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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 05 Apr 2015 18:16:45 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/05/t1428254241w30pci1yqhfxphg.htm/, Retrieved Thu, 09 May 2024 05:44:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278687, Retrieved Thu, 09 May 2024 05:44:48 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

159

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

-       [Classical Decomposition] [Inflatie Multipli...] [2015-04-05 17:16:45] [d7b65c9a7c286d706dc95a87d306e880] [Current]

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Dataseries X:

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Boxplots

2
2,2
2,2
2
2,3
2,6
3,2
3,2
3,1
2,8
2,3
1,9
1,9
2
2
1,8
1,6
1,4
0,2
0,3
0,4
0,7
1
1,1
0,8
0,8
1
1,1
1
0,8
1,6
1,5
1,6
1,6
1,6
1,9
2
1,9
2
2,1
2,3
2,3
2,6
2,6
2,7
2,6
2,6
2,4
2,5
2,5
2,5
2,4
2,1
2,1
2,3
2,3
2,3
2,9
2,8
2,9
3
3
2,9
2,6
2,8
2,9
3,1
2,8
2,4
1,6
1,5
1,7

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	'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278687&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278687&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278687&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2	NA	NA	1.00737	NA
2	2.2	NA	NA	0.997058	NA
3	2.2	NA	NA	1.04382	NA
4	2	NA	NA	1.02767	NA
5	2.3	NA	NA	1.0029	NA
6	2.6	NA	NA	0.955923	NA
7	3.2	2.34072	2.47917	0.944157	1.3671
8	3.2	2.29357	2.46667	0.929827	1.3952
9	3.1	2.33259	2.45	0.952079	1.32899
10	2.8	2.49545	2.43333	1.02553	1.12204
11	2.3	2.5067	2.39583	1.04627	0.917542
12	1.9	2.47282	2.31667	1.0674	0.768355
13	1.9	2.15744	2.14167	1.00737	0.880672
14	2	1.89026	1.89583	0.997058	1.05806
15	2	1.73535	1.6625	1.04382	1.1525
16	1.8	1.50297	1.4625	1.02767	1.19763
17	1.6	1.32466	1.32083	1.0029	1.20786
18	1.4	1.17897	1.23333	0.955923	1.18748
19	0.2	1.08971	1.15417	0.944157	0.183534
20	0.3	0.984067	1.05833	0.929827	0.304857
21	0.4	0.920343	0.966667	0.952079	0.434621
22	0.7	0.9187	0.895833	1.02553	0.761946
23	1	0.880613	0.841667	1.04627	1.13557
24	1.1	0.845027	0.791667	1.0674	1.30173
25	0.8	0.831078	0.825	1.00737	0.962606
26	0.8	0.930587	0.933333	0.997058	0.859672
27	1	1.07862	1.03333	1.04382	0.927114
28	1.1	1.15185	1.12083	1.02767	0.954989
29	1	1.18676	1.18333	1.0029	0.842629
30	0.8	1.18694	1.24167	0.955923	0.674003
31	1.6	1.25101	1.325	0.944157	1.27897
32	1.5	1.32113	1.42083	0.929827	1.13539
33	1.6	1.43605	1.50833	0.952079	1.11417
34	1.6	1.6323	1.59167	1.02553	0.980215
