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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 28 Nov 2014 11:15:53 +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/2014/Nov/28/t1417173367tyjvyuhpjr7sa2l.htm/, Retrieved Sun, 19 May 2024 14:05:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260834, Retrieved Sun, 19 May 2024 14:05:23 +0000

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-       [Classical Decomposition] [] [2014-11-28 11:15:53] [72d1b0bbc256d1ec09d716526c8fc98d] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260834&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260834&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260834&T=0

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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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	37.3	NA	NA	-0.053125	NA
2	39.5	NA	NA	0.00790441	NA
3	40.6	40.4322	40.2	0.232169	0.167831
4	41.4	41.0131	41.2	-0.186949	0.386949
5	41.3	42.0719	42.125	-0.053125	-0.771875
6	43.5	42.9954	42.9875	0.00790441	0.504596
7	44	44.2947	44.0625	0.232169	-0.294669
8	44.9	45.0006	45.1875	-0.186949	-0.100551
9	46.4	46.2094	46.2625	-0.053125	0.190625
10	47.4	47.4579	47.45	0.00790441	-0.0579044
11	48.7	48.8697	48.6375	0.232169	-0.169669
12	49.7	49.7631	49.95	-0.186949	-0.0630515
13	51.1	51.5594	51.6125	-0.053125	-0.459375
14	53.2	53.6079	53.6	0.00790441	-0.407904
15	56.2	56.0697	55.8375	0.232169	0.130331
16	58.1	58.2006	58.3875	-0.186949	-0.100551
17	60.6	61.0969	61.15	-0.053125	-0.496875
18	64.1	63.7954	63.7875	0.00790441	0.304596
19	67.4	66.5447	66.3125	0.232169	0.855331
20	68	68.5006	68.6875	-0.186949	-0.500551
21	70.9	70.6594	70.7125	-0.053125	0.240625
22	72.8	72.6704	72.6625	0.00790441	0.129596
23	74.9	74.6697	74.4375	0.232169	0.230331
24	76.1	75.6756	75.8625	-0.186949	0.424449
25	77	77.1094	77.1625	-0.053125	-0.109375
26	78.1	78.2579	78.25	0.00790441	-0.157904
27	80	79.6447	79.4125	0.232169	0.355331
28	79.7	80.7131	80.9	-0.186949	-1.01305
29	82.7	82.0594	82.1125	-0.053125	0.640625
30	84.3	83.3329	83.325	0.00790441	0.967096
31	83.5	84.8697	84.6375	0.232169	-1.36967
32	85.9	85.5256	85.7125	-0.186949	0.374449
33	87	87.0844	87.1375	-0.053125	-0.084375
34	88.6	88.7079	88.7	0.00790441	-0.107904
35	90.6	90.1822	89.95	0.232169	0.417831
36	91.3	90.9131	91.1	-0.186949	0.386949
37	91.6	92.1719	92.225	-0.053125	-0.571875
38	93.2	93.2704	93.2625	0.00790441	-0.0704044
39	95	94.7072	94.475	0.232169	0.292831
40	95.2	95.6881	95.875	-0.186949	-0.488051
41	97.4	97.0719	97.125	-0.053125	0.328125
42	98.6	98.3829	98.375	0.00790441	0.217096
43	99.6	99.7697	99.5375	0.232169	-0.169669
44	100.6	100.363	100.55	-0.186949	0.236949
