 197 190 196 174 180 171 200 215 184 186 197 186 211 205 218 199 213 207 236 248 211 220 235 223 245 236 253 246 255 248 274 288

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	5 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	25	NA	NA	-9.86265432098766	NA
2	24	NA	NA	-6.20987654320987	NA
3	23	NA	NA	-2.71913580246914	NA
4	21	NA	NA	-6.23302469135802	NA
5	41	NA	NA	15.8364197530864	NA
6	40	NA	NA	9.84567901234568	NA
7	25	31.7253086419753	23.2083333333333	8.51697530864198	-6.72530864197531
8	15	14.5679012345679	22.7083333333333	-8.14043209876543	0.432098765432098
9	16	14.5679012345679	22.375	-7.80709876543211	1.43209876543211
10	16	11.8595679012346	22.25	-10.3904320987654	4.14043209876543
11	17	28.2993827160494	22.4583333333333	5.84104938271605	-11.2993827160494
12	19	34.2808641975309	22.9583333333333	11.3225308641975	-15.2808641975309
13	18	13.5956790123457	23.4583333333333	-9.86265432098766	4.40432098765433
14	19	17.4984567901235	23.7083333333333	-6.20987654320987	1.50154320987654
15	20	20.9891975308642	23.7083333333333	-2.71913580246914	-0.989197530864192
16	21	17.5169753086420	23.75	-6.23302469135802	3.48302469135802
17	46	40.2114197530864	24.375	15.8364197530864	5.78858024691358
18	47	35.2623456790123	25.4166666666667	9.84567901234568	11.7376543209877
19	30	35.016975308642	26.5	8.51697530864198	-5.01697530864198
20	16	19.6512345679012	27.7916666666667	-8.14043209876543	-3.65123456790124
21	15	21.1095679012346	28.9166666666667	-7.80709876543211	-6.10956790123456
22	18	19.3595679012346	29.75	-10.3904320987654	-1.35956790123457
23	30	36.6327160493827	30.7916666666667	5.84104938271605	-6.63271604938272
24	31	43.1558641975309	31.8333333333333	11.3225308641975	-12.1558641975309
25	32	23.0123456790123	32.875	-9.86265432098766	8.98765432098766
26	36	27.9984567901235	34.2083333333333	-6.20987654320987	8.00154320987654
27	30	32.8641975308642	35.5833333333333	-2.71913580246914	-2.86419753086419
28	31	30.766975308642	37	-6.23302469135802	0.233024691358018
29	61	54.2530864197531	38.4166666666667	15.8364197530864	6.74691358024692
30	57	49.679012345679	39.8333333333333	9.84567901234568	7.320987654321
31	45	49.1836419753086	40.6666666666667	8.51697530864198	-4.18364197530864
32	33	32.7762345679012	40.9166666666667	-8.14043209876543	0.223765432098766
33	31	33.7345679012346	41.5416666666667	-7.80709876543211	-2.73456790123456
34	36	32.3179012345679	42.7083333333333	-10.3904320987654	3.6820987654321
35	46	49.841049382716	44	5.84104938271605	-3.84104938271604
36	49	56.7391975308642	45.4166666666667	11.3225308641975	-7.7391975308642
37	34	37.4706790123457	47.3333333333333	-9.86265432098766	-3.47067901234568
38	40	43.0817901234568	49.2916666666667	-6.20987654320987	-3.0817901234568
39	41	48.2391975308642	50.9583333333333	-2.71913580246914	-7.2391975308642
40	48	46.3503086419753	52.5833333333333	-6.23302469135802	1.64969135802468
41	75	70.0864197530864	54.25	15.8364197530864	4.91358024691358
42	77	65.6373456790123	55.7916666666667	9.84567901234568	11.3626543209877
43	71	65.6003086419753	57.0833333333333	8.51697530864198	5.3996913580247
44	54	50.4845679012346	58.625	-8.14043209876543	3.51543209876544
45	50	53.0262345679012	60.8333333333333	-7.80709876543211	-3.02623456790122
46	56	52.6095679012346	63	-10.3904320987654	3.39043209876544
47	66	70.2993827160494	64.4583333333333	5.84104938271605	-4.29938271604937
48	66	76.9475308641975	65.625	11.3225308641975	-10.9475308641975
49	48	57.2206790123457	67.0833333333333	-9.86265432098766	-9.22067901234567
50	63	62.7901234567901	69	-6.20987654320987	0.209876543209873
51	71	68.6558641975309	71.375	-2.71913580246914	2.34413580246914
52	70	67.4753086419753	73.7083333333333	-6.23302469135802	2.52469135802470
53	88	91.9197530864198	76.0833333333333	15.8364197530864	-3.91975308641976
54	92	88.929012345679	79.0833333333333	9.84567901234568	3.07098765432099
55	91	90.8086419753086	82.2916666666667	8.51697530864198	0.191358024691354
56	80	76.9429012345679	85.0833333333333	-8.14043209876543	3.0570987654321
57	81	79.5679012345679	87.375	-7.80709876543211	1.43209876543212
58	81	78.9429012345679	89.3333333333333	-10.3904320987654	2.0570987654321
59	98	97.216049382716	91.375	5.84104938271605	0.78395061728395
60	106	104.530864197531	93.2083333333333	11.3225308641975	1.46913580246913
61	85	85.2206790123457	95.0833333333333	-9.86265432098766	-0.220679012345684
62	93	91.1651234567901	97.375	-6.20987654320987	1.83487654320987
63	96	96.8641975308642	99.5833333333333	-2.71913580246914	-0.864197530864189
64	92	95.4753086419753	101.708333333333	-6.23302469135802	-3.4753086419753
