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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Thu, 24 Nov 2016 17:50:59 +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/2016/Nov/24/t1480009906ex5x9efiuuk16kn.htm/, Retrieved Wed, 08 May 2024 02:21:44 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 08 May 2024 02:21:44 +0200

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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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	134.93	NA	NA	-0.560687	NA
2	134.37	NA	NA	-1.51394	NA
3	132.98	NA	NA	-2.43294	NA
4	130.1	NA	NA	-2.88202	NA
5	128.24	NA	NA	-1.43627	NA
6	127.52	NA	NA	0.704729	NA
7	126.94	130.41	129.332	1.07815	-3.46981
8	127.38	130.097	128.528	1.56898	-2.7169
9	130.95	130.074	127.622	2.45215	0.875771
10	128.65	128.227	126.717	1.50973	0.422771
11	127.37	127.027	125.912	1.11523	0.342688
12	127.04	125.567	125.17	0.396896	1.47269
13	125.95	123.886	124.446	-0.560687	2.06444
14	124.06	122.243	123.757	-1.51394	1.81685
15	121.55	120.53	122.962	-2.43294	1.02044
16	119.82	119.149	122.031	-2.88202	0.670771
17	119.19	119.644	121.08	-1.43627	-0.454146
18	118.77	120.798	120.093	0.704729	-2.02765
19	118.31	120.121	119.043	1.07815	-1.81148
20	119.47	119.54	117.971	1.56898	-0.0698125
21	119.79	119.441	116.989	2.45215	0.349104
22	117.46	117.619	116.11	1.50973	-0.159312
23	115.74	116.334	115.219	1.11523	-0.593979
24	114.97	114.681	114.284	0.396896	0.289354
25	112.83	113.165	113.725	-0.560687	-0.334729
26	111.44	111.908	113.422	-1.51394	-0.468146
27	110.6	110.534	112.967	-2.43294	0.0658542
28	109.67	109.696	112.578	-2.88202	-0.0258958
29	107.96	110.964	112.4	-1.43627	-3.00415
30	107.56	113.018	112.314	0.704729	-5.45848
31	116.12	113.324	112.246	1.07815	2.79602
32	114.38	113.767	112.198	1.56898	0.613104
33	113.96	114.594	112.142	2.45215	-0.633813
34	113.95	113.618	112.109	1.50973	0.331521
35	114.99	113.315	112.2	1.11523	1.67519
36	113.64	112.996	112.599	0.396896	0.644354
37	112.53	112.266	112.827	-0.560687	0.264021
38	110.59	111.26	112.774	-1.51394	-0.670229
39	110.1	110.328	112.761	-2.43294	-0.228312
40	109.38	109.751	112.633	-2.88202	-0.370896
41	110.43	110.885	112.321	-1.43627	-0.454562
42	114.67	112.58	111.875	0.704729	2.09027
43	114.48	112.511	111.433	1.07815	1.96852
44	114.76	112.607	111.038	1.56898	2.15269
45	113.27	113.054	110.602	2.45215	0.215771
46	111.56	111.596	110.087	1.50973	-0.0363958
47	109.89	110.699	109.584	1.11523	-0.808979
48	108.04	109.305	108.908	0.396896	-1.26481
49	107.53	107.388	107.948	-0.560687	0.142354
50	106.11	105.336	106.85	-1.51394	0.773521
51	104.11	103.288	105.721	-2.43294	0.821688
52	103	101.743	104.625	-2.88202	1.25744
53	104.74	102.122	103.559	-1.43627	2.61752
