Home » date » 2010 » Dec » 12 »

Eigen reeks (Opgave 9)

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 12 Dec 2010 21:01:00 +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/Dec/12/t1292188088qqcfjtrpk2jaxrm.htm/, Retrieved Sun, 12 Dec 2010 22:08:13 +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/Dec/12/t1292188088qqcfjtrpk2jaxrm.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:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

98.4 96.5 97.4 99.2 100.8 101.8 102.7 100 100.8 101.7 99 101.7 100.2 101.2 99.5 100.8 100.7 99.5 99.4 101.1 97.2 98.1 97.8 95.5 96.3 93.6 96.7 95.1 97.7 96.5 98.1 97.3 97 93.7 95.6 94.6 95.1 94.5 93.6 92.1 95.9 98.1 98.2 96.2 94.1 95 93.4 95.4 93.5 94.5 94.3 95.7 98.4 99.4 99.2 99 99.4 99.3 98.6 98.7 96 98.7 100.1 100 101.5 101.5 103.8 104.1 101 104.9 104.4 105.6 103.4 101.7 103.5 101.2 105.4 105.4 108.6 110.6 110.2 106.2 108.6 107.5 106.9 108.4 109.9 108.6 106.5 105.7 105.6 104.2 105.1 102.7 108.3 104.2 105.4 104.6 106.4 111 111.7 113.8 115.9 117.3 113.6 113.6 114.6 113.2 112.8 109.6 111.1 109.7 113 111 113.3 111.8 107.2 106.4 110 108.2 108.2

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	98.4	NA	NA	-1.24506172839507	NA
2	96.5	NA	NA	-1.65987654320988	NA
3	97.4	NA	NA	-0.821913580246914	NA
4	99.2	NA	NA	-0.9733024691358	NA
5	100.8	NA	NA	0.798456790123467	NA
6	101.8	NA	NA	0.728549382716051	NA
7	102.7	101.980864197531	100.075	1.90586419753087	0.71913580246914
8	100	102.207253086420	100.345833333333	1.86141975308642	-2.20725308641973
9	100.8	100.712345679012	100.629166666667	0.0831790123456801	0.0876543209876388
10	101.7	100.373456790123	100.783333333333	-0.409876543209883	1.32654320987656
11	99	101.287345679012	100.845833333333	0.441512345679011	-2.28734567901235
12	101.7	100.036882716049	100.745833333333	-0.708950617283948	1.66311728395064
13	100.2	99.267438271605	100.5125	-1.24506172839507	0.932561728395072
14	101.2	98.7609567901235	100.420833333333	-1.65987654320988	2.43904320987654
15	99.5	99.4947530864197	100.316666666667	-0.821913580246914	0.0052469135802653
16	100.8	99.0433641975308	100.016666666667	-0.9733024691358	1.75663580246916
17	100.7	100.615123456790	99.8166666666666	0.798456790123467	0.0848765432098872
18	99.5	100.236882716049	99.5083333333333	0.728549382716051	-0.73688271604938
19	99.4	100.993364197531	99.0875	1.90586419753087	-1.59336419753086
20	101.1	100.469753086420	98.6083333333333	1.86141975308642	0.630246913580251
21	97.2	98.2581790123457	98.175	0.0831790123456801	-1.05817901234568
22	98.1	97.4109567901234	97.8208333333333	-0.409876543209883	0.689043209876544
23	97.8	97.8998456790123	97.4583333333333	0.441512345679011	-0.0998456790123328
24	95.5	96.4993827160494	97.2083333333333	-0.708950617283948	-0.999382716049368
25	96.3	95.7841049382716	97.0291666666667	-1.24506172839507	0.515895061728415
26	93.6	95.1567901234568	96.8166666666666	-1.65987654320988	-1.55679012345678
27	96.7	95.828086419753	96.65	-0.821913580246914	0.87191358024694
28	95.1	95.4850308641975	96.4583333333333	-0.9733024691358	-0.385030864197518
29	97.7	96.9817901234568	96.1833333333333	0.798456790123467	0.718209876543227
30	96.5	96.7827160493827	96.0541666666667	0.728549382716051	-0.282716049382714
31	98.1	97.8725308641975	95.9666666666667	1.90586419753087	0.227469135802480
32	97.3	97.815586419753	95.9541666666667	1.86141975308642	-0.515586419753078
33	97	95.9456790123457	95.8625	0.0831790123456801	1.05432098765432
34	93.7	95.1984567901234	95.6083333333333	-0.409876543209883	-1.49845679012344
