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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 10:46:48 +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/2016/Apr/25/t14615776413e4i9785fchvste.htm/, Retrieved Mon, 06 May 2024 09:08:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294678, Retrieved Mon, 06 May 2024 09:08:54 +0000

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116

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-       [Classical Decomposition] [] [2016-04-25 09:46:48] [55e0f811d0de406b35493d0ca672d497] [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' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294678&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294678&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294678&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	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	83.61	NA	NA	-0.484917	NA
2	83.89	NA	NA	-0.265	NA
3	83.4	NA	NA	-0.725083	NA
4	82.96	NA	NA	-0.538167	NA
5	82.76	NA	NA	0.0338333	NA
6	83.35	NA	NA	0.3215	NA
7	87.78	87.3182	86.6392	0.679	0.461833
8	88.99	88.1595	87.4075	0.752	0.8305
9	88.92	88.8552	88.1871	0.668167	0.06475
10	88.91	89.3419	89.1121	0.229833	-0.431917
11	89.79	90.2868	90.3846	-0.09775	-0.496833
12	90.54	91.4149	91.9883	-0.573417	-0.874917
13	93.15	93.0284	93.5133	-0.484917	0.121583
14	92.79	94.5579	94.8229	-0.265	-1.76792
15	93.21	95.3878	96.1129	-0.725083	-2.17783
16	95.35	96.9106	97.4488	-0.538167	-1.56058
17	100.91	98.7909	98.7571	0.0338333	2.11908
18	103.69	100.304	99.9829	0.3215	3.38558
19	104.04	101.747	101.068	0.679	2.29308
20	104.16	102.82	102.068	0.752	1.33967
21	104.71	103.722	103.054	0.668167	0.988083
22	105.18	104.086	103.856	0.229833	1.09433
23	104.92	104.153	104.25	-0.09775	0.767333
24	104.83	103.636	104.209	-0.573417	1.19425
25	104.9	103.497	103.982	-0.484917	1.40283
26	105.05	103.522	103.787	-0.265	1.5275
27	104.6	102.899	103.625	-0.725083	1.7005
28	103.21	102.886	103.425	-0.538167	0.323583
29	102.52	103.216	103.182	0.0338333	-0.696333
30	101.09	103.251	102.93	0.3215	-2.16108
31	101.19	103.345	102.666	0.679	-2.15483
32	102.34	103.15	102.398	0.752	-0.809917
33	102.62	102.798	102.13	0.668167	-0.17775
34	102.47	102.102	101.872	0.229833	0.368083
35	101.82	101.55	101.648	-0.09775	0.27025
36	101.86	100.919	101.492	-0.573417	0.941333
37	101.54	100.91	101.395	-0.484917	0.630333
38	101.98	100.932	101.197	-0.265	1.0475
39	101.23	100.177	100.902	-0.725083	1.053
40	100.4	100.091	100.629	-0.538167	0.309417
41	99.94	100.427	100.393	0.0338333	-0.487167
42	99.94	100.464	100.142	0.3215	-0.523583
43	100	100.496	99.8167	0.679	-0.495667
