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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 06 Jun 2010 15:57:00 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/06/t1275839925vpcov2o81ilgui2.htm/, Retrieved Sat, 27 Apr 2024 21:46:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77732, Retrieved Sat, 27 Apr 2024 21:46:00 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W52

Estimated Impact

105

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Verbruik zonne-en...] [2010-06-06 15:57:00] [dd2ef098fd65ce7e9f689caa343b799f] [Current]

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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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77732&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77732&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77732&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

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	5.074	NA	NA	0.986490971516826	NA
2	4.643	NA	NA	0.90952257528937	NA
3	5.451	NA	NA	1.03225635717524	NA
4	5.397	NA	NA	1.01661998319296	NA
5	5.635	NA	NA	1.07622189976605	NA
6	5.708	NA	NA	1.05398534932221	NA
7	5.578	5.61083828506803	5.30270833333333	1.05810803317199	0.994147347793747
8	5.574	5.61933994771643	5.30883333333333	1.05848867253629	0.991931446017098
9	5.352	5.30811489987963	5.31608333333333	0.998501070627742	1.00826754901658
10	5.302	5.22262816292635	5.31783333333333	0.98209699995481	1.01519768105206
11	4.923	4.85065769828212	5.32395833333333	0.91109986115258	1.01491391605380
12	4.982	4.88556003815607	5.33004166666667	0.916608226293928	1.01973979668467
13	5.101	5.26654646660449	5.33866666666667	0.986490971516826	0.968566409191634
14	4.763	4.86893962294179	5.35329166666667	0.90952257528937	0.978241746428193
15	5.505	5.53461450172126	5.36166666666667	1.03225635717524	0.994649220517156
16	5.385	5.45412385066427	5.36495833333333	1.01661998319296	0.987326314444463
17	5.794	5.77630714894018	5.36720833333333	1.07622189976605	1.00306300385413
18	5.695	5.66205321261514	5.37204166666667	1.05398534932221	1.00581887632413
19	5.798	5.69328253598601	5.380625	1.05810803317199	1.01839316130055
20	5.705	5.7021225826477	5.38704166666667	1.05848867253629	1.00050462214914
21	5.422	5.38083906119035	5.38891666666667	0.998501070627742	1.00764953910377
22	5.311	5.30090947796441	5.39754166666667	0.98209699995481	1.00190354543452
23	4.968	4.93091041105198	5.41204166666667	0.91109986115258	1.00752185415190
24	5.053	4.973707195918	5.42620833333333	0.916608226293928	1.01594239486938
25	5.236	5.36305816665122	5.4365	0.986490971516826	0.976308635352624
26	4.782	4.95511688695046	5.44804166666667	0.90952257528937	0.965063006403266
27	5.531	5.63990465015313	5.46366666666667	1.03225635717524	0.980690338417303
28	5.566	5.5708657120676	5.47979166666667	1.01661998319296	0.999126578826509
29	5.961	5.91352544116035	5.49470833333333	1.07622189976605	1.00802813132572
30	5.868	5.80306766914321	5.50583333333333	1.05398534932221	1.01118931133649
31	5.872	5.8576419838054	5.53595833333333	1.05810803317199	1.00245115973873
32	5.908	5.91112999177893	5.5845	1.05848867253629	0.999470491803887
33	5.594	5.62077054761994	5.62920833333333	0.998501070627742	0.995237210380118
34	5.526	5.5685309104521	5.67004166666667	0.98209699995481	0.992362274514402
35	5.111	5.20089966990686	5.708375	0.91109986115258	0.982714592548857
36	5.177	5.26262974724773	5.74141666666667	0.916608226293928	0.983728715231673
37	5.835	5.68901122515657	5.76691666666667	0.986490971516826	1.02566153749141
38	5.348	5.27875533665759	5.803875	0.90952257528937	1.01311761180927