45	101.3	101.472	101.525	-0.053125	-0.171875
46	102.8	102.283	102.275	0.00790441	0.517096
47	103.2	103.32	103.087	0.232169	-0.119669
48	103	103.651	103.837	-0.186949	-0.650551
49	105.4	104.272	104.325	-0.053125	1.12812
50	104.7	104.858	104.85	0.00790441	-0.157904
51	105.2	105.032	104.8	0.232169	0.167831
52	105.2	103.738	103.925	-0.186949	1.46195
53	102.8	102.647	102.7	-0.053125	0.153125
54	100.3	101.308	101.3	0.00790441	-1.0079
55	99.8	100.532	100.3	0.232169	-0.732169
56	99.4	99.8256	100.012	-0.186949	-0.425551
57	100.6	100.022	100.075	-0.053125	0.578125
58	100.2	100.083	100.075	0.00790441	0.117096
59	100.4	99.7697	99.5375	0.232169	0.630331
60	98.8	98.4006	98.5875	-0.186949	0.399449
61	96.9	97.5094	97.5625	-0.053125	-0.609375
62	96.3	96.3704	96.3625	0.00790441	-0.0704044
63	96.1	95.3322	95.1	0.232169	0.767831
64	93.5	93.7381	93.925	-0.186949	-0.238051
65	92.1	92.2719	92.325	-0.053125	-0.171875
66	91.7	90.4204	90.4125	0.00790441	1.2796
67	87.9	88.8572	88.625	0.232169	-0.957169
68	86.4	86.2881	86.475	-0.186949	0.111949
69	84.9	84.5094	84.5625	-0.053125	0.390625
70	81.7	83.4954	83.4875	0.00790441	-1.7954
71	82.6	NA	NA	0.232169	NA
72	83.1	NA	NA	-0.186949	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 37.3 & NA & NA & -0.053125 & NA \tabularnewline
2 & 39.5 & NA & NA & 0.00790441 & NA \tabularnewline
3 & 40.6 & 40.4322 & 40.2 & 0.232169 & 0.167831 \tabularnewline
4 & 41.4 & 41.0131 & 41.2 & -0.186949 & 0.386949 \tabularnewline
5 & 41.3 & 42.0719 & 42.125 & -0.053125 & -0.771875 \tabularnewline
6 & 43.5 & 42.9954 & 42.9875 & 0.00790441 & 0.504596 \tabularnewline
7 & 44 & 44.2947 & 44.0625 & 0.232169 & -0.294669 \tabularnewline
8 & 44.9 & 45.0006 & 45.1875 & -0.186949 & -0.100551 \tabularnewline
9 & 46.4 & 46.2094 & 46.2625 & -0.053125 & 0.190625 \tabularnewline
10 & 47.4 & 47.4579 & 47.45 & 0.00790441 & -0.0579044 \tabularnewline
11 & 48.7 & 48.8697 & 48.6375 & 0.232169 & -0.169669 \tabularnewline
12 & 49.7 & 49.7631 & 49.95 & -0.186949 & -0.0630515 \tabularnewline
13 & 51.1 & 51.5594 & 51.6125 & -0.053125 & -0.459375 \tabularnewline
14 & 53.2 & 53.6079 & 53.6 & 0.00790441 & -0.407904 \tabularnewline
15 & 56.2 & 56.0697 & 55.8375 & 0.232169 & 0.130331 \tabularnewline
16 & 58.1 & 58.2006 & 58.3875 & -0.186949 & -0.100551 \tabularnewline
17 & 60.6 & 61.0969 & 61.15 & -0.053125 & -0.496875 \tabularnewline
18 & 64.1 & 63.7954 & 63.7875 & 0.00790441 & 0.304596 \tabularnewline
19 & 67.4 & 66.5447 & 66.3125 & 0.232169 & 0.855331 \tabularnewline
20 & 68 & 68.5006 & 68.6875 & -0.186949 & -0.500551 \tabularnewline
21 & 70.9 & 70.6594 & 70.7125 & -0.053125 & 0.240625 \tabularnewline