44	98.8	100.173	99.4212	0.752	-1.37325
45	99.07	99.664	98.9958	0.668167	-0.594
46	99.46	98.8769	98.6471	0.229833	0.583083
47	99.18	98.2839	98.3817	-0.09775	0.896083
48	98.47	97.5603	98.1337	-0.573417	0.909667
49	97.12	97.5276	98.0125	-0.484917	-0.407583
50	96.91	97.8167	98.0817	-0.265	-0.906667
51	96.09	97.5037	98.2287	-0.725083	-1.41367
52	97.17	97.7789	98.3171	-0.538167	-0.608917
53	96.8	98.418	98.3842	0.0338333	-1.618
54	97.13	98.8248	98.5033	0.3215	-1.69483
55	99.9	99.424	98.745	0.679	0.476
56	100.56	99.9666	99.2146	0.752	0.593417
57	100.84	100.541	99.8725	0.668167	0.299333
58	99.81	100.843	100.613	0.229833	-1.03317
59	100.44	101.296	101.394	-0.09775	-0.856417
60	100.07	101.66	102.233	-0.573417	-1.58992
61	101.32	102.487	102.972	-0.484917	-1.16675
62	103.98	103.3	103.565	-0.265	0.68
63	104.81	103.392	104.117	-0.725083	1.41842
64	106.23	104.113	104.651	-0.538167	2.11692
65	106.48	105.217	105.183	0.0338333	1.26283
66	107.59	106.016	105.694	0.3215	1.57433
67	107.16	NA	NA	0.679	NA
68	107.54	NA	NA	0.752	NA
69	107.1	NA	NA	0.668167	NA
70	106.38	NA	NA	0.229833	NA
71	106.64	NA	NA	-0.09775	NA
72	106.13	NA	NA	-0.573417	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 83.61 & NA & NA & -0.484917 & NA \tabularnewline
2 & 83.89 & NA & NA & -0.265 & NA \tabularnewline
3 & 83.4 & NA & NA & -0.725083 & NA \tabularnewline
4 & 82.96 & NA & NA & -0.538167 & NA \tabularnewline
5 & 82.76 & NA & NA & 0.0338333 & NA \tabularnewline
6 & 83.35 & NA & NA & 0.3215 & NA \tabularnewline
7 & 87.78 & 87.3182 & 86.6392 & 0.679 & 0.461833 \tabularnewline
8 & 88.99 & 88.1595 & 87.4075 & 0.752 & 0.8305 \tabularnewline
9 & 88.92 & 88.8552 & 88.1871 & 0.668167 & 0.06475 \tabularnewline
10 & 88.91 & 89.3419 & 89.1121 & 0.229833 & -0.431917 \tabularnewline
11 & 89.79 & 90.2868 & 90.3846 & -0.09775 & -0.496833 \tabularnewline
12 & 90.54 & 91.4149 & 91.9883 & -0.573417 & -0.874917 \tabularnewline
13 & 93.15 & 93.0284 & 93.5133 & -0.484917 & 0.121583 \tabularnewline
14 & 92.79 & 94.5579 & 94.8229 & -0.265 & -1.76792 \tabularnewline
15 & 93.21 & 95.3878 & 96.1129 & -0.725083 & -2.17783 \tabularnewline
16 & 95.35 & 96.9106 & 97.4488 & -0.538167 & -1.56058 \tabularnewline
17 & 100.91 & 98.7909 & 98.7571 & 0.0338333 & 2.11908 \tabularnewline
18 & 103.69 & 100.304 & 99.9829 & 0.3215 & 3.38558 \tabularnewline
19 & 104.04 & 101.747 & 101.068 & 0.679 & 2.29308 \tabularnewline
20 & 104.16 & 102.82 & 102.068 & 0.752 & 1.33967 \tabularnewline
21 & 104.71 & 103.722 & 103.054 & 0.668167 & 0.988083 \tabularnewline
22 & 105.18 & 104.086 & 103.856 & 0.229833 & 1.09433 \tabularnewline