39	6.038	6.03775345448109	5.84908333333333	1.03225635717524	1.00004083398250
40	6.039	5.98712923601915	5.88925	1.01661998319296	1.00866371209574
41	6.408	6.38598685515765	5.93370833333333	1.07622189976605	1.00344710149608
42	6.214	6.30335938162149	5.9805	1.05398534932221	0.985823530563396
43	6.138	6.3813172845561	6.030875	1.05810803317199	0.961870367244555
44	6.529	6.43834555809139	6.08258333333333	1.05848867253629	1.01408039396001
45	6.058	6.13129582418965	6.1405	0.998501070627742	0.988045622607136
46	6.026	6.09018810026143	6.20120833333333	0.98209699995481	0.989460407592555
47	5.678	5.70458604314737	6.26120833333333	0.91109986115258	0.995339531572267
48	5.733	5.79873098360139	6.32629166666667	0.916608226293928	0.988664591651643
49	6.488	6.3167894171556	6.40329166666667	0.986490971516826	1.02710405105154
50	5.936	5.88631641695089	6.471875	0.90952257528937	1.00844052197161
51	6.84	6.73856949963998	6.528	1.03225635717524	1.01505223035326
52	6.694	6.70401576083405	6.59441666666667	1.01661998319296	0.998506005774544
53	7.193	7.16611320475056	6.65858333333333	1.07622189976605	1.00375193560040
54	6.991	7.07948784322863	6.716875	1.05398534932221	0.987500812885318
55	7.209	7.16643344516971	6.772875	1.05810803317199	1.00593971257195
56	7.104	7.23997431275887	6.83991666666667	1.05848867253629	0.981218950940303
57	6.83	6.90471811181339	6.91508333333333	0.998501070627742	0.989178687586746
58	6.848	6.86453066401746	6.98966666666667	0.98209699995481	0.997591872652836
59	6.396	6.43187150731242	7.05945833333333	0.91109986115258	0.994422850756326
60	6.414	6.53973235054118	7.13470833333333	0.916608226293928	0.980774083127305
61	7.151	7.11979306797029	7.21729166666667	0.986490971516826	1.00438312346044
62	6.882	6.6354219480236	7.2955	0.90952257528937	1.03716086993531
63	7.698	7.60979386509589	7.372	1.03225635717524	1.01159113327743
64	7.626	7.56246661830857	7.43883333333333	1.01661998319296	1.00840114540640
65	7.936	8.06722483290885	7.495875	1.07622189976605	0.983733584271317
66	8.054	7.96092700765555	7.55316666666667	1.05398534932221	1.01169122543831
67	8.128	8.02076750628666	7.58029166666667	1.05810803317199	1.01336935569187
68	8.062	8.00795194837864	7.56545833333333	1.05848867253629	1.00674929769431
69	7.708	7.54271869173324	7.55404166666667	0.998501070627742	1.02191269686988
70	7.574	7.42035664528355	7.555625	0.98209699995481	1.02070565635334
71	7.039	6.88730755040606	7.55933333333333	0.91109986115258	1.0220249275183
72	7.146	6.91829154800057	7.54770833333333	0.916608226293928	1.03291397166765
73	7.07	NA	7.53220833333333	NA	NA
74	6.607	NA	7.52908333333333	NA	NA
75	7.699	NA	7.51325	NA	NA
76	7.663	NA	NA	NA	NA
77	7.988	NA	NA	NA	NA
78	7.723	NA	NA	NA	NA
79	8.087	NA	NA	NA	NA
80	8.028	NA	NA	NA	NA
81	7.362	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 5.074 & NA & NA & 0.986490971516826 & NA \tabularnewline
2 & 4.643 & NA & NA & 0.90952257528937 & NA \tabularnewline
3 & 5.451 & NA & NA & 1.03225635717524 & NA \tabularnewline
4 & 5.397 & NA & NA & 1.01661998319296 & NA \tabularnewline
5 & 5.635 & NA & NA & 1.07622189976605 & NA \tabularnewline
6 & 5.708 & NA & NA & 1.05398534932221 & NA \tabularnewline
7 & 5.578 & 5.61083828506803 & 5.30270833333333 & 1.05810803317199 & 0.994147347793747 \tabularnewline
8 & 5.574 & 5.61933994771643 & 5.30883333333333 & 1.05848867253629 & 0.991931446017098 \tabularnewline
9 & 5.352 & 5.30811489987963 & 5.31608333333333 & 0.998501070627742 & 1.00826754901658 \tabularnewline
10 & 5.302 & 5.22262816292635 & 5.31783333333333 & 0.98209699995481 & 1.01519768105206 \tabularnewline
11 & 4.923 & 4.85065769828212 & 5.32395833333333 & 0.91109986115258 & 1.01491391605380 \tabularnewline