22 & 72.8 & 72.6704 & 72.6625 & 0.00790441 & 0.129596 \tabularnewline
23 & 74.9 & 74.6697 & 74.4375 & 0.232169 & 0.230331 \tabularnewline
24 & 76.1 & 75.6756 & 75.8625 & -0.186949 & 0.424449 \tabularnewline
25 & 77 & 77.1094 & 77.1625 & -0.053125 & -0.109375 \tabularnewline
26 & 78.1 & 78.2579 & 78.25 & 0.00790441 & -0.157904 \tabularnewline
27 & 80 & 79.6447 & 79.4125 & 0.232169 & 0.355331 \tabularnewline
28 & 79.7 & 80.7131 & 80.9 & -0.186949 & -1.01305 \tabularnewline
29 & 82.7 & 82.0594 & 82.1125 & -0.053125 & 0.640625 \tabularnewline
30 & 84.3 & 83.3329 & 83.325 & 0.00790441 & 0.967096 \tabularnewline
31 & 83.5 & 84.8697 & 84.6375 & 0.232169 & -1.36967 \tabularnewline
32 & 85.9 & 85.5256 & 85.7125 & -0.186949 & 0.374449 \tabularnewline
33 & 87 & 87.0844 & 87.1375 & -0.053125 & -0.084375 \tabularnewline
34 & 88.6 & 88.7079 & 88.7 & 0.00790441 & -0.107904 \tabularnewline
35 & 90.6 & 90.1822 & 89.95 & 0.232169 & 0.417831 \tabularnewline
36 & 91.3 & 90.9131 & 91.1 & -0.186949 & 0.386949 \tabularnewline
37 & 91.6 & 92.1719 & 92.225 & -0.053125 & -0.571875 \tabularnewline
38 & 93.2 & 93.2704 & 93.2625 & 0.00790441 & -0.0704044 \tabularnewline
39 & 95 & 94.7072 & 94.475 & 0.232169 & 0.292831 \tabularnewline
40 & 95.2 & 95.6881 & 95.875 & -0.186949 & -0.488051 \tabularnewline
41 & 97.4 & 97.0719 & 97.125 & -0.053125 & 0.328125 \tabularnewline
42 & 98.6 & 98.3829 & 98.375 & 0.00790441 & 0.217096 \tabularnewline
43 & 99.6 & 99.7697 & 99.5375 & 0.232169 & -0.169669 \tabularnewline
44 & 100.6 & 100.363 & 100.55 & -0.186949 & 0.236949 \tabularnewline
45 & 101.3 & 101.472 & 101.525 & -0.053125 & -0.171875 \tabularnewline
46 & 102.8 & 102.283 & 102.275 & 0.00790441 & 0.517096 \tabularnewline
47 & 103.2 & 103.32 & 103.087 & 0.232169 & -0.119669 \tabularnewline
48 & 103 & 103.651 & 103.837 & -0.186949 & -0.650551 \tabularnewline
49 & 105.4 & 104.272 & 104.325 & -0.053125 & 1.12812 \tabularnewline
50 & 104.7 & 104.858 & 104.85 & 0.00790441 & -0.157904 \tabularnewline
51 & 105.2 & 105.032 & 104.8 & 0.232169 & 0.167831 \tabularnewline
52 & 105.2 & 103.738 & 103.925 & -0.186949 & 1.46195 \tabularnewline
53 & 102.8 & 102.647 & 102.7 & -0.053125 & 0.153125 \tabularnewline
54 & 100.3 & 101.308 & 101.3 & 0.00790441 & -1.0079 \tabularnewline
55 & 99.8 & 100.532 & 100.3 & 0.232169 & -0.732169 \tabularnewline
56 & 99.4 & 99.8256 & 100.012 & -0.186949 & -0.425551 \tabularnewline
57 & 100.6 & 100.022 & 100.075 & -0.053125 & 0.578125 \tabularnewline
58 & 100.2 & 100.083 & 100.075 & 0.00790441 & 0.117096 \tabularnewline
59 & 100.4 & 99.7697 & 99.5375 & 0.232169 & 0.630331 \tabularnewline
60 & 98.8 & 98.4006 & 98.5875 & -0.186949 & 0.399449 \tabularnewline