23 & 104.92 & 104.153 & 104.25 & -0.09775 & 0.767333 \tabularnewline
24 & 104.83 & 103.636 & 104.209 & -0.573417 & 1.19425 \tabularnewline
25 & 104.9 & 103.497 & 103.982 & -0.484917 & 1.40283 \tabularnewline
26 & 105.05 & 103.522 & 103.787 & -0.265 & 1.5275 \tabularnewline
27 & 104.6 & 102.899 & 103.625 & -0.725083 & 1.7005 \tabularnewline
28 & 103.21 & 102.886 & 103.425 & -0.538167 & 0.323583 \tabularnewline
29 & 102.52 & 103.216 & 103.182 & 0.0338333 & -0.696333 \tabularnewline
30 & 101.09 & 103.251 & 102.93 & 0.3215 & -2.16108 \tabularnewline
31 & 101.19 & 103.345 & 102.666 & 0.679 & -2.15483 \tabularnewline
32 & 102.34 & 103.15 & 102.398 & 0.752 & -0.809917 \tabularnewline
33 & 102.62 & 102.798 & 102.13 & 0.668167 & -0.17775 \tabularnewline
34 & 102.47 & 102.102 & 101.872 & 0.229833 & 0.368083 \tabularnewline
35 & 101.82 & 101.55 & 101.648 & -0.09775 & 0.27025 \tabularnewline
36 & 101.86 & 100.919 & 101.492 & -0.573417 & 0.941333 \tabularnewline
37 & 101.54 & 100.91 & 101.395 & -0.484917 & 0.630333 \tabularnewline
38 & 101.98 & 100.932 & 101.197 & -0.265 & 1.0475 \tabularnewline
39 & 101.23 & 100.177 & 100.902 & -0.725083 & 1.053 \tabularnewline
40 & 100.4 & 100.091 & 100.629 & -0.538167 & 0.309417 \tabularnewline
41 & 99.94 & 100.427 & 100.393 & 0.0338333 & -0.487167 \tabularnewline
42 & 99.94 & 100.464 & 100.142 & 0.3215 & -0.523583 \tabularnewline
43 & 100 & 100.496 & 99.8167 & 0.679 & -0.495667 \tabularnewline
44 & 98.8 & 100.173 & 99.4212 & 0.752 & -1.37325 \tabularnewline
45 & 99.07 & 99.664 & 98.9958 & 0.668167 & -0.594 \tabularnewline
46 & 99.46 & 98.8769 & 98.6471 & 0.229833 & 0.583083 \tabularnewline
47 & 99.18 & 98.2839 & 98.3817 & -0.09775 & 0.896083 \tabularnewline
48 & 98.47 & 97.5603 & 98.1337 & -0.573417 & 0.909667 \tabularnewline
49 & 97.12 & 97.5276 & 98.0125 & -0.484917 & -0.407583 \tabularnewline
50 & 96.91 & 97.8167 & 98.0817 & -0.265 & -0.906667 \tabularnewline
51 & 96.09 & 97.5037 & 98.2287 & -0.725083 & -1.41367 \tabularnewline
52 & 97.17 & 97.7789 & 98.3171 & -0.538167 & -0.608917 \tabularnewline
53 & 96.8 & 98.418 & 98.3842 & 0.0338333 & -1.618 \tabularnewline
54 & 97.13 & 98.8248 & 98.5033 & 0.3215 & -1.69483 \tabularnewline
55 & 99.9 & 99.424 & 98.745 & 0.679 & 0.476 \tabularnewline
56 & 100.56 & 99.9666 & 99.2146 & 0.752 & 0.593417 \tabularnewline
57 & 100.84 & 100.541 & 99.8725 & 0.668167 & 0.299333 \tabularnewline
58 & 99.81 & 100.843 & 100.613 & 0.229833 & -1.03317 \tabularnewline
59 & 100.44 & 101.296 & 101.394 & -0.09775 & -0.856417 \tabularnewline
60 & 100.07 & 101.66 & 102.233 & -0.573417 & -1.58992 \tabularnewline