12 & 4.982 & 4.88556003815607 & 5.33004166666667 & 0.916608226293928 & 1.01973979668467 \tabularnewline
13 & 5.101 & 5.26654646660449 & 5.33866666666667 & 0.986490971516826 & 0.968566409191634 \tabularnewline
14 & 4.763 & 4.86893962294179 & 5.35329166666667 & 0.90952257528937 & 0.978241746428193 \tabularnewline
15 & 5.505 & 5.53461450172126 & 5.36166666666667 & 1.03225635717524 & 0.994649220517156 \tabularnewline
16 & 5.385 & 5.45412385066427 & 5.36495833333333 & 1.01661998319296 & 0.987326314444463 \tabularnewline
17 & 5.794 & 5.77630714894018 & 5.36720833333333 & 1.07622189976605 & 1.00306300385413 \tabularnewline
18 & 5.695 & 5.66205321261514 & 5.37204166666667 & 1.05398534932221 & 1.00581887632413 \tabularnewline
19 & 5.798 & 5.69328253598601 & 5.380625 & 1.05810803317199 & 1.01839316130055 \tabularnewline
20 & 5.705 & 5.7021225826477 & 5.38704166666667 & 1.05848867253629 & 1.00050462214914 \tabularnewline
21 & 5.422 & 5.38083906119035 & 5.38891666666667 & 0.998501070627742 & 1.00764953910377 \tabularnewline
22 & 5.311 & 5.30090947796441 & 5.39754166666667 & 0.98209699995481 & 1.00190354543452 \tabularnewline
23 & 4.968 & 4.93091041105198 & 5.41204166666667 & 0.91109986115258 & 1.00752185415190 \tabularnewline
24 & 5.053 & 4.973707195918 & 5.42620833333333 & 0.916608226293928 & 1.01594239486938 \tabularnewline
25 & 5.236 & 5.36305816665122 & 5.4365 & 0.986490971516826 & 0.976308635352624 \tabularnewline
26 & 4.782 & 4.95511688695046 & 5.44804166666667 & 0.90952257528937 & 0.965063006403266 \tabularnewline
27 & 5.531 & 5.63990465015313 & 5.46366666666667 & 1.03225635717524 & 0.980690338417303 \tabularnewline
28 & 5.566 & 5.5708657120676 & 5.47979166666667 & 1.01661998319296 & 0.999126578826509 \tabularnewline
29 & 5.961 & 5.91352544116035 & 5.49470833333333 & 1.07622189976605 & 1.00802813132572 \tabularnewline
30 & 5.868 & 5.80306766914321 & 5.50583333333333 & 1.05398534932221 & 1.01118931133649 \tabularnewline
31 & 5.872 & 5.8576419838054 & 5.53595833333333 & 1.05810803317199 & 1.00245115973873 \tabularnewline
32 & 5.908 & 5.91112999177893 & 5.5845 & 1.05848867253629 & 0.999470491803887 \tabularnewline
33 & 5.594 & 5.62077054761994 & 5.62920833333333 & 0.998501070627742 & 0.995237210380118 \tabularnewline
34 & 5.526 & 5.5685309104521 & 5.67004166666667 & 0.98209699995481 & 0.992362274514402 \tabularnewline
35 & 5.111 & 5.20089966990686 & 5.708375 & 0.91109986115258 & 0.982714592548857 \tabularnewline
36 & 5.177 & 5.26262974724773 & 5.74141666666667 & 0.916608226293928 & 0.983728715231673 \tabularnewline
37 & 5.835 & 5.68901122515657 & 5.76691666666667 & 0.986490971516826 & 1.02566153749141 \tabularnewline
38 & 5.348 & 5.27875533665759 & 5.803875 & 0.90952257528937 & 1.01311761180927 \tabularnewline
39 & 6.038 & 6.03775345448109 & 5.84908333333333 & 1.03225635717524 & 1.00004083398250 \tabularnewline
40 & 6.039 & 5.98712923601915 & 5.88925 & 1.01661998319296 & 1.00866371209574 \tabularnewline
41 & 6.408 & 6.38598685515765 & 5.93370833333333 & 1.07622189976605 & 1.00344710149608 \tabularnewline
42 & 6.214 & 6.30335938162149 & 5.9805 & 1.05398534932221 & 0.985823530563396 \tabularnewline
43 & 6.138 & 6.3813172845561 & 6.030875 & 1.05810803317199 & 0.961870367244555 \tabularnewline
44 & 6.529 & 6.43834555809139 & 6.08258333333333 & 1.05848867253629 & 1.01408039396001 \tabularnewline
45 & 6.058 & 6.13129582418965 & 6.1405 & 0.998501070627742 & 0.988045622607136 \tabularnewline
46 & 6.026 & 6.09018810026143 & 6.20120833333333 & 0.98209699995481 & 0.989460407592555 \tabularnewline
