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

Title produced by software: Classical Decomposition

Date of computation: Fri, 04 Dec 2009 07:52:58 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil.htm/, Retrieved Fri, 04 Dec 2009 15:54:35 +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/2009/Dec/04/t1259938469akt76117z9mdlil.htm/},
    year = {2009},
}
@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 = {2009},
    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:

WS9

Dataseries X:

» Textbox « » Textfile « » CSV «

106370 109375 116476 123297 114813 117925 126466 131235 120546 123791 129813 133463 122987 125418 130199 133016 121454 122044 128313 131556 120027 123001 130111 132524 123742 124931 133646 136557 127509 128945 137191 139716 129083 131604 139413 143125 133948 137116 144864 149277 138796 143258 150034 154708 144888 148762 156500 161088 152772 158011 163318 169969 162269 165765 170600 174681 166364 170240 176150 182056 172218 177856 182253 188090 176863 183273 187969 194650 183036 189516 193805 200499 188142 193732 197126 205140 191751 196700 199784 207360 196101 200824 205743 212489 200810 203683 207286 210910 194915 217920

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	106370	NA	NA	-5397.39880952381	NA
2	109375	NA	NA	-2732.01190476190	NA
3	116476	117118.321428571	114934.875	2183.44642857143	-642.321428571435
4	123297	123004.964285714	117059	5945.96428571429	292.03571428571
5	114813	113979.101190476	119376.5	-5397.39880952381	833.898809523816
6	117925	118885.488095238	121617.5	-2732.01190476190	-960.488095238092
7	126466	125509.821428571	123326.375	2183.44642857143	956.178571428565
8	131235	130722.214285714	124776.25	5945.96428571429	512.78571428571
9	120546	120530.476190476	125927.875	-5397.39880952381	15.5238095238165
10	123791	123892.738095238	126624.75	-2732.01190476190	-101.738095238092
11	129813	129391.821428571	127208.375	2183.44642857143	421.178571428565
12	133463	133662.839285714	127716.875	5945.96428571429	-199.83928571429
13	122987	122571.101190476	127968.5	-5397.39880952381	415.898809523816
14	125418	125228.863095238	127960.875	-2732.01190476190	189.136904761908
15	130199	129896.821428571	127713.375	2183.44642857143	302.178571428565
16	133016	133045.964285714	127100	5945.96428571429	-29.9642857142899
17	121454	121045.101190476	126442.5	-5397.39880952381	408.898809523816
18	122044	123292.238095238	126024.25	-2732.01190476190	-1248.23809523809
19	128313	127846.821428571	125663.375	2183.44642857143	466.178571428565
20	131556	131550.589285714	125604.625	5945.96428571429	5.41071428571013
21	120027	120551.601190476	125949	-5397.39880952381	-524.601190476184
22	123001	123562.738095238	126294.75	-2732.01190476190	-561.738095238092
23	130111	129063.571428571	126880.125	2183.44642857143	1047.42857142857
24	132524	133531.714285714	127585.75	5945.96428571429	-1007.71428571429
25	123742	122871.476190476	128268.875	-5397.39880952381	870.523809523816
26	124931	126482.863095238	129214.875	-2732.01190476190	-1551.86309523809
27	133646	132373.321428571	130189.875	2183.44642857143	1272.67857142858
28	136557	137108.464285714	131162.5	5945.96428571429	-551.46428571429
29	127509	126709.976190476	132107.375	-5397.39880952381	799.023809523816
30	128945	130213.363095238	132945.375	-2732.01190476190	-1268.36309523811
31	137191	135720.446428571	133537	2183.44642857143	1470.55357142858
32	139716	140012.089285714	134066.125	5945.96428571429	-296.08928571429
33	129083	129278.851190476	134676.25	-5397.39880952381	-195.851190476184
34	131604	132648.113095238	135380.125	-2732.01190476190	-1044.11309523811
35	139413	138597.821428571	136414.375	2183.44642857143	815.17857142858
36	143125	143657.464285714	137711.5	5945.96428571429	-532.46428571429
37	133948	133684.476190476	139081.875	-5397.39880952381	263.523809523816
38	137116	137800.238095238	140532.25	-2732.01190476190	-684.238095238106
39	144864	144090.696428571	141907.25	2183.44642857143	773.30357142858
40	149277	149226.964285714	143281	5945.96428571429	50.0357142857101
41	138796	139297.601190476	144695	-5397.39880952381	-501.601190476184
42	143258	143288.113095238	146020.125	-2732.01190476190	-30.1130952381063