61 & 101.32 & 102.487 & 102.972 & -0.484917 & -1.16675 \tabularnewline
62 & 103.98 & 103.3 & 103.565 & -0.265 & 0.68 \tabularnewline
63 & 104.81 & 103.392 & 104.117 & -0.725083 & 1.41842 \tabularnewline
64 & 106.23 & 104.113 & 104.651 & -0.538167 & 2.11692 \tabularnewline
65 & 106.48 & 105.217 & 105.183 & 0.0338333 & 1.26283 \tabularnewline
66 & 107.59 & 106.016 & 105.694 & 0.3215 & 1.57433 \tabularnewline
67 & 107.16 & NA & NA & 0.679 & NA \tabularnewline
68 & 107.54 & NA & NA & 0.752 & NA \tabularnewline
69 & 107.1 & NA & NA & 0.668167 & NA \tabularnewline
70 & 106.38 & NA & NA & 0.229833 & NA \tabularnewline
71 & 106.64 & NA & NA & -0.09775 & NA \tabularnewline
72 & 106.13 & NA & NA & -0.573417 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294678&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]83.61[/C][C]NA[/C][C]NA[/C][C]-0.484917[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]83.89[/C][C]NA[/C][C]NA[/C][C]-0.265[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]83.4[/C][C]NA[/C][C]NA[/C][C]-0.725083[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]82.96[/C][C]NA[/C][C]NA[/C][C]-0.538167[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]82.76[/C][C]NA[/C][C]NA[/C][C]0.0338333[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]83.35[/C][C]NA[/C][C]NA[/C][C]0.3215[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]87.78[/C][C]87.3182[/C][C]86.6392[/C][C]0.679[/C][C]0.461833[/C][/ROW]
[ROW][C]8[/C][C]88.99[/C][C]88.1595[/C][C]87.4075[/C][C]0.752[/C][C]0.8305[/C][/ROW]
[ROW][C]9[/C][C]88.92[/C][C]88.8552[/C][C]88.1871[/C][C]0.668167[/C][C]0.06475[/C][/ROW]
[ROW][C]10[/C][C]88.91[/C][C]89.3419[/C][C]89.1121[/C][C]0.229833[/C][C]-0.431917[/C][/ROW]
[ROW][C]11[/C][C]89.79[/C][C]90.2868[/C][C]90.3846[/C][C]-0.09775[/C][C]-0.496833[/C][/ROW]
[ROW][C]12[/C][C]90.54[/C][C]91.4149[/C][C]91.9883[/C][C]-0.573417[/C][C]-0.874917[/C][/ROW]
[ROW][C]13[/C][C]93.15[/C][C]93.0284[/C][C]93.5133[/C][C]-0.484917[/C][C]0.121583[/C][/ROW]
[ROW][C]14[/C][C]92.79[/C][C]94.5579[/C][C]94.8229[/C][C]-0.265[/C][C]-1.76792[/C][/ROW]
[ROW][C]15[/C][C]93.21[/C][C]95.3878[/C][C]96.1129[/C][C]-0.725083[/C][C]-2.17783[/C][/ROW]
[ROW][C]16[/C][C]95.35[/C][C]96.9106[/C][C]97.4488[/C][C]-0.538167[/C][C]-1.56058[/C][/ROW]
[ROW][C]17[/C][C]100.91[/C][C]98.7909[/C][C]98.7571[/C][C]0.0338333[/C][C]2.11908[/C][/ROW]
[ROW][C]18[/C][C]103.69[/C][C]100.304[/C][C]99.9829[/C][C]0.3215[/C][C]3.38558[/C][/ROW]
[ROW][C]19[/C][C]104.04[/C][C]101.747[/C][C]101.068[/C][C]0.679[/C][C]2.29308[/C][/ROW]
[ROW][C]20[/C][C]104.16[/C][C]102.82[/C][C]102.068[/C][C]0.752[/C][C]1.33967[/C][/ROW]
