Home » date » 2010 » Aug » 06 »

Tijdsreeks 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: Fri, 06 Aug 2010 17:35:03 +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/06/t1281116162j47soyitn3pmx53.htm/, Retrieved Fri, 06 Aug 2010 19:36:08 +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/06/t1281116162j47soyitn3pmx53.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:

Gosselin Claudia

Dataseries X:

» Textbox « » Textfile « » CSV «

155 154 153 151 171 170 155 145 146 146 147 149 146 155 149 140 155 152 137 127 134 125 132 141 133 143 141 132 144 140 130 122 124 119 128 131 121 123 116 109 116 109 103 98 95 83 92 94 76 75 77 68 80 66 69 67 68 64 72 70 55 55 54 55 67 54 57 53 49 47 64 58 38 41 38 41 60 49 53 55 56 52 68 68 41 46 41 47 62 48 53 61 59 46 69 69 42 42 42 50 64 47 51 66 64 49 71 68 39 30 22 33 46 24 27 45 38 18 36 31

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	155	NA	NA	-6.289737654321	NA
2	154	NA	NA	-3.12307098765432	NA
3	153	NA	NA	-5.4934413580247	NA
4	151	NA	NA	-4.95640432098766	NA
5	171	NA	NA	9.37229938271605	NA
6	170	NA	NA	-1.23418209876543	NA
7	155	152.742669753086	153.125	-0.382330246913579	2.25733024691357
8	145	151.964891975309	152.791666666667	-0.826774691358022	-6.96489197530863
9	146	153.131558641975	152.666666666667	0.464891975308641	-7.13155864197532
10	146	146.548225308642	152.041666666667	-5.49344135802469	-0.548225308641975
11	147	158.992669753086	150.916666666667	8.07600308641976	-11.9926697530864
12	149	159.386188271605	149.5	9.88618827160494	-10.3861882716049
13	146	141.710262345679	148	-6.289737654321	4.28973765432096
14	155	143.376929012346	146.5	-3.12307098765432	11.6230709876543
15	149	139.756558641975	145.25	-5.4934413580247	9.24344135802465
16	140	138.918595679012	143.875	-4.95640432098766	1.08140432098762
17	155	151.747299382716	142.375	9.37229938271605	3.25270061728395
18	152	140.182484567901	141.416666666667	-1.23418209876543	11.8175154320988
19	137	140.159336419753	140.541666666667	-0.382330246913579	-3.15933641975312
20	127	138.673225308642	139.5	-0.826774691358022	-11.673225308642
21	134	139.131558641975	138.666666666667	0.464891975308641	-5.13155864197532
22	125	132.506558641975	138	-5.49344135802469	-7.50655864197535
23	132	145.284336419753	137.208333333333	8.07600308641976	-13.2843364197531
24	141	146.136188271605	136.25	9.88618827160494	-5.13618827160494
25	133	129.168595679012	135.458333333333	-6.289737654321	3.83140432098764
26	143	131.835262345679	134.958333333333	-3.12307098765432	11.1647376543210
27	141	128.839891975309	134.333333333333	-5.4934413580247	12.1601080246913
28	132	128.710262345679	133.666666666667	-4.95640432098766	3.28973765432099
29	144	142.622299382716	133.25	9.37229938271605	1.37770061728395
30	140	131.432484567901	132.666666666667	-1.23418209876543	8.56751543209876
31	130	131.367669753086	131.75	-0.382330246913579	-1.36766975308643
32	122	129.589891975309	130.416666666667	-0.826774691358022	-7.58989197530863
33	124	129.006558641975	128.541666666667	0.464891975308641	-5.0065586419753
34	119	121.048225308642	126.541666666667	-5.49344135802469	-2.04822530864196
35	128	132.492669753086	124.416666666667	8.07600308641976	-4.49266975308642
36	131	131.844521604938	121.958333333333	9.88618827160494	-0.844521604938265
37	121	113.251929012346	119.541666666667	-6.289737654321	7.74807098765432
38	123	114.293595679012	117.416666666667	-3.12307098765432	8.70640432098764
39	116	109.714891975309	115.208333333333	-5.4934413580247	6.28510802469137
40	109	107.543595679012	112.5	-4.95640432098766	1.45640432098766
41	116	118.872299382716	109.5	9.37229938271605	-2.87229938271604
42	109	105.224151234568	106.458333333333	-1.23418209876543	3.77584876543212
43	103	102.659336419753	103.041666666667	-0.382330246913579	0.340663580246925
44	98	98.3398919753086	99.1666666666667	-0.826774691358022	-0.339891975308632
45	95	96.0065586419753	95.5416666666666	0.464891975308641	-1.00655864197529
46	83	86.7148919753086	92.2083333333333	-5.49344135802469	-3.71489197530863
47	92	97.0760030864197	89	8.07600308641976	-5.07600308641973
48	94	95.5945216049383	85.7083333333333	9.88618827160494	-1.59452160493828
49	76	76.210262345679	82.5	-6.289737654321	-0.210262345679013
50	75	76.6685956790124	79.7916666666667	-3.12307098765432	-1.66859567901236
51	77	71.8815586419753	77.375	-5.4934413580247	5.1184413580247
52	68	70.5019290123457	75.4583333333333	-4.95640432098766	-2.50192901234567
53	80	83.2056327160494	73.8333333333333	9.37229938271605	-3.20563271604938
54	66	70.7658179012346	72	-1.23418209876543	-4.76581790123457
55	69	69.7426697530864	70.125	-0.382330246913579	-0.742669753086403
56	67	67.5898919753086	68.4166666666667	-0.826774691358022	-0.589891975308632
57	68	67.0898919753086	66.625	0.464891975308641	0.910108024691354
58	64	59.6315586419753	65.125	-5.49344135802469	4.3684413580247
59	72	72.1176697530864	64.0416666666667	8.07600308641976	-0.117669753086432