35	1.6	1.76559	1.6875	1.04627	0.906215
36	1.9	1.92577	1.80417	1.0674	0.986617
37	2	1.92239	1.90833	1.00737	1.04037
38	1.9	1.98996	1.99583	0.997058	0.954792
39	2	2.17898	2.0875	1.04382	0.917861
40	2.1	2.23518	2.175	1.02767	0.939522
41	2.3	2.26488	2.25833	1.0029	1.01551
42	2.3	2.21854	2.32083	0.955923	1.03672
43	2.6	2.23057	2.3625	0.944157	1.16562
44	2.6	2.23933	2.40833	0.929827	1.16106
45	2.7	2.33656	2.45417	0.952079	1.15555
46	2.6	2.551	2.4875	1.02553	1.01921
47	2.6	2.60696	2.49167	1.04627	0.997329
48	2.4	2.64182	2.475	1.0674	0.908464
49	2.5	2.47225	2.45417	1.00737	1.01123
50	2.5	2.42202	2.42917	0.997058	1.0322
51	2.5	2.50517	2.4	1.04382	0.997935
52	2.4	2.46212	2.39583	1.02767	0.974768
53	2.1	2.42367	2.41667	1.0029	0.866456
54	2.1	2.33803	2.44583	0.955923	0.898193
55	2.3	2.34859	2.4875	0.944157	0.979311
56	2.3	2.35169	2.52917	0.929827	0.978021
57	2.3	2.44367	2.56667	0.952079	0.941208
58	2.9	2.65782	2.59167	1.02553	1.09112
59	2.8	2.75083	2.62917	1.04627	1.01788
60	2.9	2.87309	2.69167	1.0674	1.00937
61	3	2.77865	2.75833	1.00737	1.07966
62	3	2.80423	2.8125	0.997058	1.06981
63	2.9	2.96184	2.8375	1.04382	0.97912
64	2.6	2.86463	2.7875	1.02767	0.907622
65	2.8	2.68693	2.67917	1.0029	1.04208
66	2.9	2.4615	2.575	0.955923	1.17814
67	3.1	NA	NA	0.944157	NA
68	2.8	NA	NA	0.929827	NA
69	2.4	NA	NA	0.952079	NA
70	1.6	NA	NA	1.02553	NA
71	1.5	NA	NA	1.04627	NA
72	1.7	NA	NA	1.0674	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2 & NA & NA & 1.00737 & NA \tabularnewline
2 & 2.2 & NA & NA & 0.997058 & NA \tabularnewline
3 & 2.2 & NA & NA & 1.04382 & NA \tabularnewline
4 & 2 & NA & NA & 1.02767 & NA \tabularnewline
5 & 2.3 & NA & NA & 1.0029 & NA \tabularnewline
6 & 2.6 & NA & NA & 0.955923 & NA \tabularnewline
7 & 3.2 & 2.34072 & 2.47917 & 0.944157 & 1.3671 \tabularnewline
8 & 3.2 & 2.29357 & 2.46667 & 0.929827 & 1.3952 \tabularnewline
9 & 3.1 & 2.33259 & 2.45 & 0.952079 & 1.32899 \tabularnewline
10 & 2.8 & 2.49545 & 2.43333 & 1.02553 & 1.12204 \tabularnewline
11 & 2.3 & 2.5067 & 2.39583 & 1.04627 & 0.917542 \tabularnewline
12 & 1.9 & 2.47282 & 2.31667 & 1.0674 & 0.768355 \tabularnewline
13 & 1.9 & 2.15744 & 2.14167 & 1.00737 & 0.880672 \tabularnewline
14 & 2 & 1.89026 & 1.89583 & 0.997058 & 1.05806 \tabularnewline
15 & 2 & 1.73535 & 1.6625 & 1.04382 & 1.1525 \tabularnewline
16 & 1.8 & 1.50297 & 1.4625 & 1.02767 & 1.19763 \tabularnewline
17 & 1.6 & 1.32466 & 1.32083 & 1.0029 & 1.20786 \tabularnewline
18 & 1.4 & 1.17897 & 1.23333 & 0.955923 & 1.18748 \tabularnewline
19 & 0.2 & 1.08971 & 1.15417 & 0.944157 & 0.183534 \tabularnewline