61 & 96.9 & 97.5094 & 97.5625 & -0.053125 & -0.609375 \tabularnewline
62 & 96.3 & 96.3704 & 96.3625 & 0.00790441 & -0.0704044 \tabularnewline
63 & 96.1 & 95.3322 & 95.1 & 0.232169 & 0.767831 \tabularnewline
64 & 93.5 & 93.7381 & 93.925 & -0.186949 & -0.238051 \tabularnewline
65 & 92.1 & 92.2719 & 92.325 & -0.053125 & -0.171875 \tabularnewline
66 & 91.7 & 90.4204 & 90.4125 & 0.00790441 & 1.2796 \tabularnewline
67 & 87.9 & 88.8572 & 88.625 & 0.232169 & -0.957169 \tabularnewline
68 & 86.4 & 86.2881 & 86.475 & -0.186949 & 0.111949 \tabularnewline
69 & 84.9 & 84.5094 & 84.5625 & -0.053125 & 0.390625 \tabularnewline
70 & 81.7 & 83.4954 & 83.4875 & 0.00790441 & -1.7954 \tabularnewline
71 & 82.6 & NA & NA & 0.232169 & NA \tabularnewline
72 & 83.1 & NA & NA & -0.186949 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260834&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]37.3[/C][C]NA[/C][C]NA[/C][C]-0.053125[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]39.5[/C][C]NA[/C][C]NA[/C][C]0.00790441[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]40.6[/C][C]40.4322[/C][C]40.2[/C][C]0.232169[/C][C]0.167831[/C][/ROW]
[ROW][C]4[/C][C]41.4[/C][C]41.0131[/C][C]41.2[/C][C]-0.186949[/C][C]0.386949[/C][/ROW]
[ROW][C]5[/C][C]41.3[/C][C]42.0719[/C][C]42.125[/C][C]-0.053125[/C][C]-0.771875[/C][/ROW]
[ROW][C]6[/C][C]43.5[/C][C]42.9954[/C][C]42.9875[/C][C]0.00790441[/C][C]0.504596[/C][/ROW]
[ROW][C]7[/C][C]44[/C][C]44.2947[/C][C]44.0625[/C][C]0.232169[/C][C]-0.294669[/C][/ROW]
[ROW][C]8[/C][C]44.9[/C][C]45.0006[/C][C]45.1875[/C][C]-0.186949[/C][C]-0.100551[/C][/ROW]
[ROW][C]9[/C][C]46.4[/C][C]46.2094[/C][C]46.2625[/C][C]-0.053125[/C][C]0.190625[/C][/ROW]
[ROW][C]10[/C][C]47.4[/C][C]47.4579[/C][C]47.45[/C][C]0.00790441[/C][C]-0.0579044[/C][/ROW]
[ROW][C]11[/C][C]48.7[/C][C]48.8697[/C][C]48.6375[/C][C]0.232169[/C][C]-0.169669[/C][/ROW]
[ROW][C]12[/C][C]49.7[/C][C]49.7631[/C][C]49.95[/C][C]-0.186949[/C][C]-0.0630515[/C][/ROW]
[ROW][C]13[/C][C]51.1[/C][C]51.5594[/C][C]51.6125[/C][C]-0.053125[/C][C]-0.459375[/C][/ROW]
[ROW][C]14[/C][C]53.2[/C][C]53.6079[/C][C]53.6[/C][C]0.00790441[/C][C]-0.407904[/C][/ROW]
[ROW][C]15[/C][C]56.2[/C][C]56.0697[/C][C]55.8375[/C][C]0.232169[/C][C]0.130331[/C][/ROW]
[ROW][C]16[/C][C]58.1[/C][C]58.2006[/C][C]58.3875[/C][C]-0.186949[/C][C]-0.100551[/C][/ROW]
[ROW][C]17[/C][C]60.6[/C][C]61.0969[/C][C]61.15[/C][C]-0.053125[/C][C]-0.496875[/C][/ROW]
[ROW][C]18[/C][C]64.1[/C][C]63.7954[/C][C]63.7875[/C][C]0.00790441[/C][C]0.304596[/C][/ROW]
[ROW][C]19[/C][C]67.4[/C][C]66.5447[/C][C]66.3125[/C][C]0.232169[/C][C]0.855331[/C][/ROW]
[ROW][C]20[/C][C]68[/C][C]68.5006[/C][C]68.6875[/C][C]-0.186949[/C][C]-0.500551[/C][/ROW]
