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Classical decomposition - Koers BEL 20 van Januari 2000 tot Januari 2009 - Claus Wesley

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 01 Jun 2009 03:21:25 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n.htm/, Retrieved Mon, 01 Jun 2009 11:22:19 +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/2009/Jun/01/t1243848135wpktbb437dudg7n.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

3030,29 2803,47 2767,63 2882,6 2863,36 2897,06 3012,61 3142,95 3032,93 3045,78 3110,52 3013,24 2987,1 2995,55 2833,18 2848,96 2794,83 2845,26 2915,02 2892,63 2604,42 2641,65 2659,81 2638,53 2720,25 2745,88 2735,7 2811,7 2799,43 2555,28 2304,98 2214,95 2065,81 1940,49 2042 1995,37 1946,81 1765,9 1635,25 1833,42 1910,43 1959,67 1969,6 2061,41 2091,48 2120,88 2174,56 2196,72 2350,44 2440,25 2408,64 2472,81 2407,6 2452,62 2448,05 2497,84 2645,64 2756,76 2849,27 2921,44 2981,85 3080,58 3106,22 3119,31 3061,26 3097,31 3161,69 3257,16 3277,01 3295,32 3363,99 3494,17 3667,03 3813,06 3917,96 3895,51 3801,06 3570,12 3701,61 3862,27 3970,1 4138,52 4199,75 4290,89 4443,91 4502,64 4356,98 4591,27 4696,96 4621,4 4562,84 4202,52 4296,49 4435,23 4105,18 4116,68 3844,49 3720,98 3674,4 3857,62 3801,06 3504,37 3032,6 3047,03 2962,34 2197,82 2014,45 1862,83 1905,41

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	3030.29	NA	NA	20.4275824652778	NA
2	2803.47	NA	NA	36.1930512152779	NA
3	2767.63	NA	NA	-12.503459201389	NA
4	2882.6	NA	NA	87.5644053819447	NA
5	2863.36	NA	NA	77.9433116319444	NA
6	2897.06	NA	NA	6.31872829861102	NA
7	3012.61	2919.30966579861	2965.07041666667	-45.7607508680556	93.3003342013894
8	3142.95	2915.49461371528	2971.27416666667	-55.7795529513891	227.455386284722
9	3032.93	2928.85784288194	2982.00875	-53.1509071180558	104.072157118056
10	3045.78	2952.69581163194	2983.33833333333	-30.6425217013889	93.0841883680564
11	3110.52	2947.59831163194	2979.08125	-31.4829383680555	162.921688368056
12	3013.24	2974.94055121528	2974.0675	0.873051215277894	38.2994487847218
13	2987.1	2988.27049913194	2967.84291666667	20.4275824652778	-1.17049913194433
14	2995.55	2989.53971788195	2953.34666666667	36.1930512152779	6.01028211805487
15	2833.18	2912.55862413194	2925.06208333333	-12.503459201389	-79.3786241319444
16	2848.96	2977.93315538194	2890.36875	87.5644053819447	-128.973155381945
17	2794.83	2932.69372829861	2854.75041666667	77.9433116319444	-137.863728298612
18	2845.26	2826.67664496528	2820.35791666667	6.31872829861102	18.5833550347224
19	2915.02	2747.86549913194	2793.62625	-45.7607508680556	167.154500868056
20	2892.63	2716.32503038194	2772.10458333333	-55.7795529513891	176.304969618056
21	2604.42	2704.48909288194	2757.64	-53.1509071180558	-100.069092881944
22	2641.65	2721.38331163194	2752.02583333333	-30.6425217013889	-79.7333116319446
23	2659.81	2719.18206163195	2750.665	-31.4829383680555	-59.3720616319451
24	2638.53	2739.64721788194	2738.77416666667	0.873051215277894	-101.117217881945
25	2720.25	2721.70091579861	2701.27333333333	20.4275824652778	-1.45091579861037
26	2745.88	2683.81138454861	2647.61833333333	36.1930512152779	62.0686154513892
27	2735.7	2584.43612413194	2596.93958333333	-12.503459201389	151.263875868056
28	2811.7	2632.84690538194	2545.2825	87.5644053819447	178.853094618056