20 & 0.3 & 0.984067 & 1.05833 & 0.929827 & 0.304857 \tabularnewline
21 & 0.4 & 0.920343 & 0.966667 & 0.952079 & 0.434621 \tabularnewline
22 & 0.7 & 0.9187 & 0.895833 & 1.02553 & 0.761946 \tabularnewline
23 & 1 & 0.880613 & 0.841667 & 1.04627 & 1.13557 \tabularnewline
24 & 1.1 & 0.845027 & 0.791667 & 1.0674 & 1.30173 \tabularnewline
25 & 0.8 & 0.831078 & 0.825 & 1.00737 & 0.962606 \tabularnewline
26 & 0.8 & 0.930587 & 0.933333 & 0.997058 & 0.859672 \tabularnewline
27 & 1 & 1.07862 & 1.03333 & 1.04382 & 0.927114 \tabularnewline
28 & 1.1 & 1.15185 & 1.12083 & 1.02767 & 0.954989 \tabularnewline
29 & 1 & 1.18676 & 1.18333 & 1.0029 & 0.842629 \tabularnewline
30 & 0.8 & 1.18694 & 1.24167 & 0.955923 & 0.674003 \tabularnewline
31 & 1.6 & 1.25101 & 1.325 & 0.944157 & 1.27897 \tabularnewline
32 & 1.5 & 1.32113 & 1.42083 & 0.929827 & 1.13539 \tabularnewline
33 & 1.6 & 1.43605 & 1.50833 & 0.952079 & 1.11417 \tabularnewline
34 & 1.6 & 1.6323 & 1.59167 & 1.02553 & 0.980215 \tabularnewline
35 & 1.6 & 1.76559 & 1.6875 & 1.04627 & 0.906215 \tabularnewline
36 & 1.9 & 1.92577 & 1.80417 & 1.0674 & 0.986617 \tabularnewline
37 & 2 & 1.92239 & 1.90833 & 1.00737 & 1.04037 \tabularnewline
38 & 1.9 & 1.98996 & 1.99583 & 0.997058 & 0.954792 \tabularnewline
39 & 2 & 2.17898 & 2.0875 & 1.04382 & 0.917861 \tabularnewline
40 & 2.1 & 2.23518 & 2.175 & 1.02767 & 0.939522 \tabularnewline
41 & 2.3 & 2.26488 & 2.25833 & 1.0029 & 1.01551 \tabularnewline
42 & 2.3 & 2.21854 & 2.32083 & 0.955923 & 1.03672 \tabularnewline
43 & 2.6 & 2.23057 & 2.3625 & 0.944157 & 1.16562 \tabularnewline
44 & 2.6 & 2.23933 & 2.40833 & 0.929827 & 1.16106 \tabularnewline
45 & 2.7 & 2.33656 & 2.45417 & 0.952079 & 1.15555 \tabularnewline
46 & 2.6 & 2.551 & 2.4875 & 1.02553 & 1.01921 \tabularnewline
47 & 2.6 & 2.60696 & 2.49167 & 1.04627 & 0.997329 \tabularnewline
48 & 2.4 & 2.64182 & 2.475 & 1.0674 & 0.908464 \tabularnewline
49 & 2.5 & 2.47225 & 2.45417 & 1.00737 & 1.01123 \tabularnewline
50 & 2.5 & 2.42202 & 2.42917 & 0.997058 & 1.0322 \tabularnewline
51 & 2.5 & 2.50517 & 2.4 & 1.04382 & 0.997935 \tabularnewline
52 & 2.4 & 2.46212 & 2.39583 & 1.02767 & 0.974768 \tabularnewline
53 & 2.1 & 2.42367 & 2.41667 & 1.0029 & 0.866456 \tabularnewline
54 & 2.1 & 2.33803 & 2.44583 & 0.955923 & 0.898193 \tabularnewline
55 & 2.3 & 2.34859 & 2.4875 & 0.944157 & 0.979311 \tabularnewline
56 & 2.3 & 2.35169 & 2.52917 & 0.929827 & 0.978021 \tabularnewline
57 & 2.3 & 2.44367 & 2.56667 & 0.952079 & 0.941208 \tabularnewline