[ROW][C]21[/C][C]70.9[/C][C]70.6594[/C][C]70.7125[/C][C]-0.053125[/C][C]0.240625[/C][/ROW]
[ROW][C]22[/C][C]72.8[/C][C]72.6704[/C][C]72.6625[/C][C]0.00790441[/C][C]0.129596[/C][/ROW]
[ROW][C]23[/C][C]74.9[/C][C]74.6697[/C][C]74.4375[/C][C]0.232169[/C][C]0.230331[/C][/ROW]
[ROW][C]24[/C][C]76.1[/C][C]75.6756[/C][C]75.8625[/C][C]-0.186949[/C][C]0.424449[/C][/ROW]
[ROW][C]25[/C][C]77[/C][C]77.1094[/C][C]77.1625[/C][C]-0.053125[/C][C]-0.109375[/C][/ROW]
[ROW][C]26[/C][C]78.1[/C][C]78.2579[/C][C]78.25[/C][C]0.00790441[/C][C]-0.157904[/C][/ROW]
[ROW][C]27[/C][C]80[/C][C]79.6447[/C][C]79.4125[/C][C]0.232169[/C][C]0.355331[/C][/ROW]
[ROW][C]28[/C][C]79.7[/C][C]80.7131[/C][C]80.9[/C][C]-0.186949[/C][C]-1.01305[/C][/ROW]
[ROW][C]29[/C][C]82.7[/C][C]82.0594[/C][C]82.1125[/C][C]-0.053125[/C][C]0.640625[/C][/ROW]
[ROW][C]30[/C][C]84.3[/C][C]83.3329[/C][C]83.325[/C][C]0.00790441[/C][C]0.967096[/C][/ROW]
[ROW][C]31[/C][C]83.5[/C][C]84.8697[/C][C]84.6375[/C][C]0.232169[/C][C]-1.36967[/C][/ROW]
[ROW][C]32[/C][C]85.9[/C][C]85.5256[/C][C]85.7125[/C][C]-0.186949[/C][C]0.374449[/C][/ROW]
[ROW][C]33[/C][C]87[/C][C]87.0844[/C][C]87.1375[/C][C]-0.053125[/C][C]-0.084375[/C][/ROW]
[ROW][C]34[/C][C]88.6[/C][C]88.7079[/C][C]88.7[/C][C]0.00790441[/C][C]-0.107904[/C][/ROW]
[ROW][C]35[/C][C]90.6[/C][C]90.1822[/C][C]89.95[/C][C]0.232169[/C][C]0.417831[/C][/ROW]
[ROW][C]36[/C][C]91.3[/C][C]90.9131[/C][C]91.1[/C][C]-0.186949[/C][C]0.386949[/C][/ROW]
[ROW][C]37[/C][C]91.6[/C][C]92.1719[/C][C]92.225[/C][C]-0.053125[/C][C]-0.571875[/C][/ROW]
[ROW][C]38[/C][C]93.2[/C][C]93.2704[/C][C]93.2625[/C][C]0.00790441[/C][C]-0.0704044[/C][/ROW]
[ROW][C]39[/C][C]95[/C][C]94.7072[/C][C]94.475[/C][C]0.232169[/C][C]0.292831[/C][/ROW]
[ROW][C]40[/C][C]95.2[/C][C]95.6881[/C][C]95.875[/C][C]-0.186949[/C][C]-0.488051[/C][/ROW]
[ROW][C]41[/C][C]97.4[/C][C]97.0719[/C][C]97.125[/C][C]-0.053125[/C][C]0.328125[/C][/ROW]
[ROW][C]42[/C][C]98.6[/C][C]98.3829[/C][C]98.375[/C][C]0.00790441[/C][C]0.217096[/C][/ROW]
[ROW][C]43[/C][C]99.6[/C][C]99.7697[/C][C]99.5375[/C][C]0.232169[/C][C]-0.169669[/C][/ROW]
[ROW][C]44[/C][C]100.6[/C][C]100.363[/C][C]100.55[/C][C]-0.186949[/C][C]0.236949[/C][/ROW]
[ROW][C]45[/C][C]101.3[/C][C]101.472[/C][C]101.525[/C][C]-0.053125[/C][C]-0.171875[/C][/ROW]
[ROW][C]46[/C][C]102.8[/C][C]102.283[/C][C]102.275[/C][C]0.00790441[/C][C]0.517096[/C][/ROW]
[ROW][C]47[/C][C]103.2[/C][C]103.32[/C][C]103.087[/C][C]0.232169[/C][C]-0.119669[/C][/ROW]
[ROW][C]48[/C][C]103[/C][C]103.651[/C][C]103.837[/C][C]-0.186949[/C][C]-0.650551[/C][/ROW]
[ROW][C]49[/C][C]105.4[/C][C]104.272[/C][C]104.325[/C][C]-0.053125[/C][C]1.12812[/C][/ROW]