35	95.6	95.8498456790123	95.4083333333333	0.441512345679011	-0.249845679012353
36	94.6	94.691049382716	95.4	-0.708950617283948	-0.0910493827160366
37	95.1	94.2257716049383	95.4708333333333	-1.24506172839507	0.874228395061735
38	94.5	93.7692901234568	95.4291666666666	-1.65987654320988	0.73070987654323
39	93.6	94.4405864197531	95.2625	-0.821913580246914	-0.840586419753095
40	92.1	94.2225308641975	95.1958333333333	-0.9733024691358	-2.12253086419753
41	95.9	95.9567901234568	95.1583333333333	0.798456790123467	-0.0567901234567785
42	98.1	95.828549382716	95.1	0.728549382716051	2.27145061728395
43	98.2	96.9725308641975	95.0666666666667	1.90586419753087	1.22746913580248
44	96.2	96.8614197530864	95	1.86141975308642	-0.661419753086406
45	94.1	95.1123456790123	95.0291666666667	0.0831790123456801	-1.01234567901234
46	95	94.7984567901235	95.2083333333333	-0.409876543209883	0.201543209876547
47	93.4	95.904012345679	95.4625	0.441512345679011	-2.504012345679
48	95.4	94.9118827160494	95.6208333333333	-0.708950617283948	0.488117283950615
49	93.5	94.4716049382716	95.7166666666667	-1.24506172839507	-0.97160493827161
50	94.5	94.2151234567901	95.875	-1.65987654320988	0.284876543209876
51	94.3	95.3905864197531	96.2125	-0.821913580246914	-1.09058641975309
52	95.7	95.6391975308642	96.6125	-0.9733024691358	0.0608024691358082
53	98.4	97.8067901234568	97.0083333333333	0.798456790123467	0.593209876543213
54	99.4	98.091049382716	97.3625	0.728549382716051	1.30895061728397
55	99.2	99.5100308641975	97.6041666666666	1.90586419753087	-0.310030864197500
56	99	99.7447530864197	97.8833333333333	1.86141975308642	-0.744753086419735
57	99.4	98.3831790123457	98.3	0.0831790123456801	1.01682098765434
58	99.3	98.3109567901234	98.7208333333333	-0.409876543209883	0.98904320987657
59	98.6	99.4706790123457	99.0291666666667	0.441512345679011	-0.870679012345676
60	98.7	98.5368827160494	99.2458333333333	-0.708950617283948	0.163117283950641
61	96	98.279938271605	99.525	-1.24506172839507	-2.27993827160491
62	98.7	98.2692901234568	99.9291666666667	-1.65987654320988	0.430709876543204
63	100.1	99.3864197530864	100.208333333333	-0.821913580246914	0.71358024691358
64	100	99.5350308641975	100.508333333333	-0.9733024691358	0.464969135802491
65	101.5	101.781790123457	100.983333333333	0.798456790123467	-0.281790123456773
66	101.5	102.241049382716	101.5125	0.728549382716051	-0.741049382716028
67	103.8	104.014197530864	102.108333333333	1.90586419753087	-0.214197530864169
68	104.1	104.403086419753	102.541666666667	1.86141975308642	-0.303086419753058
69	101	102.891512345679	102.808333333333	0.0831790123456801	-1.89151234567899
70	104.9	102.590123456790	103	-0.409876543209883	2.30987654320991
71	104.4	103.654012345679	103.2125	0.441512345679011	0.745987654320984
72	105.6	102.828549382716	103.5375	-0.708950617283948	2.77145061728393
73	103.4	102.654938271605	103.9	-1.24506172839507	0.745061728395058
74	101.7	102.710956790123	104.370833333333	-1.65987654320988	-1.01095679012347
75	103.5	104.203086419753	105.025	-0.821913580246914	-0.703086419753078
76	101.2	104.489197530864	105.4625	-0.9733024691358	-3.2891975308642
77	105.4	106.490123456790	105.691666666667	0.798456790123467	-1.09012345679011
78	105.4	106.674382716049	105.945833333333	0.728549382716051	-1.27438271604937
79	108.6	108.076697530864	106.170833333333	1.90586419753087	0.5233024691358
80	110.6	108.457253086420	106.595833333333	1.86141975308642	2.14274691358025
81	110.2	107.224845679012	107.141666666667	0.0831790123456801	2.97515432098766