58 & 2.9 & 2.65782 & 2.59167 & 1.02553 & 1.09112 \tabularnewline
59 & 2.8 & 2.75083 & 2.62917 & 1.04627 & 1.01788 \tabularnewline
60 & 2.9 & 2.87309 & 2.69167 & 1.0674 & 1.00937 \tabularnewline
61 & 3 & 2.77865 & 2.75833 & 1.00737 & 1.07966 \tabularnewline
62 & 3 & 2.80423 & 2.8125 & 0.997058 & 1.06981 \tabularnewline
63 & 2.9 & 2.96184 & 2.8375 & 1.04382 & 0.97912 \tabularnewline
64 & 2.6 & 2.86463 & 2.7875 & 1.02767 & 0.907622 \tabularnewline
65 & 2.8 & 2.68693 & 2.67917 & 1.0029 & 1.04208 \tabularnewline
66 & 2.9 & 2.4615 & 2.575 & 0.955923 & 1.17814 \tabularnewline
67 & 3.1 & NA & NA & 0.944157 & NA \tabularnewline
68 & 2.8 & NA & NA & 0.929827 & NA \tabularnewline
69 & 2.4 & NA & NA & 0.952079 & NA \tabularnewline
70 & 1.6 & NA & NA & 1.02553 & NA \tabularnewline
71 & 1.5 & NA & NA & 1.04627 & NA \tabularnewline
72 & 1.7 & NA & NA & 1.0674 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278687&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]2[/C][C]NA[/C][C]NA[/C][C]1.00737[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.2[/C][C]NA[/C][C]NA[/C][C]0.997058[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.2[/C][C]NA[/C][C]NA[/C][C]1.04382[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2[/C][C]NA[/C][C]NA[/C][C]1.02767[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.3[/C][C]NA[/C][C]NA[/C][C]1.0029[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.6[/C][C]NA[/C][C]NA[/C][C]0.955923[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3.2[/C][C]2.34072[/C][C]2.47917[/C][C]0.944157[/C][C]1.3671[/C][/ROW]
[ROW][C]8[/C][C]3.2[/C][C]2.29357[/C][C]2.46667[/C][C]0.929827[/C][C]1.3952[/C][/ROW]
[ROW][C]9[/C][C]3.1[/C][C]2.33259[/C][C]2.45[/C][C]0.952079[/C][C]1.32899[/C][/ROW]
[ROW][C]10[/C][C]2.8[/C][C]2.49545[/C][C]2.43333[/C][C]1.02553[/C][C]1.12204[/C][/ROW]
[ROW][C]11[/C][C]2.3[/C][C]2.5067[/C][C]2.39583[/C][C]1.04627[/C][C]0.917542[/C][/ROW]
[ROW][C]12[/C][C]1.9[/C][C]2.47282[/C][C]2.31667[/C][C]1.0674[/C][C]0.768355[/C][/ROW]
[ROW][C]13[/C][C]1.9[/C][C]2.15744[/C][C]2.14167[/C][C]1.00737[/C][C]0.880672[/C][/ROW]
[ROW][C]14[/C][C]2[/C][C]1.89026[/C][C]1.89583[/C][C]0.997058[/C][C]1.05806[/C][/ROW]
[ROW][C]15[/C][C]2[/C][C]1.73535[/C][C]1.6625[/C][C]1.04382[/C][C]1.1525[/C][/ROW]
[ROW][C]16[/C][C]1.8[/C][C]1.50297[/C][C]1.4625[/C][C]1.02767[/C][C]1.19763[/C][/ROW]
[ROW][C]17[/C][C]1.6[/C][C]1.32466[/C][C]1.32083[/C][C]1.0029[/C][C]1.20786[/C][/ROW]
[ROW][C]18[/C][C]1.4[/C][C]1.17897[/C][C]1.23333[/C][C]0.955923[/C][C]1.18748[/C][/ROW]