29	2799.43	2568.26872829861	2490.32541666667	77.9433116319444	231.161271701389
30	2555.28	2444.10372829861	2437.785	6.31872829861102	111.176271701389
31	2304.98	2332.99924913194	2378.76	-45.7607508680556	-28.0192491319444
32	2214.95	2249.92128038194	2305.70083333333	-55.7795529513891	-34.9712803819448
33	2065.81	2165.86534288194	2219.01625	-53.1509071180558	-100.055342881944
34	1940.49	2101.75997829861	2132.4025	-30.6425217013889	-161.269978298611
35	2042	2023.11622829861	2054.59916666667	-31.4829383680555	18.8837717013889
36	1995.37	1993.61346788194	1992.74041666667	0.873051215277894	1.75653211805547
37	1946.81	1974.37674913194	1953.94916666667	20.4275824652778	-27.5667491319443
38	1765.9	1969.77055121528	1933.5775	36.1930512152779	-203.870551215278
39	1635.25	1915.74612413194	1928.24958333333	-12.503459201389	-280.496124131944
40	1833.42	2024.39982204861	1936.83541666667	87.5644053819447	-190.979822048611
41	1910.43	2027.81831163194	1949.875	77.9433116319444	-117.388311631944
42	1959.67	1970.10664496528	1963.78791666667	6.31872829861102	-10.4366449652771
43	1969.6	1943.23466579861	1988.99541666667	-45.7607508680556	26.3653342013890
44	2061.41	1978.13169704861	2033.91125	-55.7795529513891	83.2783029513892
45	2091.48	2041.08284288194	2094.23375	-53.1509071180558	50.3971571180559
46	2120.88	2122.45706163194	2153.09958333333	-30.6425217013889	-1.57706163194371
47	2174.56	2168.97331163194	2200.45625	-31.4829383680555	5.58668836805509
48	2196.72	2242.58430121528	2241.71125	0.873051215277894	-45.8643012152775
49	2350.44	2302.61383246528	2282.18625	20.4275824652778	47.8261675347221
50	2440.25	2356.49930121528	2320.30625	36.1930512152779	83.7506987847223
51	2408.64	2349.07737413194	2361.58083333333	-12.503459201389	59.5626258680559
52	2472.81	2498.73023871528	2411.16583333333	87.5644053819447	-25.9202387152777
53	2407.6	2543.71706163194	2465.77375	77.9433116319444	-136.117061631945
54	2452.62	2530.40206163194	2524.08333333333	6.31872829861102	-77.7820616319445
55	2448.05	2534.82799913194	2580.58875	-45.7607508680556	-86.777999131944
56	2497.84	2577.79836371528	2633.57791666667	-55.7795529513891	-79.9583637152773
57	2645.64	2636.17325954861	2689.32416666667	-53.1509071180558	9.46674045138889
58	2756.76	2714.68497829861	2745.3275	-30.6425217013889	42.0750217013892
59	2849.27	2768.01789496528	2799.50083333333	-31.4829383680555	81.2521050347227
60	2921.44	2854.47180121528	2853.59875	0.873051215277894	66.9681987847225
61	2981.85	2930.62341579861	2910.19583333333	20.4275824652778	51.2265842013894
62	3080.58	3007.76221788194	2971.56916666667	36.1930512152779	72.8177821180557
63	3106.22	3017.01112413194	3029.51458333333	-12.503459201389	89.2088758680552
64	3119.31	3165.82607204861	3078.26166666667	87.5644053819447	-46.516072048611
65	3061.26	3200.09164496528	3122.14833333333	77.9433116319444	-138.831644965278
66	3097.31	3173.77747829861	3167.45875	6.31872829861102	-76.4674782986108
67	3161.69	3174.11091579861	3219.87166666667	-45.7607508680556	-12.4209157986111
68	3257.16	3223.16128038194	3278.94083333333	-55.7795529513891	33.9987196180559
69	3277.01	3290.13242621528	3343.28333333333	-53.1509071180558	-13.1224262152773
70	3295.32	3378.80497829861	3409.4475	-30.6425217013889	-83.4849782986107
71	3363.99	3441.13122829861	3472.61416666667	-31.4829383680555	-77.1412282986112
72	3494.17	3524.01263454861	3523.13958333333	0.873051215277894	-29.8426345486114