54	104.14	103.235	102.53	0.704729	0.905271
55	101.98	102.536	101.458	1.07815	-0.556479
56	100.91	101.962	100.393	1.56898	-1.05231
57	100.02	101.9	99.4479	2.45215	-1.88006
58	98.49	100.122	98.6121	1.50973	-1.63181
59	97.38	99.0681	97.9529	1.11523	-1.68815
60	95.86	98.0748	97.6779	0.396896	-2.21481
61	93.99	97.1993	97.76	-0.560687	-3.20931
62	94.09	96.6152	98.1292	-1.51394	-2.52523
63	93.44	96.1929	98.6258	-2.43294	-2.7529
64	93.61	96.2146	99.0967	-2.88202	-2.60465
65	98.31	98.0879	99.5242	-1.43627	0.222104
66	103.97	100.553	99.8479	0.704729	3.41735
67	104.12	NA	NA	1.07815	NA
68	107.63	NA	NA	1.56898	NA
69	105.22	NA	NA	2.45215	NA
70	104.59	NA	NA	1.50973	NA
71	101.54	NA	NA	1.11523	NA
72	99.47	NA	NA	0.396896	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 134.93 & NA & NA & -0.560687 & NA \tabularnewline
2 & 134.37 & NA & NA & -1.51394 & NA \tabularnewline
3 & 132.98 & NA & NA & -2.43294 & NA \tabularnewline
4 & 130.1 & NA & NA & -2.88202 & NA \tabularnewline
5 & 128.24 & NA & NA & -1.43627 & NA \tabularnewline
6 & 127.52 & NA & NA & 0.704729 & NA \tabularnewline
7 & 126.94 & 130.41 & 129.332 & 1.07815 & -3.46981 \tabularnewline
8 & 127.38 & 130.097 & 128.528 & 1.56898 & -2.7169 \tabularnewline
9 & 130.95 & 130.074 & 127.622 & 2.45215 & 0.875771 \tabularnewline
10 & 128.65 & 128.227 & 126.717 & 1.50973 & 0.422771 \tabularnewline
11 & 127.37 & 127.027 & 125.912 & 1.11523 & 0.342688 \tabularnewline
12 & 127.04 & 125.567 & 125.17 & 0.396896 & 1.47269 \tabularnewline
13 & 125.95 & 123.886 & 124.446 & -0.560687 & 2.06444 \tabularnewline
14 & 124.06 & 122.243 & 123.757 & -1.51394 & 1.81685 \tabularnewline
15 & 121.55 & 120.53 & 122.962 & -2.43294 & 1.02044 \tabularnewline
16 & 119.82 & 119.149 & 122.031 & -2.88202 & 0.670771 \tabularnewline
17 & 119.19 & 119.644 & 121.08 & -1.43627 & -0.454146 \tabularnewline
18 & 118.77 & 120.798 & 120.093 & 0.704729 & -2.02765 \tabularnewline
19 & 118.31 & 120.121 & 119.043 & 1.07815 & -1.81148 \tabularnewline
20 & 119.47 & 119.54 & 117.971 & 1.56898 & -0.0698125 \tabularnewline
21 & 119.79 & 119.441 & 116.989 & 2.45215 & 0.349104 \tabularnewline
22 & 117.46 & 117.619 & 116.11 & 1.50973 & -0.159312 \tabularnewline
23 & 115.74 & 116.334 & 115.219 & 1.11523 & -0.593979 \tabularnewline
24 & 114.97 & 114.681 & 114.284 & 0.396896 & 0.289354 \tabularnewline
25 & 112.83 & 113.165 & 113.725 & -0.560687 & -0.334729 \tabularnewline
26 & 111.44 & 111.908 & 113.422 & -1.51394 & -0.468146 \tabularnewline
27 & 110.6 & 110.534 & 112.967 & -2.43294 & 0.0658542 \tabularnewline
28 & 109.67 & 109.696 & 112.578 & -2.88202 & -0.0258958 \tabularnewline
29 & 107.96 & 110.964 & 112.4 & -1.43627 & -3.00415 \tabularnewline
30 & 107.56 & 113.018 & 112.314 & 0.704729 & -5.45848 \tabularnewline