47 & 5.678 & 5.70458604314737 & 6.26120833333333 & 0.91109986115258 & 0.995339531572267 \tabularnewline
48 & 5.733 & 5.79873098360139 & 6.32629166666667 & 0.916608226293928 & 0.988664591651643 \tabularnewline
49 & 6.488 & 6.3167894171556 & 6.40329166666667 & 0.986490971516826 & 1.02710405105154 \tabularnewline
50 & 5.936 & 5.88631641695089 & 6.471875 & 0.90952257528937 & 1.00844052197161 \tabularnewline
51 & 6.84 & 6.73856949963998 & 6.528 & 1.03225635717524 & 1.01505223035326 \tabularnewline
52 & 6.694 & 6.70401576083405 & 6.59441666666667 & 1.01661998319296 & 0.998506005774544 \tabularnewline
53 & 7.193 & 7.16611320475056 & 6.65858333333333 & 1.07622189976605 & 1.00375193560040 \tabularnewline
54 & 6.991 & 7.07948784322863 & 6.716875 & 1.05398534932221 & 0.987500812885318 \tabularnewline
55 & 7.209 & 7.16643344516971 & 6.772875 & 1.05810803317199 & 1.00593971257195 \tabularnewline
56 & 7.104 & 7.23997431275887 & 6.83991666666667 & 1.05848867253629 & 0.981218950940303 \tabularnewline
57 & 6.83 & 6.90471811181339 & 6.91508333333333 & 0.998501070627742 & 0.989178687586746 \tabularnewline
58 & 6.848 & 6.86453066401746 & 6.98966666666667 & 0.98209699995481 & 0.997591872652836 \tabularnewline
59 & 6.396 & 6.43187150731242 & 7.05945833333333 & 0.91109986115258 & 0.994422850756326 \tabularnewline
60 & 6.414 & 6.53973235054118 & 7.13470833333333 & 0.916608226293928 & 0.980774083127305 \tabularnewline
61 & 7.151 & 7.11979306797029 & 7.21729166666667 & 0.986490971516826 & 1.00438312346044 \tabularnewline
62 & 6.882 & 6.6354219480236 & 7.2955 & 0.90952257528937 & 1.03716086993531 \tabularnewline
63 & 7.698 & 7.60979386509589 & 7.372 & 1.03225635717524 & 1.01159113327743 \tabularnewline
64 & 7.626 & 7.56246661830857 & 7.43883333333333 & 1.01661998319296 & 1.00840114540640 \tabularnewline
65 & 7.936 & 8.06722483290885 & 7.495875 & 1.07622189976605 & 0.983733584271317 \tabularnewline
66 & 8.054 & 7.96092700765555 & 7.55316666666667 & 1.05398534932221 & 1.01169122543831 \tabularnewline
67 & 8.128 & 8.02076750628666 & 7.58029166666667 & 1.05810803317199 & 1.01336935569187 \tabularnewline
68 & 8.062 & 8.00795194837864 & 7.56545833333333 & 1.05848867253629 & 1.00674929769431 \tabularnewline
69 & 7.708 & 7.54271869173324 & 7.55404166666667 & 0.998501070627742 & 1.02191269686988 \tabularnewline
70 & 7.574 & 7.42035664528355 & 7.555625 & 0.98209699995481 & 1.02070565635334 \tabularnewline
71 & 7.039 & 6.88730755040606 & 7.55933333333333 & 0.91109986115258 & 1.0220249275183 \tabularnewline
72 & 7.146 & 6.91829154800057 & 7.54770833333333 & 0.916608226293928 & 1.03291397166765 \tabularnewline
73 & 7.07 & NA & 7.53220833333333 & NA & NA \tabularnewline
74 & 6.607 & NA & 7.52908333333333 & NA & NA \tabularnewline
75 & 7.699 & NA & 7.51325 & NA & NA \tabularnewline
76 & 7.663 & NA & NA & NA & NA \tabularnewline
77 & 7.988 & NA & NA & NA & NA \tabularnewline
78 & 7.723 & NA & NA & NA & NA \tabularnewline
79 & 8.087 & NA & NA & NA & NA \tabularnewline
80 & 8.028 & NA & NA & NA & NA \tabularnewline
81 & 7.362 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77732&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]5.074[/C][C]NA[/C][C]NA[/C][C]0.986490971516826[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]4.643[/C][C]NA[/C][C]NA[/C][C]0.90952257528937[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5.451[/C][C]NA[/C][C]NA[/C][C]1.03225635717524[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]5.397[/C][C]NA[/C][C]NA[/C][C]1.01661998319296[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5.635[/C][C]NA[/C][C]NA[/C][C]1.07622189976605[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]5.708[/C][C]NA[/C][C]NA[/C][C]1.05398534932221[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]5.578[/C][C]5.61083828506803[/C][C]5.30270833333333[/C][C]1.05810803317199[/C][C]0.994147347793747[/C][/ROW]