43	150034	149643.946428571	147460.5	2183.44642857143	390.05357142858
44	154708	154855.964285714	148910	5945.96428571429	-147.96428571429
45	144888	145008.851190476	150406.25	-5397.39880952381	-120.851190476184
46	148762	149279.988095238	152012	-2732.01190476190	-517.988095238106
47	156500	155978.446428571	153795	2183.44642857143	521.55357142858
48	161088	161882.589285714	155936.625	5945.96428571429	-794.58928571429
49	152772	152547.601190476	157945	-5397.39880952381	224.398809523816
50	158011	157175.363095238	159907.375	-2732.01190476190	835.636904761894
51	163318	164388.071428571	162204.625	2183.44642857143	-1070.07142857142
52	169969	170306.964285714	164361	5945.96428571429	-337.96428571429
53	162269	160843.101190476	166240.5	-5397.39880952381	1425.89880952382
54	165765	165007.738095238	167739.75	-2732.01190476190	757.261904761894
55	170600	171024.071428571	168840.625	2183.44642857143	-424.07142857142
56	174681	175857.839285714	169911.875	5945.96428571429	-1176.83928571429
57	166364	165767.601190476	171165	-5397.39880952381	596.398809523816
58	170240	170048.613095238	172780.625	-2732.01190476190	191.386904761894
59	176150	176617.696428571	174434.25	2183.44642857143	-467.69642857142
60	182056	182063.964285714	176118	5945.96428571429	-7.96428571428987
61	172218	172435.476190476	177832.875	-5397.39880952381	-217.476190476184
62	177856	176617.988095238	179350	-2732.01190476190	1238.01190476189
63	182253	182868.321428571	180684.875	2183.44642857143	-615.32142857142
64	188090	187888.589285714	181942.625	5945.96428571429	201.41071428571
65	176863	177936.851190476	183334.25	-5397.39880952381	-1073.85119047618
66	183273	182136.738095238	184868.75	-2732.01190476190	1136.26190476189
67	187969	188643.821428571	186460.375	2183.44642857143	-674.82142857142
68	194650	193958.339285714	188012.375	5945.96428571429	691.66071428571
69	183036	184124.851190476	189522.25	-5397.39880952381	-1088.85119047618
70	189516	188250.863095238	190982.875	-2732.01190476190	1265.13690476189
71	193805	194535.696428571	192352.25	2183.44642857143	-730.69642857142
72	200499	199463.464285714	193517.5	5945.96428571429	1035.53571428571
73	188142	189062.226190476	194459.625	-5397.39880952381	-920.226190476184
74	193732	192722.863095238	195454.875	-2732.01190476190	1009.13690476189
75	197126	198669.571428571	196486.125	2183.44642857143	-1543.57142857142
76	205140	203254.214285714	197308.25	5945.96428571429	1885.78571428571
77	191751	192614.101190476	198011.5	-5397.39880952381	-863.101190476184
78	196700	195889.238095238	198621.25	-2732.01190476190	810.761904761894
79	199784	201625.946428571	199442.5	2183.44642857143	-1841.94642857142
80	207360	206447.714285714	200501.75	5945.96428571429	912.28571428571
81	196101	196364.726190476	201762.125	-5397.39880952381	-263.726190476184
82	200824	200416.113095238	203148.125	-2732.01190476190	407.886904761894
83	205743	206561.321428571	204377.875	2183.44642857143	-818.32142857142
84	212489	211269.839285714	205323.875	5945.96428571429	1219.16071428571
85	200810	200476.726190476	205874.125	-5397.39880952381	333.273809523816
86	203683	203137.613095238	205869.625	-2732.01190476190	545.386904761894
87	207286	207118.821428571	204935.375	2183.44642857143	167.178571428580
88	210910	211924.089285714	205978.125	5945.96428571429	-1014.08928571429
89	194915	NA	NA	NA	NA
90	217920	NA	NA	NA	NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/1o5f61259938376.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/1o5f61259938376.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/24e1y1259938376.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/24e1y1259938376.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/3xzep1259938376.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/3xzep1259938376.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/4c7lx1259938376.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938469akt76117z9mdlil/4c7lx1259938376.ps (open in new window)

Parameters (Session):

par1 = additive ; par2 = 4 ;

Parameters (R input):

par1 = additive ; par2 = 4 ;

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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