82	106.2	107.306790123457	107.716666666667	-0.409876543209883	-1.10679012345676
83	108.6	108.512345679012	108.070833333333	0.441512345679011	0.087654320987653
84	107.5	107.420216049383	108.129166666667	-0.708950617283948	0.0797839506172977
85	106.9	106.771604938272	108.016666666667	-1.24506172839507	0.128395061728412
86	108.4	105.96512345679	107.625	-1.65987654320988	2.43487654320990
87	109.9	106.323919753086	107.145833333333	-0.821913580246914	3.57608024691361
88	108.6	105.814197530864	106.7875	-0.9733024691358	2.78580246913582
89	106.5	107.427623456790	106.629166666667	0.798456790123467	-0.92762345679013
90	105.7	107.207716049383	106.479166666667	0.728549382716051	-1.50771604938271
91	105.6	108.185030864198	106.279166666667	1.90586419753087	-2.58503086419752
92	104.2	107.919753086420	106.058333333333	1.86141975308642	-3.71975308641973
93	105.1	105.837345679012	105.754166666667	0.0831790123456801	-0.73734567901235
94	102.7	105.298456790123	105.708333333333	-0.409876543209883	-2.59845679012344
95	108.3	106.466512345679	106.025	0.441512345679011	1.83348765432099
96	104.2	105.870216049383	106.579166666667	-0.708950617283948	-1.67021604938272
97	105.4	106.100771604938	107.345833333333	-1.24506172839507	-0.700771604938254
98	104.6	106.660956790123	108.320833333333	-1.65987654320988	-2.06095679012346
99	106.4	108.398919753086	109.220833333333	-0.821913580246914	-1.99891975308641
100	111	109.055864197531	110.029166666667	-0.9733024691358	1.94413580246913
101	111.7	111.544290123457	110.745833333333	0.798456790123467	0.155709876543213
102	113.8	112.111882716049	111.383333333333	0.728549382716051	1.68811728395062
103	115.9	113.972530864198	112.066666666667	1.90586419753087	1.92746913580250
104	117.3	114.444753086420	112.583333333333	1.86141975308642	2.85524691358026
105	113.6	113.070679012346	112.9875	0.0831790123456801	0.529320987654316
106	113.6	112.719290123457	113.129166666667	-0.409876543209883	0.880709876543207
107	114.6	113.570679012346	113.129166666667	0.441512345679011	1.02932098765433
108	113.2	112.357716049383	113.066666666667	-0.708950617283948	0.8422839506173
109	112.8	111.596604938272	112.841666666667	-1.24506172839507	1.20339506172841
110	109.6	110.844290123457	112.504166666667	-1.65987654320988	-1.24429012345679
111	111.1	111.186419753086	112.008333333333	-0.821913580246914	-0.0864197530864175
112	109.7	110.468364197531	111.441666666667	-0.9733024691358	-0.768364197530857
113	113	111.748456790123	110.95	0.798456790123467	1.25154320987654
114	111	111.278549382716	110.55	0.728549382716051	-0.278549382716065
115	113.3	112.055864197531	110.15	1.90586419753087	1.24413580246915
116	111.8	NA	NA	1.86141975308642	NA
117	107.2	NA	NA	0.0831790123456801	NA
118	106.4	NA	NA	-0.409876543209883	NA
119	110	NA	NA	0.441512345679011	NA
120	108.2	NA	NA	-0.708950617283948	NA
121	108.2	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/14wzt1292187656.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/14wzt1292187656.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/24wzt1292187656.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/24wzt1292187656.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/3f6hw1292187656.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/3f6hw1292187656.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/4f6hw1292187656.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Dec/12/t1292188088qqcfjtrpk2jaxrm/4f6hw1292187656.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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