65	115	120.003086419753	104.166666666667	15.8364197530864	-5.00308641975306
66	109	116.970679012346	107.125	9.84567901234568	-7.97067901234566
67	119	118.641975308642	110.125	8.51697530864198	0.358024691358025
68	107	104.692901234568	112.833333333333	-8.14043209876543	2.3070987654321
69	107	107.776234567901	115.583333333333	-7.80709876543211	-0.776234567901241
70	106	108.526234567901	118.916666666667	-10.3904320987654	-2.52623456790123
71	132	128.382716049383	122.541666666667	5.84104938271605	3.61728395061728
72	143	137.405864197531	126.083333333333	11.3225308641975	5.59413580246911
73	120	119.470679012346	129.333333333333	-9.86265432098766	0.529320987654302
74	123	125.915123456790	132.125	-6.20987654320987	-2.91512345679013
75	132	132.197530864198	134.916666666667	-2.71913580246914	-0.197530864197546
76	136	131.558641975309	137.791666666667	-6.23302469135802	4.44135802469137
77	158	156.503086419753	140.666666666667	15.8364197530864	1.49691358024691
78	151	153.637345679012	143.791666666667	9.84567901234568	-2.63734567901233
79	155	155.350308641975	146.833333333333	8.51697530864198	-0.350308641975289
80	138	141.567901234568	149.708333333333	-8.14043209876543	-3.56790123456793
81	143	144.817901234568	152.625	-7.80709876543211	-1.8179012345679
82	139	145.109567901235	155.5	-10.3904320987654	-6.10956790123456
83	168	164.382716049383	158.541666666667	5.84104938271605	3.61728395061726
84	182	173.114197530864	161.791666666667	11.3225308641975	8.88580246913583
85	154	155.262345679012	165.125	-9.86265432098766	-1.26234567901236
86	158	162.123456790123	168.333333333333	-6.20987654320987	-4.12345679012347
87	167	168.655864197531	171.375	-2.71913580246914	-1.65586419753086
88	170	168.016975308642	174.25	-6.23302469135802	1.98302469135805
89	197	192.753086419753	176.916666666667	15.8364197530864	4.24691358024691
90	190	189.470679012346	179.625	9.84567901234568	0.529320987654359
91	196	190.766975308642	182.25	8.51697530864198	5.23302469135808
92	174	176.526234567901	184.666666666667	-8.14043209876543	-2.52623456790121
93	180	179.276234567901	187.083333333333	-7.80709876543211	0.723765432098759
94	171	178.609567901235	189	-10.3904320987654	-7.60956790123458
95	200	196.091049382716	190.25	5.84104938271605	3.90895061728395
96	215	202.780864197531	191.458333333333	11.3225308641975	12.2191358024691
97	184	183.137345679012	193	-9.86265432098766	0.862654320987673
98	186	188.748456790123	194.958333333333	-6.20987654320987	-2.74845679012344
99	197	194.655864197531	197.375	-2.71913580246914	2.34413580246917
100	186	194.016975308642	200.25	-6.23302469135802	-8.01697530864195
101	211	219.086419753086	203.25	15.8364197530864	-8.0864197530864
102	205	215.970679012346	206.125	9.84567901234568	-10.9706790123457
103	218	217.141975308642	208.625	8.51697530864198	0.858024691358025
104	199	203.026234567901	211.166666666667	-8.14043209876543	-4.02623456790124
105	213	206.359567901235	214.166666666667	-7.80709876543211	6.64043209876542
106	207	206.901234567901	217.291666666667	-10.3904320987654	0.0987654320987588
107	236	226.091049382716	220.25	5.84104938271605	9.90895061728398
108	248	234.280864197531	222.958333333333	11.3225308641975	13.7191358024692
109	211	215.845679012346	225.708333333333	-9.86265432098766	-4.84567901234567
110	220	222.91512345679	229.125	-6.20987654320987	-2.91512345679007
111	235	230.114197530864	232.833333333333	-2.71913580246914	4.88580246913583
112	223	230.058641975309	236.291666666667	-6.23302469135802	-7.05864197530863
113	245	255.419753086420	239.583333333333	15.8364197530864	-10.4197530864198
114	236	252.679012345679	242.833333333333	9.84567901234568	-16.6790123456790
115	253	NA	NA	8.51697530864198	NA
116	246	NA	NA	-8.14043209876543	NA
117	255	NA	NA	-7.80709876543211	NA
118	248	NA	NA	-10.3904320987654	NA
119	274	NA	NA	5.84104938271605	NA
120	288	NA	NA	11.3225308641975	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/19mml1282249886.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/19mml1282249886.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/2kel61282249886.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/2kel61282249886.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/3kel61282249886.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/3kel61282249886.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/4dnkr1282249886.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/19/t1282251454xt7eqq9xb0veza7/4dnkr1282249886.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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