[ROW][C]8[/C][C]5.574[/C][C]5.61933994771643[/C][C]5.30883333333333[/C][C]1.05848867253629[/C][C]0.991931446017098[/C][/ROW]
[ROW][C]9[/C][C]5.352[/C][C]5.30811489987963[/C][C]5.31608333333333[/C][C]0.998501070627742[/C][C]1.00826754901658[/C][/ROW]
[ROW][C]10[/C][C]5.302[/C][C]5.22262816292635[/C][C]5.31783333333333[/C][C]0.98209699995481[/C][C]1.01519768105206[/C][/ROW]
[ROW][C]11[/C][C]4.923[/C][C]4.85065769828212[/C][C]5.32395833333333[/C][C]0.91109986115258[/C][C]1.01491391605380[/C][/ROW]
[ROW][C]12[/C][C]4.982[/C][C]4.88556003815607[/C][C]5.33004166666667[/C][C]0.916608226293928[/C][C]1.01973979668467[/C][/ROW]
[ROW][C]13[/C][C]5.101[/C][C]5.26654646660449[/C][C]5.33866666666667[/C][C]0.986490971516826[/C][C]0.968566409191634[/C][/ROW]
[ROW][C]14[/C][C]4.763[/C][C]4.86893962294179[/C][C]5.35329166666667[/C][C]0.90952257528937[/C][C]0.978241746428193[/C][/ROW]
[ROW][C]15[/C][C]5.505[/C][C]5.53461450172126[/C][C]5.36166666666667[/C][C]1.03225635717524[/C][C]0.994649220517156[/C][/ROW]
[ROW][C]16[/C][C]5.385[/C][C]5.45412385066427[/C][C]5.36495833333333[/C][C]1.01661998319296[/C][C]0.987326314444463[/C][/ROW]
[ROW][C]17[/C][C]5.794[/C][C]5.77630714894018[/C][C]5.36720833333333[/C][C]1.07622189976605[/C][C]1.00306300385413[/C][/ROW]
[ROW][C]18[/C][C]5.695[/C][C]5.66205321261514[/C][C]5.37204166666667[/C][C]1.05398534932221[/C][C]1.00581887632413[/C][/ROW]
[ROW][C]19[/C][C]5.798[/C][C]5.69328253598601[/C][C]5.380625[/C][C]1.05810803317199[/C][C]1.01839316130055[/C][/ROW]
[ROW][C]20[/C][C]5.705[/C][C]5.7021225826477[/C][C]5.38704166666667[/C][C]1.05848867253629[/C][C]1.00050462214914[/C][/ROW]
[ROW][C]21[/C][C]5.422[/C][C]5.38083906119035[/C][C]5.38891666666667[/C][C]0.998501070627742[/C][C]1.00764953910377[/C][/ROW]
[ROW][C]22[/C][C]5.311[/C][C]5.30090947796441[/C][C]5.39754166666667[/C][C]0.98209699995481[/C][C]1.00190354543452[/C][/ROW]
[ROW][C]23[/C][C]4.968[/C][C]4.93091041105198[/C][C]5.41204166666667[/C][C]0.91109986115258[/C][C]1.00752185415190[/C][/ROW]
[ROW][C]24[/C][C]5.053[/C][C]4.973707195918[/C][C]5.42620833333333[/C][C]0.916608226293928[/C][C]1.01594239486938[/C][/ROW]
[ROW][C]25[/C][C]5.236[/C][C]5.36305816665122[/C][C]5.4365[/C][C]0.986490971516826[/C][C]0.976308635352624[/C][/ROW]
[ROW][C]26[/C][C]4.782[/C][C]4.95511688695046[/C][C]5.44804166666667[/C][C]0.90952257528937[/C][C]0.965063006403266[/C][/ROW]
[ROW][C]27[/C][C]5.531[/C][C]5.63990465015313[/C][C]5.46366666666667[/C][C]1.03225635717524[/C][C]0.980690338417303[/C][/ROW]
[ROW][C]28[/C][C]5.566[/C][C]5.5708657120676[/C][C]5.47979166666667[/C][C]1.01661998319296[/C][C]0.999126578826509[/C][/ROW]
[ROW][C]29[/C][C]5.961[/C][C]5.91352544116035[/C][C]5.49470833333333[/C][C]1.07622189976605[/C][C]1.00802813132572[/C][/ROW]
[ROW][C]30[/C][C]5.868[/C][C]5.80306766914321[/C][C]5.50583333333333[/C][C]1.05398534932221[/C][C]1.01118931133649[/C][/ROW]
[ROW][C]31[/C][C]5.872[/C][C]5.8576419838054[/C][C]5.53595833333333[/C][C]1.05810803317199[/C][C]1.00245115973873[/C][/ROW]
[ROW][C]32[/C][C]5.908[/C][C]5.91112999177893[/C][C]5.5845[/C][C]1.05848867253629[/C][C]0.999470491803887[/C][/ROW]
[ROW][C]33[/C][C]5.594[/C][C]5.62077054761994[/C][C]5.62920833333333[/C][C]0.998501070627742[/C][C]0.995237210380118[/C][/ROW]
[ROW][C]34[/C][C]5.526[/C][C]5.5685309104521[/C][C]5.67004166666667[/C][C]0.98209699995481[/C][C]0.992362274514402[/C][/ROW]