[ROW][C]21[/C][C]104.71[/C][C]103.722[/C][C]103.054[/C][C]0.668167[/C][C]0.988083[/C][/ROW]
[ROW][C]22[/C][C]105.18[/C][C]104.086[/C][C]103.856[/C][C]0.229833[/C][C]1.09433[/C][/ROW]
[ROW][C]23[/C][C]104.92[/C][C]104.153[/C][C]104.25[/C][C]-0.09775[/C][C]0.767333[/C][/ROW]
[ROW][C]24[/C][C]104.83[/C][C]103.636[/C][C]104.209[/C][C]-0.573417[/C][C]1.19425[/C][/ROW]
[ROW][C]25[/C][C]104.9[/C][C]103.497[/C][C]103.982[/C][C]-0.484917[/C][C]1.40283[/C][/ROW]
[ROW][C]26[/C][C]105.05[/C][C]103.522[/C][C]103.787[/C][C]-0.265[/C][C]1.5275[/C][/ROW]
[ROW][C]27[/C][C]104.6[/C][C]102.899[/C][C]103.625[/C][C]-0.725083[/C][C]1.7005[/C][/ROW]
[ROW][C]28[/C][C]103.21[/C][C]102.886[/C][C]103.425[/C][C]-0.538167[/C][C]0.323583[/C][/ROW]
[ROW][C]29[/C][C]102.52[/C][C]103.216[/C][C]103.182[/C][C]0.0338333[/C][C]-0.696333[/C][/ROW]
[ROW][C]30[/C][C]101.09[/C][C]103.251[/C][C]102.93[/C][C]0.3215[/C][C]-2.16108[/C][/ROW]
[ROW][C]31[/C][C]101.19[/C][C]103.345[/C][C]102.666[/C][C]0.679[/C][C]-2.15483[/C][/ROW]
[ROW][C]32[/C][C]102.34[/C][C]103.15[/C][C]102.398[/C][C]0.752[/C][C]-0.809917[/C][/ROW]
[ROW][C]33[/C][C]102.62[/C][C]102.798[/C][C]102.13[/C][C]0.668167[/C][C]-0.17775[/C][/ROW]
[ROW][C]34[/C][C]102.47[/C][C]102.102[/C][C]101.872[/C][C]0.229833[/C][C]0.368083[/C][/ROW]
[ROW][C]35[/C][C]101.82[/C][C]101.55[/C][C]101.648[/C][C]-0.09775[/C][C]0.27025[/C][/ROW]
[ROW][C]36[/C][C]101.86[/C][C]100.919[/C][C]101.492[/C][C]-0.573417[/C][C]0.941333[/C][/ROW]
[ROW][C]37[/C][C]101.54[/C][C]100.91[/C][C]101.395[/C][C]-0.484917[/C][C]0.630333[/C][/ROW]
[ROW][C]38[/C][C]101.98[/C][C]100.932[/C][C]101.197[/C][C]-0.265[/C][C]1.0475[/C][/ROW]
[ROW][C]39[/C][C]101.23[/C][C]100.177[/C][C]100.902[/C][C]-0.725083[/C][C]1.053[/C][/ROW]
[ROW][C]40[/C][C]100.4[/C][C]100.091[/C][C]100.629[/C][C]-0.538167[/C][C]0.309417[/C][/ROW]
[ROW][C]41[/C][C]99.94[/C][C]100.427[/C][C]100.393[/C][C]0.0338333[/C][C]-0.487167[/C][/ROW]
[ROW][C]42[/C][C]99.94[/C][C]100.464[/C][C]100.142[/C][C]0.3215[/C][C]-0.523583[/C][/ROW]
[ROW][C]43[/C][C]100[/C][C]100.496[/C][C]99.8167[/C][C]0.679[/C][C]-0.495667[/C][/ROW]
[ROW][C]44[/C][C]98.8[/C][C]100.173[/C][C]99.4212[/C][C]0.752[/C][C]-1.37325[/C][/ROW]
[ROW][C]45[/C][C]99.07[/C][C]99.664[/C][C]98.9958[/C][C]0.668167[/C][C]-0.594[/C][/ROW]
[ROW][C]46[/C][C]99.46[/C][C]98.8769[/C][C]98.6471[/C][C]0.229833[/C][C]0.583083[/C][/ROW]
[ROW][C]47[/C][C]99.18[/C][C]98.2839[/C][C]98.3817[/C][C]-0.09775[/C][C]0.896083[/C][/ROW]
[ROW][C]48[/C][C]98.47[/C][C]97.5603[/C][C]98.1337[/C][C]-0.573417[/C][C]0.909667[/C][/ROW]
[ROW][C]49[/C][C]97.12[/C][C]97.5276[/C][C]98.0125[/C][C]-0.484917[/C][C]-0.407583[/C][/ROW]