[ROW][C]19[/C][C]0.2[/C][C]1.08971[/C][C]1.15417[/C][C]0.944157[/C][C]0.183534[/C][/ROW]
[ROW][C]20[/C][C]0.3[/C][C]0.984067[/C][C]1.05833[/C][C]0.929827[/C][C]0.304857[/C][/ROW]
[ROW][C]21[/C][C]0.4[/C][C]0.920343[/C][C]0.966667[/C][C]0.952079[/C][C]0.434621[/C][/ROW]
[ROW][C]22[/C][C]0.7[/C][C]0.9187[/C][C]0.895833[/C][C]1.02553[/C][C]0.761946[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]0.880613[/C][C]0.841667[/C][C]1.04627[/C][C]1.13557[/C][/ROW]
[ROW][C]24[/C][C]1.1[/C][C]0.845027[/C][C]0.791667[/C][C]1.0674[/C][C]1.30173[/C][/ROW]
[ROW][C]25[/C][C]0.8[/C][C]0.831078[/C][C]0.825[/C][C]1.00737[/C][C]0.962606[/C][/ROW]
[ROW][C]26[/C][C]0.8[/C][C]0.930587[/C][C]0.933333[/C][C]0.997058[/C][C]0.859672[/C][/ROW]
[ROW][C]27[/C][C]1[/C][C]1.07862[/C][C]1.03333[/C][C]1.04382[/C][C]0.927114[/C][/ROW]
[ROW][C]28[/C][C]1.1[/C][C]1.15185[/C][C]1.12083[/C][C]1.02767[/C][C]0.954989[/C][/ROW]
[ROW][C]29[/C][C]1[/C][C]1.18676[/C][C]1.18333[/C][C]1.0029[/C][C]0.842629[/C][/ROW]
[ROW][C]30[/C][C]0.8[/C][C]1.18694[/C][C]1.24167[/C][C]0.955923[/C][C]0.674003[/C][/ROW]
[ROW][C]31[/C][C]1.6[/C][C]1.25101[/C][C]1.325[/C][C]0.944157[/C][C]1.27897[/C][/ROW]
[ROW][C]32[/C][C]1.5[/C][C]1.32113[/C][C]1.42083[/C][C]0.929827[/C][C]1.13539[/C][/ROW]
[ROW][C]33[/C][C]1.6[/C][C]1.43605[/C][C]1.50833[/C][C]0.952079[/C][C]1.11417[/C][/ROW]
[ROW][C]34[/C][C]1.6[/C][C]1.6323[/C][C]1.59167[/C][C]1.02553[/C][C]0.980215[/C][/ROW]
[ROW][C]35[/C][C]1.6[/C][C]1.76559[/C][C]1.6875[/C][C]1.04627[/C][C]0.906215[/C][/ROW]
[ROW][C]36[/C][C]1.9[/C][C]1.92577[/C][C]1.80417[/C][C]1.0674[/C][C]0.986617[/C][/ROW]
[ROW][C]37[/C][C]2[/C][C]1.92239[/C][C]1.90833[/C][C]1.00737[/C][C]1.04037[/C][/ROW]
[ROW][C]38[/C][C]1.9[/C][C]1.98996[/C][C]1.99583[/C][C]0.997058[/C][C]0.954792[/C][/ROW]
[ROW][C]39[/C][C]2[/C][C]2.17898[/C][C]2.0875[/C][C]1.04382[/C][C]0.917861[/C][/ROW]
[ROW][C]40[/C][C]2.1[/C][C]2.23518[/C][C]2.175[/C][C]1.02767[/C][C]0.939522[/C][/ROW]
[ROW][C]41[/C][C]2.3[/C][C]2.26488[/C][C]2.25833[/C][C]1.0029[/C][C]1.01551[/C][/ROW]
[ROW][C]42[/C][C]2.3[/C][C]2.21854[/C][C]2.32083[/C][C]0.955923[/C][C]1.03672[/C][/ROW]
[ROW][C]43[/C][C]2.6[/C][C]2.23057[/C][C]2.3625[/C][C]0.944157[/C][C]1.16562[/C][/ROW]
[ROW][C]44[/C][C]2.6[/C][C]2.23933[/C][C]2.40833[/C][C]0.929827[/C][C]1.16106[/C][/ROW]
[ROW][C]45[/C][C]2.7[/C][C]2.33656[/C][C]2.45417[/C][C]0.952079[/C][C]1.15555[/C][/ROW]
[ROW][C]46[/C][C]2.6[/C][C]2.551[/C][C]2.4875[/C][C]1.02553[/C][C]1.01921[/C][/ROW]
[ROW][C]47[/C][C]2.6[/C][C]2.60696[/C][C]2.49167[/C][C]1.04627[/C][C]0.997329[/C][/ROW]