[ROW][C]35[/C][C]5.111[/C][C]5.20089966990686[/C][C]5.708375[/C][C]0.91109986115258[/C][C]0.982714592548857[/C][/ROW]
[ROW][C]36[/C][C]5.177[/C][C]5.26262974724773[/C][C]5.74141666666667[/C][C]0.916608226293928[/C][C]0.983728715231673[/C][/ROW]
[ROW][C]37[/C][C]5.835[/C][C]5.68901122515657[/C][C]5.76691666666667[/C][C]0.986490971516826[/C][C]1.02566153749141[/C][/ROW]
[ROW][C]38[/C][C]5.348[/C][C]5.27875533665759[/C][C]5.803875[/C][C]0.90952257528937[/C][C]1.01311761180927[/C][/ROW]
[ROW][C]39[/C][C]6.038[/C][C]6.03775345448109[/C][C]5.84908333333333[/C][C]1.03225635717524[/C][C]1.00004083398250[/C][/ROW]
[ROW][C]40[/C][C]6.039[/C][C]5.98712923601915[/C][C]5.88925[/C][C]1.01661998319296[/C][C]1.00866371209574[/C][/ROW]
[ROW][C]41[/C][C]6.408[/C][C]6.38598685515765[/C][C]5.93370833333333[/C][C]1.07622189976605[/C][C]1.00344710149608[/C][/ROW]
[ROW][C]42[/C][C]6.214[/C][C]6.30335938162149[/C][C]5.9805[/C][C]1.05398534932221[/C][C]0.985823530563396[/C][/ROW]
[ROW][C]43[/C][C]6.138[/C][C]6.3813172845561[/C][C]6.030875[/C][C]1.05810803317199[/C][C]0.961870367244555[/C][/ROW]
[ROW][C]44[/C][C]6.529[/C][C]6.43834555809139[/C][C]6.08258333333333[/C][C]1.05848867253629[/C][C]1.01408039396001[/C][/ROW]
[ROW][C]45[/C][C]6.058[/C][C]6.13129582418965[/C][C]6.1405[/C][C]0.998501070627742[/C][C]0.988045622607136[/C][/ROW]
[ROW][C]46[/C][C]6.026[/C][C]6.09018810026143[/C][C]6.20120833333333[/C][C]0.98209699995481[/C][C]0.989460407592555[/C][/ROW]
[ROW][C]47[/C][C]5.678[/C][C]5.70458604314737[/C][C]6.26120833333333[/C][C]0.91109986115258[/C][C]0.995339531572267[/C][/ROW]
[ROW][C]48[/C][C]5.733[/C][C]5.79873098360139[/C][C]6.32629166666667[/C][C]0.916608226293928[/C][C]0.988664591651643[/C][/ROW]
[ROW][C]49[/C][C]6.488[/C][C]6.3167894171556[/C][C]6.40329166666667[/C][C]0.986490971516826[/C][C]1.02710405105154[/C][/ROW]
[ROW][C]50[/C][C]5.936[/C][C]5.88631641695089[/C][C]6.471875[/C][C]0.90952257528937[/C][C]1.00844052197161[/C][/ROW]
[ROW][C]51[/C][C]6.84[/C][C]6.73856949963998[/C][C]6.528[/C][C]1.03225635717524[/C][C]1.01505223035326[/C][/ROW]
[ROW][C]52[/C][C]6.694[/C][C]6.70401576083405[/C][C]6.59441666666667[/C][C]1.01661998319296[/C][C]0.998506005774544[/C][/ROW]
[ROW][C]53[/C][C]7.193[/C][C]7.16611320475056[/C][C]6.65858333333333[/C][C]1.07622189976605[/C][C]1.00375193560040[/C][/ROW]
[ROW][C]54[/C][C]6.991[/C][C]7.07948784322863[/C][C]6.716875[/C][C]1.05398534932221[/C][C]0.987500812885318[/C][/ROW]
[ROW][C]55[/C][C]7.209[/C][C]7.16643344516971[/C][C]6.772875[/C][C]1.05810803317199[/C][C]1.00593971257195[/C][/ROW]
[ROW][C]56[/C][C]7.104[/C][C]7.23997431275887[/C][C]6.83991666666667[/C][C]1.05848867253629[/C][C]0.981218950940303[/C][/ROW]
[ROW][C]57[/C][C]6.83[/C][C]6.90471811181339[/C][C]6.91508333333333[/C][C]0.998501070627742[/C][C]0.989178687586746[/C][/ROW]
[ROW][C]58[/C][C]6.848[/C][C]6.86453066401746[/C][C]6.98966666666667[/C][C]0.98209699995481[/C][C]0.997591872652836[/C][/ROW]
[ROW][C]59[/C][C]6.396[/C][C]6.43187150731242[/C][C]7.05945833333333[/C][C]0.91109986115258[/C][C]0.994422850756326[/C][/ROW]
[ROW][C]60[/C][C]6.414[/C][C]6.53973235054118[/C][C]7.13470833333333[/C][C]0.916608226293928[/C][C]0.980774083127305[/C][/ROW]
[ROW][C]61[/C][C]7.151[/C][C]7.11979306797029[/C][C]7.21729166666667[/C][C]0.986490971516826[/C][C]1.00438312346044[/C][/ROW]
[ROW][C]62[/C][C]6.882[/C][C]6.6354219480236[/C][C]7.2955[/C][C]0.90952257528937[/C][C]1.03716086993531[/C][/ROW]
[ROW][C]63[/C][C]7.698[/C][C]7.60979386509589[/C][C]7.372[/C][C]1.03225635717524[/C][C]1.01159113327743[/C][/ROW]
[ROW][C]64[/C][C]7.626[/C][C]7.56246661830857[/C][C]7.43883333333333[/C][C]1.01661998319296[/C][C]1.00840114540640[/C][/ROW]