[ROW][C]50[/C][C]96.91[/C][C]97.8167[/C][C]98.0817[/C][C]-0.265[/C][C]-0.906667[/C][/ROW]
[ROW][C]51[/C][C]96.09[/C][C]97.5037[/C][C]98.2287[/C][C]-0.725083[/C][C]-1.41367[/C][/ROW]
[ROW][C]52[/C][C]97.17[/C][C]97.7789[/C][C]98.3171[/C][C]-0.538167[/C][C]-0.608917[/C][/ROW]
[ROW][C]53[/C][C]96.8[/C][C]98.418[/C][C]98.3842[/C][C]0.0338333[/C][C]-1.618[/C][/ROW]
[ROW][C]54[/C][C]97.13[/C][C]98.8248[/C][C]98.5033[/C][C]0.3215[/C][C]-1.69483[/C][/ROW]
[ROW][C]55[/C][C]99.9[/C][C]99.424[/C][C]98.745[/C][C]0.679[/C][C]0.476[/C][/ROW]
[ROW][C]56[/C][C]100.56[/C][C]99.9666[/C][C]99.2146[/C][C]0.752[/C][C]0.593417[/C][/ROW]
[ROW][C]57[/C][C]100.84[/C][C]100.541[/C][C]99.8725[/C][C]0.668167[/C][C]0.299333[/C][/ROW]
[ROW][C]58[/C][C]99.81[/C][C]100.843[/C][C]100.613[/C][C]0.229833[/C][C]-1.03317[/C][/ROW]
[ROW][C]59[/C][C]100.44[/C][C]101.296[/C][C]101.394[/C][C]-0.09775[/C][C]-0.856417[/C][/ROW]
[ROW][C]60[/C][C]100.07[/C][C]101.66[/C][C]102.233[/C][C]-0.573417[/C][C]-1.58992[/C][/ROW]
[ROW][C]61[/C][C]101.32[/C][C]102.487[/C][C]102.972[/C][C]-0.484917[/C][C]-1.16675[/C][/ROW]
[ROW][C]62[/C][C]103.98[/C][C]103.3[/C][C]103.565[/C][C]-0.265[/C][C]0.68[/C][/ROW]
[ROW][C]63[/C][C]104.81[/C][C]103.392[/C][C]104.117[/C][C]-0.725083[/C][C]1.41842[/C][/ROW]
[ROW][C]64[/C][C]106.23[/C][C]104.113[/C][C]104.651[/C][C]-0.538167[/C][C]2.11692[/C][/ROW]
[ROW][C]65[/C][C]106.48[/C][C]105.217[/C][C]105.183[/C][C]0.0338333[/C][C]1.26283[/C][/ROW]
[ROW][C]66[/C][C]107.59[/C][C]106.016[/C][C]105.694[/C][C]0.3215[/C][C]1.57433[/C][/ROW]
[ROW][C]67[/C][C]107.16[/C][C]NA[/C][C]NA[/C][C]0.679[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]107.54[/C][C]NA[/C][C]NA[/C][C]0.752[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]107.1[/C][C]NA[/C][C]NA[/C][C]0.668167[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]106.38[/C][C]NA[/C][C]NA[/C][C]0.229833[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]106.64[/C][C]NA[/C][C]NA[/C][C]-0.09775[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]106.13[/C][C]NA[/C][C]NA[/C][C]-0.573417[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294678&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294678&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	83.61	NA	NA	-0.484917	NA
2	83.89	NA	NA	-0.265	NA
3	83.4	NA	NA	-0.725083	NA
4	82.96	NA	NA	-0.538167	NA
5	82.76	NA	NA	0.0338333	NA
6	83.35	NA	NA	0.3215	NA
7	87.78	87.3182	86.6392	0.679	0.461833
8	88.99	88.1595	87.4075	0.752	0.8305
9	88.92	88.8552	88.1871	0.668167	0.06475
10	88.91	89.3419	89.1121	0.229833	-0.431917
11	89.79	90.2868	90.3846	-0.09775	-0.496833