[ROW][C]50[/C][C]104.7[/C][C]104.858[/C][C]104.85[/C][C]0.00790441[/C][C]-0.157904[/C][/ROW]
[ROW][C]51[/C][C]105.2[/C][C]105.032[/C][C]104.8[/C][C]0.232169[/C][C]0.167831[/C][/ROW]
[ROW][C]52[/C][C]105.2[/C][C]103.738[/C][C]103.925[/C][C]-0.186949[/C][C]1.46195[/C][/ROW]
[ROW][C]53[/C][C]102.8[/C][C]102.647[/C][C]102.7[/C][C]-0.053125[/C][C]0.153125[/C][/ROW]
[ROW][C]54[/C][C]100.3[/C][C]101.308[/C][C]101.3[/C][C]0.00790441[/C][C]-1.0079[/C][/ROW]
[ROW][C]55[/C][C]99.8[/C][C]100.532[/C][C]100.3[/C][C]0.232169[/C][C]-0.732169[/C][/ROW]
[ROW][C]56[/C][C]99.4[/C][C]99.8256[/C][C]100.012[/C][C]-0.186949[/C][C]-0.425551[/C][/ROW]
[ROW][C]57[/C][C]100.6[/C][C]100.022[/C][C]100.075[/C][C]-0.053125[/C][C]0.578125[/C][/ROW]
[ROW][C]58[/C][C]100.2[/C][C]100.083[/C][C]100.075[/C][C]0.00790441[/C][C]0.117096[/C][/ROW]
[ROW][C]59[/C][C]100.4[/C][C]99.7697[/C][C]99.5375[/C][C]0.232169[/C][C]0.630331[/C][/ROW]
[ROW][C]60[/C][C]98.8[/C][C]98.4006[/C][C]98.5875[/C][C]-0.186949[/C][C]0.399449[/C][/ROW]
[ROW][C]61[/C][C]96.9[/C][C]97.5094[/C][C]97.5625[/C][C]-0.053125[/C][C]-0.609375[/C][/ROW]
[ROW][C]62[/C][C]96.3[/C][C]96.3704[/C][C]96.3625[/C][C]0.00790441[/C][C]-0.0704044[/C][/ROW]
[ROW][C]63[/C][C]96.1[/C][C]95.3322[/C][C]95.1[/C][C]0.232169[/C][C]0.767831[/C][/ROW]
[ROW][C]64[/C][C]93.5[/C][C]93.7381[/C][C]93.925[/C][C]-0.186949[/C][C]-0.238051[/C][/ROW]
[ROW][C]65[/C][C]92.1[/C][C]92.2719[/C][C]92.325[/C][C]-0.053125[/C][C]-0.171875[/C][/ROW]
[ROW][C]66[/C][C]91.7[/C][C]90.4204[/C][C]90.4125[/C][C]0.00790441[/C][C]1.2796[/C][/ROW]
[ROW][C]67[/C][C]87.9[/C][C]88.8572[/C][C]88.625[/C][C]0.232169[/C][C]-0.957169[/C][/ROW]
[ROW][C]68[/C][C]86.4[/C][C]86.2881[/C][C]86.475[/C][C]-0.186949[/C][C]0.111949[/C][/ROW]
[ROW][C]69[/C][C]84.9[/C][C]84.5094[/C][C]84.5625[/C][C]-0.053125[/C][C]0.390625[/C][/ROW]
[ROW][C]70[/C][C]81.7[/C][C]83.4954[/C][C]83.4875[/C][C]0.00790441[/C][C]-1.7954[/C][/ROW]
[ROW][C]71[/C][C]82.6[/C][C]NA[/C][C]NA[/C][C]0.232169[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]83.1[/C][C]NA[/C][C]NA[/C][C]-0.186949[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260834&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260834&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	37.3	NA	NA	-0.053125	NA
2	39.5	NA	NA	0.00790441	NA
3	40.6	40.4322	40.2	0.232169	0.167831
4	41.4	41.0131	41.2	-0.186949	0.386949
5	41.3	42.0719	42.125	-0.053125	-0.771875
6	43.5	42.9954	42.9875	0.00790441	0.504596
7	44	44.2947	44.0625	0.232169	-0.294669
8	44.9	45.0006	45.1875	-0.186949	-0.100551
9	46.4	46.2094	46.2625	-0.053125	0.190625
10	47.4	47.4579	47.45	0.00790441	-0.0579044
11	48.7	48.8697	48.6375	0.232169	-0.169669