[ROW][C]65[/C][C]7.936[/C][C]8.06722483290885[/C][C]7.495875[/C][C]1.07622189976605[/C][C]0.983733584271317[/C][/ROW]
[ROW][C]66[/C][C]8.054[/C][C]7.96092700765555[/C][C]7.55316666666667[/C][C]1.05398534932221[/C][C]1.01169122543831[/C][/ROW]
[ROW][C]67[/C][C]8.128[/C][C]8.02076750628666[/C][C]7.58029166666667[/C][C]1.05810803317199[/C][C]1.01336935569187[/C][/ROW]
[ROW][C]68[/C][C]8.062[/C][C]8.00795194837864[/C][C]7.56545833333333[/C][C]1.05848867253629[/C][C]1.00674929769431[/C][/ROW]
[ROW][C]69[/C][C]7.708[/C][C]7.54271869173324[/C][C]7.55404166666667[/C][C]0.998501070627742[/C][C]1.02191269686988[/C][/ROW]
[ROW][C]70[/C][C]7.574[/C][C]7.42035664528355[/C][C]7.555625[/C][C]0.98209699995481[/C][C]1.02070565635334[/C][/ROW]
[ROW][C]71[/C][C]7.039[/C][C]6.88730755040606[/C][C]7.55933333333333[/C][C]0.91109986115258[/C][C]1.0220249275183[/C][/ROW]
[ROW][C]72[/C][C]7.146[/C][C]6.91829154800057[/C][C]7.54770833333333[/C][C]0.916608226293928[/C][C]1.03291397166765[/C][/ROW]
[ROW][C]73[/C][C]7.07[/C][C]NA[/C][C]7.53220833333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]74[/C][C]6.607[/C][C]NA[/C][C]7.52908333333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]75[/C][C]7.699[/C][C]NA[/C][C]7.51325[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]76[/C][C]7.663[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]77[/C][C]7.988[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]78[/C][C]7.723[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]79[/C][C]8.087[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]8.028[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]7.362[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77732&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77732&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	5.074	NA	NA	0.986490971516826	NA
2	4.643	NA	NA	0.90952257528937	NA
3	5.451	NA	NA	1.03225635717524	NA
4	5.397	NA	NA	1.01661998319296	NA
5	5.635	NA	NA	1.07622189976605	NA
6	5.708	NA	NA	1.05398534932221	NA
7	5.578	5.61083828506803	5.30270833333333	1.05810803317199	0.994147347793747
8	5.574	5.61933994771643	5.30883333333333	1.05848867253629	0.991931446017098
9	5.352	5.30811489987963	5.31608333333333	0.998501070627742	1.00826754901658
10	5.302	5.22262816292635	5.31783333333333	0.98209699995481	1.01519768105206
11	4.923	4.85065769828212	5.32395833333333	0.91109986115258	1.01491391605380
12	4.982	4.88556003815607	5.33004166666667	0.916608226293928	1.01973979668467
13	5.101	5.26654646660449	5.33866666666667	0.986490971516826	0.968566409191634
14	4.763	4.86893962294179	5.35329166666667	0.90952257528937	0.978241746428193
15	5.505	5.53461450172126	5.36166666666667	1.03225635717524	0.994649220517156
16	5.385	5.45412385066427	5.36495833333333	1.01661998319296	0.987326314444463
17	5.794	5.77630714894018	5.36720833333333	1.07622189976605	1.00306300385413
18	5.695	5.66205321261514	5.37204166666667	1.05398534932221	1.00581887632413
19	5.798	5.69328253598601	5.380625	1.05810803317199	1.01839316130055
20	5.705	5.7021225826477	5.38704166666667	1.05848867253629	1.00050462214914
21	5.422	5.38083906119035	5.38891666666667	0.998501070627742	1.00764953910377
22	5.311	5.30090947796441	5.39754166666667	0.98209699995481	1.00190354543452
23	4.968	4.93091041105198	5.41204166666667	0.91109986115258	1.00752185415190
24	5.053	4.973707195918	5.42620833333333	0.916608226293928	1.01594239486938
25	5.236	5.36305816665122	5.4365	0.986490971516826	0.976308635352624
26	4.782	4.95511688695046	5.44804166666667	0.90952257528937	0.965063006403266
27	5.531	5.63990465015313	5.46366666666667	1.03225635717524	0.980690338417303