[ROW][C]48[/C][C]2.4[/C][C]2.64182[/C][C]2.475[/C][C]1.0674[/C][C]0.908464[/C][/ROW]
[ROW][C]49[/C][C]2.5[/C][C]2.47225[/C][C]2.45417[/C][C]1.00737[/C][C]1.01123[/C][/ROW]
[ROW][C]50[/C][C]2.5[/C][C]2.42202[/C][C]2.42917[/C][C]0.997058[/C][C]1.0322[/C][/ROW]
[ROW][C]51[/C][C]2.5[/C][C]2.50517[/C][C]2.4[/C][C]1.04382[/C][C]0.997935[/C][/ROW]
[ROW][C]52[/C][C]2.4[/C][C]2.46212[/C][C]2.39583[/C][C]1.02767[/C][C]0.974768[/C][/ROW]
[ROW][C]53[/C][C]2.1[/C][C]2.42367[/C][C]2.41667[/C][C]1.0029[/C][C]0.866456[/C][/ROW]
[ROW][C]54[/C][C]2.1[/C][C]2.33803[/C][C]2.44583[/C][C]0.955923[/C][C]0.898193[/C][/ROW]
[ROW][C]55[/C][C]2.3[/C][C]2.34859[/C][C]2.4875[/C][C]0.944157[/C][C]0.979311[/C][/ROW]
[ROW][C]56[/C][C]2.3[/C][C]2.35169[/C][C]2.52917[/C][C]0.929827[/C][C]0.978021[/C][/ROW]
[ROW][C]57[/C][C]2.3[/C][C]2.44367[/C][C]2.56667[/C][C]0.952079[/C][C]0.941208[/C][/ROW]
[ROW][C]58[/C][C]2.9[/C][C]2.65782[/C][C]2.59167[/C][C]1.02553[/C][C]1.09112[/C][/ROW]
[ROW][C]59[/C][C]2.8[/C][C]2.75083[/C][C]2.62917[/C][C]1.04627[/C][C]1.01788[/C][/ROW]
[ROW][C]60[/C][C]2.9[/C][C]2.87309[/C][C]2.69167[/C][C]1.0674[/C][C]1.00937[/C][/ROW]
[ROW][C]61[/C][C]3[/C][C]2.77865[/C][C]2.75833[/C][C]1.00737[/C][C]1.07966[/C][/ROW]
[ROW][C]62[/C][C]3[/C][C]2.80423[/C][C]2.8125[/C][C]0.997058[/C][C]1.06981[/C][/ROW]
[ROW][C]63[/C][C]2.9[/C][C]2.96184[/C][C]2.8375[/C][C]1.04382[/C][C]0.97912[/C][/ROW]
[ROW][C]64[/C][C]2.6[/C][C]2.86463[/C][C]2.7875[/C][C]1.02767[/C][C]0.907622[/C][/ROW]
[ROW][C]65[/C][C]2.8[/C][C]2.68693[/C][C]2.67917[/C][C]1.0029[/C][C]1.04208[/C][/ROW]
[ROW][C]66[/C][C]2.9[/C][C]2.4615[/C][C]2.575[/C][C]0.955923[/C][C]1.17814[/C][/ROW]
[ROW][C]67[/C][C]3.1[/C][C]NA[/C][C]NA[/C][C]0.944157[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]2.8[/C][C]NA[/C][C]NA[/C][C]0.929827[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]2.4[/C][C]NA[/C][C]NA[/C][C]0.952079[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.6[/C][C]NA[/C][C]NA[/C][C]1.02553[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.5[/C][C]NA[/C][C]NA[/C][C]1.04627[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.7[/C][C]NA[/C][C]NA[/C][C]1.0674[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278687&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278687&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	2	NA	NA	1.00737	NA
2	2.2	NA	NA	0.997058	NA
3	2.2	NA	NA	1.04382	NA
4	2	NA	NA	1.02767	NA
5	2.3	NA	NA	1.0029	NA
6	2.6	NA	NA	0.955923	NA
7	3.2	2.34072	2.47917	0.944157	1.3671
8	3.2	2.29357	2.46667	0.929827	1.3952