73	3667.03	3585.76424913194	3565.33666666667	20.4275824652778	81.2657508680559
74	3813.06	3649.23930121528	3613.04625	36.1930512152779	163.820698784722
75	3917.96	3654.63445746528	3667.13791666667	-12.503459201389	263.325542534722
76	3895.51	3818.71440538194	3731.15	87.5644053819447	76.7955946180555
77	3801.06	3879.04997829861	3801.10666666667	77.9433116319444	-77.9899782986113
78	3570.12	3875.44539496528	3869.12666666667	6.31872829861102	-305.325394965278
79	3701.61	3888.93258246528	3934.69333333333	-45.7607508680556	-187.322582465278
80	3862.27	3940.01628038194	3995.79583333333	-55.7795529513891	-77.7462803819449
81	3970.1	3989.66992621528	4042.82083333333	-53.1509071180558	-19.5699262152780
82	4138.52	4059.46081163194	4090.10333333333	-30.6425217013889	79.0591883680563
83	4199.75	4124.93956163194	4156.4225	-31.4829383680555	74.8104383680557
84	4290.89	4238.42805121528	4237.555	0.873051215277894	52.4619487847231
85	4443.91	4337.67049913194	4317.24291666667	20.4275824652778	106.239500868056
86	4502.64	4403.49763454861	4367.30458333333	36.1930512152779	99.14236545139
87	4356.98	4382.57779079861	4395.08125	-12.503459201389	-25.5977907986116
88	4591.27	4508.60815538194	4421.04375	87.5644053819447	82.6618446180555
89	4696.96	4507.40956163194	4429.46625	77.9433116319444	189.550438368056
90	4621.4	4424.58581163195	4418.26708333333	6.31872829861102	196.814188368055
91	4562.84	4340.27174913194	4386.0325	-45.7607508680556	222.568250868057
92	4202.52	4272.70794704861	4328.4875	-55.7795529513891	-70.187947048611
93	4296.49	4214.32659288194	4267.4775	-53.1509071180558	82.1634071180551
94	4435.23	4177.82539496528	4208.46791666667	-30.6425217013889	257.404605034721
95	4105.18	4109.08706163195	4140.57	-31.4829383680555	-3.907061631945
96	4116.68	4057.57096788194	4056.69791666667	0.873051215277894	59.1090321180554
97	3844.49	3966.82258246528	3946.395	20.4275824652778	-122.332582465278
98	3720.98	3870.68263454861	3834.48958333333	36.1930512152779	-149.702634548612
99	3674.4	3718.25112413194	3730.75458333333	-12.503459201389	-43.8511241319443
100	3857.62	3669.50398871528	3581.93958333333	87.5644053819447	188.116011284722
101	3801.06	3479.54372829861	3401.60041666667	77.9433116319444	321.516271701389
102	3504.37	3226.89497829861	3220.57625	6.31872829861102	277.47502170139
103	3032.6	3000.11008246528	3045.87083333333	-45.7607508680556	32.4899175347227
104	3047.03	NA	NA	-55.7795529513891	NA
105	2962.34	NA	NA	-53.1509071180558	NA
106	2197.82	NA	NA	-30.6425217013889	NA
107	2014.45	NA	NA	-31.4829383680555	NA
108	1862.83	NA	NA	0.873051215277894	NA
109	1905.41	NA	NA	NA	NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/1cob71243848083.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/1cob71243848083.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/298vv1243848083.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/298vv1243848083.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/3kei31243848083.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/3kei31243848083.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/4z1ix1243848083.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/01/t1243848135wpktbb437dudg7n/4z1ix1243848083.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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