28	5.566	5.5708657120676	5.47979166666667	1.01661998319296	0.999126578826509
29	5.961	5.91352544116035	5.49470833333333	1.07622189976605	1.00802813132572
30	5.868	5.80306766914321	5.50583333333333	1.05398534932221	1.01118931133649
31	5.872	5.8576419838054	5.53595833333333	1.05810803317199	1.00245115973873
32	5.908	5.91112999177893	5.5845	1.05848867253629	0.999470491803887
33	5.594	5.62077054761994	5.62920833333333	0.998501070627742	0.995237210380118
34	5.526	5.5685309104521	5.67004166666667	0.98209699995481	0.992362274514402
35	5.111	5.20089966990686	5.708375	0.91109986115258	0.982714592548857
36	5.177	5.26262974724773	5.74141666666667	0.916608226293928	0.983728715231673
37	5.835	5.68901122515657	5.76691666666667	0.986490971516826	1.02566153749141
38	5.348	5.27875533665759	5.803875	0.90952257528937	1.01311761180927
39	6.038	6.03775345448109	5.84908333333333	1.03225635717524	1.00004083398250
40	6.039	5.98712923601915	5.88925	1.01661998319296	1.00866371209574
41	6.408	6.38598685515765	5.93370833333333	1.07622189976605	1.00344710149608
42	6.214	6.30335938162149	5.9805	1.05398534932221	0.985823530563396
43	6.138	6.3813172845561	6.030875	1.05810803317199	0.961870367244555
44	6.529	6.43834555809139	6.08258333333333	1.05848867253629	1.01408039396001
45	6.058	6.13129582418965	6.1405	0.998501070627742	0.988045622607136
46	6.026	6.09018810026143	6.20120833333333	0.98209699995481	0.989460407592555
47	5.678	5.70458604314737	6.26120833333333	0.91109986115258	0.995339531572267
48	5.733	5.79873098360139	6.32629166666667	0.916608226293928	0.988664591651643
49	6.488	6.3167894171556	6.40329166666667	0.986490971516826	1.02710405105154
50	5.936	5.88631641695089	6.471875	0.90952257528937	1.00844052197161
51	6.84	6.73856949963998	6.528	1.03225635717524	1.01505223035326
52	6.694	6.70401576083405	6.59441666666667	1.01661998319296	0.998506005774544
53	7.193	7.16611320475056	6.65858333333333	1.07622189976605	1.00375193560040
54	6.991	7.07948784322863	6.716875	1.05398534932221	0.987500812885318
55	7.209	7.16643344516971	6.772875	1.05810803317199	1.00593971257195
56	7.104	7.23997431275887	6.83991666666667	1.05848867253629	0.981218950940303
57	6.83	6.90471811181339	6.91508333333333	0.998501070627742	0.989178687586746
58	6.848	6.86453066401746	6.98966666666667	0.98209699995481	0.997591872652836
59	6.396	6.43187150731242	7.05945833333333	0.91109986115258	0.994422850756326
60	6.414	6.53973235054118	7.13470833333333	0.916608226293928	0.980774083127305
61	7.151	7.11979306797029	7.21729166666667	0.986490971516826	1.00438312346044
62	6.882	6.6354219480236	7.2955	0.90952257528937	1.03716086993531
63	7.698	7.60979386509589	7.372	1.03225635717524	1.01159113327743
64	7.626	7.56246661830857	7.43883333333333	1.01661998319296	1.00840114540640
65	7.936	8.06722483290885	7.495875	1.07622189976605	0.983733584271317
66	8.054	7.96092700765555	7.55316666666667	1.05398534932221	1.01169122543831
67	8.128	8.02076750628666	7.58029166666667	1.05810803317199	1.01336935569187
68	8.062	8.00795194837864	7.56545833333333	1.05848867253629	1.00674929769431
69	7.708	7.54271869173324	7.55404166666667	0.998501070627742	1.02191269686988
70	7.574	7.42035664528355	7.555625	0.98209699995481	1.02070565635334
71	7.039	6.88730755040606	7.55933333333333	0.91109986115258	1.0220249275183
72	7.146	6.91829154800057	7.54770833333333	0.916608226293928	1.03291397166765
73	7.07	NA	7.53220833333333	NA	NA
74	6.607	NA	7.52908333333333	NA	NA
75	7.699	NA	7.51325	NA	NA
76	7.663	NA	NA	NA	NA
77	7.988	NA	NA	NA	NA
78	7.723	NA	NA	NA	NA
79	8.087	NA	NA	NA	NA
80	8.028	NA	NA	NA	NA
81	7.362	NA	NA	NA	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code