9	3.1	2.33259	2.45	0.952079	1.32899
10	2.8	2.49545	2.43333	1.02553	1.12204
11	2.3	2.5067	2.39583	1.04627	0.917542
12	1.9	2.47282	2.31667	1.0674	0.768355
13	1.9	2.15744	2.14167	1.00737	0.880672
14	2	1.89026	1.89583	0.997058	1.05806
15	2	1.73535	1.6625	1.04382	1.1525
16	1.8	1.50297	1.4625	1.02767	1.19763
17	1.6	1.32466	1.32083	1.0029	1.20786
18	1.4	1.17897	1.23333	0.955923	1.18748
19	0.2	1.08971	1.15417	0.944157	0.183534
20	0.3	0.984067	1.05833	0.929827	0.304857
21	0.4	0.920343	0.966667	0.952079	0.434621
22	0.7	0.9187	0.895833	1.02553	0.761946
23	1	0.880613	0.841667	1.04627	1.13557
24	1.1	0.845027	0.791667	1.0674	1.30173
25	0.8	0.831078	0.825	1.00737	0.962606
26	0.8	0.930587	0.933333	0.997058	0.859672
27	1	1.07862	1.03333	1.04382	0.927114
28	1.1	1.15185	1.12083	1.02767	0.954989
29	1	1.18676	1.18333	1.0029	0.842629
30	0.8	1.18694	1.24167	0.955923	0.674003
31	1.6	1.25101	1.325	0.944157	1.27897
32	1.5	1.32113	1.42083	0.929827	1.13539
33	1.6	1.43605	1.50833	0.952079	1.11417
34	1.6	1.6323	1.59167	1.02553	0.980215
35	1.6	1.76559	1.6875	1.04627	0.906215
36	1.9	1.92577	1.80417	1.0674	0.986617
37	2	1.92239	1.90833	1.00737	1.04037
38	1.9	1.98996	1.99583	0.997058	0.954792
39	2	2.17898	2.0875	1.04382	0.917861
40	2.1	2.23518	2.175	1.02767	0.939522
41	2.3	2.26488	2.25833	1.0029	1.01551
42	2.3	2.21854	2.32083	0.955923	1.03672
43	2.6	2.23057	2.3625	0.944157	1.16562
44	2.6	2.23933	2.40833	0.929827	1.16106
45	2.7	2.33656	2.45417	0.952079	1.15555
46	2.6	2.551	2.4875	1.02553	1.01921
47	2.6	2.60696	2.49167	1.04627	0.997329
48	2.4	2.64182	2.475	1.0674	0.908464
49	2.5	2.47225	2.45417	1.00737	1.01123
50	2.5	2.42202	2.42917	0.997058	1.0322
51	2.5	2.50517	2.4	1.04382	0.997935
52	2.4	2.46212	2.39583	1.02767	0.974768
53	2.1	2.42367	2.41667	1.0029	0.866456
54	2.1	2.33803	2.44583	0.955923	0.898193
55	2.3	2.34859	2.4875	0.944157	0.979311
56	2.3	2.35169	2.52917	0.929827	0.978021
57	2.3	2.44367	2.56667	0.952079	0.941208
58	2.9	2.65782	2.59167	1.02553	1.09112
59	2.8	2.75083	2.62917	1.04627	1.01788
60	2.9	2.87309	2.69167	1.0674	1.00937
61	3	2.77865	2.75833	1.00737	1.07966
62	3	2.80423	2.8125	0.997058	1.06981
63	2.9	2.96184	2.8375	1.04382	0.97912
64	2.6	2.86463	2.7875	1.02767	0.907622
65	2.8	2.68693	2.67917	1.0029	1.04208
66	2.9	2.4615	2.575	0.955923	1.17814
67	3.1	NA	NA	0.944157	NA
68	2.8	NA	NA	0.929827	NA
69	2.4	NA	NA	0.952079	NA
70	1.6	NA	NA	1.02553	NA
71	1.5	NA	NA	1.04627	NA
72	1.7	NA	NA	1.0674	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
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