12	90.54	91.4149	91.9883	-0.573417	-0.874917
13	93.15	93.0284	93.5133	-0.484917	0.121583
14	92.79	94.5579	94.8229	-0.265	-1.76792
15	93.21	95.3878	96.1129	-0.725083	-2.17783
16	95.35	96.9106	97.4488	-0.538167	-1.56058
17	100.91	98.7909	98.7571	0.0338333	2.11908
18	103.69	100.304	99.9829	0.3215	3.38558
19	104.04	101.747	101.068	0.679	2.29308
20	104.16	102.82	102.068	0.752	1.33967
21	104.71	103.722	103.054	0.668167	0.988083
22	105.18	104.086	103.856	0.229833	1.09433
23	104.92	104.153	104.25	-0.09775	0.767333
24	104.83	103.636	104.209	-0.573417	1.19425
25	104.9	103.497	103.982	-0.484917	1.40283
26	105.05	103.522	103.787	-0.265	1.5275
27	104.6	102.899	103.625	-0.725083	1.7005
28	103.21	102.886	103.425	-0.538167	0.323583
29	102.52	103.216	103.182	0.0338333	-0.696333
30	101.09	103.251	102.93	0.3215	-2.16108
31	101.19	103.345	102.666	0.679	-2.15483
32	102.34	103.15	102.398	0.752	-0.809917
33	102.62	102.798	102.13	0.668167	-0.17775
34	102.47	102.102	101.872	0.229833	0.368083
35	101.82	101.55	101.648	-0.09775	0.27025
36	101.86	100.919	101.492	-0.573417	0.941333
37	101.54	100.91	101.395	-0.484917	0.630333
38	101.98	100.932	101.197	-0.265	1.0475
39	101.23	100.177	100.902	-0.725083	1.053
40	100.4	100.091	100.629	-0.538167	0.309417
41	99.94	100.427	100.393	0.0338333	-0.487167
42	99.94	100.464	100.142	0.3215	-0.523583
43	100	100.496	99.8167	0.679	-0.495667
44	98.8	100.173	99.4212	0.752	-1.37325
45	99.07	99.664	98.9958	0.668167	-0.594
46	99.46	98.8769	98.6471	0.229833	0.583083
47	99.18	98.2839	98.3817	-0.09775	0.896083
48	98.47	97.5603	98.1337	-0.573417	0.909667
49	97.12	97.5276	98.0125	-0.484917	-0.407583
50	96.91	97.8167	98.0817	-0.265	-0.906667
51	96.09	97.5037	98.2287	-0.725083	-1.41367
52	97.17	97.7789	98.3171	-0.538167	-0.608917
53	96.8	98.418	98.3842	0.0338333	-1.618
54	97.13	98.8248	98.5033	0.3215	-1.69483
55	99.9	99.424	98.745	0.679	0.476
56	100.56	99.9666	99.2146	0.752	0.593417
57	100.84	100.541	99.8725	0.668167	0.299333
58	99.81	100.843	100.613	0.229833	-1.03317
59	100.44	101.296	101.394	-0.09775	-0.856417
60	100.07	101.66	102.233	-0.573417	-1.58992
61	101.32	102.487	102.972	-0.484917	-1.16675
62	103.98	103.3	103.565	-0.265	0.68
63	104.81	103.392	104.117	-0.725083	1.41842
64	106.23	104.113	104.651	-0.538167	2.11692
65	106.48	105.217	105.183	0.0338333	1.26283
66	107.59	106.016	105.694	0.3215	1.57433
67	107.16	NA	NA	0.679	NA
68	107.54	NA	NA	0.752	NA
69	107.1	NA	NA	0.668167	NA
70	106.38	NA	NA	0.229833	NA
71	106.64	NA	NA	-0.09775	NA
72	106.13	NA	NA	-0.573417	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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