60	70	72.886188271605	63	9.88618827160494	-2.88618827160493
61	55	55.710262345679	62	-6.289737654321	-0.710262345679006
62	55	57.7935956790123	60.9166666666667	-3.12307098765432	-2.79359567901234
63	54	54.048225308642	59.5416666666667	-5.4934413580247	-0.0482253086419746
64	55	53.085262345679	58.0416666666667	-4.95640432098766	1.91473765432099
65	67	66.372299382716	57	9.37229938271605	0.627700617283942
66	54	54.9324845679012	56.1666666666667	-1.23418209876543	-0.932484567901241
67	57	54.5760030864198	54.9583333333333	-0.382330246913579	2.42399691358025
68	53	52.8398919753086	53.6666666666667	-0.826774691358022	0.160108024691361
69	49	52.8815586419753	52.4166666666667	0.464891975308641	-3.88155864197531
70	47	45.673225308642	51.1666666666667	-5.49344135802469	1.32677469135803
71	64	58.3676697530864	50.2916666666667	8.07600308641976	5.63233024691358
72	58	59.6778549382716	49.7916666666667	9.88618827160494	-1.6778549382716
73	38	43.1269290123457	49.4166666666667	-6.289737654321	-5.12692901234567
74	41	46.210262345679	49.3333333333333	-3.12307098765432	-5.21026234567902
75	38	44.2148919753086	49.7083333333333	-5.4934413580247	-6.21489197530864
76	41	45.2519290123457	50.2083333333333	-4.95640432098766	-4.25192901234568
77	60	59.9556327160494	50.5833333333333	9.37229938271605	0.0443672839506277
78	49	49.9324845679012	51.1666666666667	-1.23418209876543	-0.93248456790122
79	53	51.3260030864197	51.7083333333333	-0.382330246913579	1.67399691358025
80	55	51.2148919753086	52.0416666666667	-0.826774691358022	3.78510802469136
81	56	52.8398919753086	52.375	0.464891975308641	3.16010802469136
82	52	47.2565586419753	52.75	-5.49344135802469	4.74344135802469
83	68	61.1593364197531	53.0833333333333	8.07600308641976	6.8406635802469
84	68	63.0111882716049	53.125	9.88618827160494	4.98881172839507
85	41	46.7935956790123	53.0833333333333	-6.289737654321	-5.79359567901234
86	46	50.210262345679	53.3333333333333	-3.12307098765432	-4.21026234567901
87	41	48.2148919753086	53.7083333333333	-5.4934413580247	-7.21489197530864
88	47	48.6269290123457	53.5833333333333	-4.95640432098766	-1.62692901234566
89	62	62.747299382716	53.375	9.37229938271605	-0.747299382716044
90	48	52.2241512345679	53.4583333333333	-1.23418209876543	-4.2241512345679
91	53	53.1593364197531	53.5416666666667	-0.382330246913579	-0.159336419753082
92	61	52.5898919753086	53.4166666666667	-0.826774691358022	8.41010802469137
93	59	53.7565586419753	53.2916666666667	0.464891975308641	5.2434413580247
94	46	47.9648919753086	53.4583333333333	-5.49344135802469	-1.96489197530864
95	69	61.7426697530864	53.6666666666667	8.07600308641976	7.25733024691358
96	69	63.5945216049383	53.7083333333333	9.88618827160494	5.40547839506173
97	42	47.2935956790123	53.5833333333333	-6.289737654321	-5.29359567901234
98	42	50.585262345679	53.7083333333333	-3.12307098765432	-8.585262345679
99	42	48.6315586419753	54.125	-5.4934413580247	-6.6315586419753
100	50	49.5019290123457	54.4583333333333	-4.95640432098766	0.49807098765433
101	64	64.0389660493827	54.6666666666667	9.37229938271605	-0.0389660493827151
102	47	53.4741512345679	54.7083333333333	-1.23418209876543	-6.4741512345679
103	51	54.1593364197531	54.5416666666667	-0.382330246913579	-3.15933641975308
104	66	53.0898919753086	53.9166666666667	-0.826774691358022	12.9101080246914
105	64	53.048225308642	52.5833333333333	0.464891975308641	10.9517746913580
106	49	45.548225308642	51.0416666666667	-5.49344135802469	3.45177469135803
107	71	57.6593364197531	49.5833333333333	8.07600308641976	13.3406635802469
108	68	57.7611882716049	47.875	9.88618827160494	10.2388117283951
109	39	39.6269290123457	45.9166666666667	-6.289737654321	-0.62692901234567
110	30	40.9185956790123	44.0416666666667	-3.12307098765432	-10.9185956790123
111	22	36.5898919753086	42.0833333333333	-5.4934413580247	-14.5898919753086
112	33	34.7519290123457	39.7083333333333	-4.95640432098766	-1.75192901234567
113	46	46.3306327160494	36.9583333333333	9.37229938271605	-0.330632716049386
114	24	32.7241512345679	33.9583333333333	-1.23418209876543	-8.7241512345679
115	27	NA	NA	-0.382330246913579	NA
116	45	NA	NA	-0.826774691358022	NA
117	38	NA	NA	0.464891975308641	NA
118	18	NA	NA	-5.49344135802469	NA
119	36	NA	NA	8.07600308641976	NA
120	31	NA	NA	9.88618827160494	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/1ko1y1281116100.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/1ko1y1281116100.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/2ko1y1281116100.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/2ko1y1281116100.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/3vyj11281116100.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/3vyj11281116100.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/45pim1281116100.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/06/t1281116162j47soyitn3pmx53/45pim1281116100.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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