12	49.7	49.7631	49.95	-0.186949	-0.0630515
13	51.1	51.5594	51.6125	-0.053125	-0.459375
14	53.2	53.6079	53.6	0.00790441	-0.407904
15	56.2	56.0697	55.8375	0.232169	0.130331
16	58.1	58.2006	58.3875	-0.186949	-0.100551
17	60.6	61.0969	61.15	-0.053125	-0.496875
18	64.1	63.7954	63.7875	0.00790441	0.304596
19	67.4	66.5447	66.3125	0.232169	0.855331
20	68	68.5006	68.6875	-0.186949	-0.500551
21	70.9	70.6594	70.7125	-0.053125	0.240625
22	72.8	72.6704	72.6625	0.00790441	0.129596
23	74.9	74.6697	74.4375	0.232169	0.230331
24	76.1	75.6756	75.8625	-0.186949	0.424449
25	77	77.1094	77.1625	-0.053125	-0.109375
26	78.1	78.2579	78.25	0.00790441	-0.157904
27	80	79.6447	79.4125	0.232169	0.355331
28	79.7	80.7131	80.9	-0.186949	-1.01305
29	82.7	82.0594	82.1125	-0.053125	0.640625
30	84.3	83.3329	83.325	0.00790441	0.967096
31	83.5	84.8697	84.6375	0.232169	-1.36967
32	85.9	85.5256	85.7125	-0.186949	0.374449
33	87	87.0844	87.1375	-0.053125	-0.084375
34	88.6	88.7079	88.7	0.00790441	-0.107904
35	90.6	90.1822	89.95	0.232169	0.417831
36	91.3	90.9131	91.1	-0.186949	0.386949
37	91.6	92.1719	92.225	-0.053125	-0.571875
38	93.2	93.2704	93.2625	0.00790441	-0.0704044
39	95	94.7072	94.475	0.232169	0.292831
40	95.2	95.6881	95.875	-0.186949	-0.488051
41	97.4	97.0719	97.125	-0.053125	0.328125
42	98.6	98.3829	98.375	0.00790441	0.217096
43	99.6	99.7697	99.5375	0.232169	-0.169669
44	100.6	100.363	100.55	-0.186949	0.236949
45	101.3	101.472	101.525	-0.053125	-0.171875
46	102.8	102.283	102.275	0.00790441	0.517096
47	103.2	103.32	103.087	0.232169	-0.119669
48	103	103.651	103.837	-0.186949	-0.650551
49	105.4	104.272	104.325	-0.053125	1.12812
50	104.7	104.858	104.85	0.00790441	-0.157904
51	105.2	105.032	104.8	0.232169	0.167831
52	105.2	103.738	103.925	-0.186949	1.46195
53	102.8	102.647	102.7	-0.053125	0.153125
54	100.3	101.308	101.3	0.00790441	-1.0079
55	99.8	100.532	100.3	0.232169	-0.732169
56	99.4	99.8256	100.012	-0.186949	-0.425551
57	100.6	100.022	100.075	-0.053125	0.578125
58	100.2	100.083	100.075	0.00790441	0.117096
59	100.4	99.7697	99.5375	0.232169	0.630331
60	98.8	98.4006	98.5875	-0.186949	0.399449
61	96.9	97.5094	97.5625	-0.053125	-0.609375
62	96.3	96.3704	96.3625	0.00790441	-0.0704044
63	96.1	95.3322	95.1	0.232169	0.767831
64	93.5	93.7381	93.925	-0.186949	-0.238051
65	92.1	92.2719	92.325	-0.053125	-0.171875
66	91.7	90.4204	90.4125	0.00790441	1.2796
67	87.9	88.8572	88.625	0.232169	-0.957169
68	86.4	86.2881	86.475	-0.186949	0.111949
69	84.9	84.5094	84.5625	-0.053125	0.390625
70	81.7	83.4954	83.4875	0.00790441	-1.7954
71	82.6	NA	NA	0.232169	NA
72	83.1	NA	NA	-0.186949	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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