31 & 116.12 & 113.324 & 112.246 & 1.07815 & 2.79602 \tabularnewline
32 & 114.38 & 113.767 & 112.198 & 1.56898 & 0.613104 \tabularnewline
33 & 113.96 & 114.594 & 112.142 & 2.45215 & -0.633813 \tabularnewline
34 & 113.95 & 113.618 & 112.109 & 1.50973 & 0.331521 \tabularnewline
35 & 114.99 & 113.315 & 112.2 & 1.11523 & 1.67519 \tabularnewline
36 & 113.64 & 112.996 & 112.599 & 0.396896 & 0.644354 \tabularnewline
37 & 112.53 & 112.266 & 112.827 & -0.560687 & 0.264021 \tabularnewline
38 & 110.59 & 111.26 & 112.774 & -1.51394 & -0.670229 \tabularnewline
39 & 110.1 & 110.328 & 112.761 & -2.43294 & -0.228312 \tabularnewline
40 & 109.38 & 109.751 & 112.633 & -2.88202 & -0.370896 \tabularnewline
41 & 110.43 & 110.885 & 112.321 & -1.43627 & -0.454562 \tabularnewline
42 & 114.67 & 112.58 & 111.875 & 0.704729 & 2.09027 \tabularnewline
43 & 114.48 & 112.511 & 111.433 & 1.07815 & 1.96852 \tabularnewline
44 & 114.76 & 112.607 & 111.038 & 1.56898 & 2.15269 \tabularnewline
45 & 113.27 & 113.054 & 110.602 & 2.45215 & 0.215771 \tabularnewline
46 & 111.56 & 111.596 & 110.087 & 1.50973 & -0.0363958 \tabularnewline
47 & 109.89 & 110.699 & 109.584 & 1.11523 & -0.808979 \tabularnewline
48 & 108.04 & 109.305 & 108.908 & 0.396896 & -1.26481 \tabularnewline
49 & 107.53 & 107.388 & 107.948 & -0.560687 & 0.142354 \tabularnewline
50 & 106.11 & 105.336 & 106.85 & -1.51394 & 0.773521 \tabularnewline
51 & 104.11 & 103.288 & 105.721 & -2.43294 & 0.821688 \tabularnewline
52 & 103 & 101.743 & 104.625 & -2.88202 & 1.25744 \tabularnewline
53 & 104.74 & 102.122 & 103.559 & -1.43627 & 2.61752 \tabularnewline
54 & 104.14 & 103.235 & 102.53 & 0.704729 & 0.905271 \tabularnewline
55 & 101.98 & 102.536 & 101.458 & 1.07815 & -0.556479 \tabularnewline
56 & 100.91 & 101.962 & 100.393 & 1.56898 & -1.05231 \tabularnewline
57 & 100.02 & 101.9 & 99.4479 & 2.45215 & -1.88006 \tabularnewline
58 & 98.49 & 100.122 & 98.6121 & 1.50973 & -1.63181 \tabularnewline
59 & 97.38 & 99.0681 & 97.9529 & 1.11523 & -1.68815 \tabularnewline
60 & 95.86 & 98.0748 & 97.6779 & 0.396896 & -2.21481 \tabularnewline
61 & 93.99 & 97.1993 & 97.76 & -0.560687 & -3.20931 \tabularnewline
62 & 94.09 & 96.6152 & 98.1292 & -1.51394 & -2.52523 \tabularnewline
63 & 93.44 & 96.1929 & 98.6258 & -2.43294 & -2.7529 \tabularnewline
64 & 93.61 & 96.2146 & 99.0967 & -2.88202 & -2.60465 \tabularnewline
65 & 98.31 & 98.0879 & 99.5242 & -1.43627 & 0.222104 \tabularnewline
66 & 103.97 & 100.553 & 99.8479 & 0.704729 & 3.41735 \tabularnewline
67 & 104.12 & NA & NA & 1.07815 & NA \tabularnewline
68 & 107.63 & NA & NA & 1.56898 & NA \tabularnewline
69 & 105.22 & NA & NA & 2.45215 & NA \tabularnewline
70 & 104.59 & NA & NA & 1.50973 & NA \tabularnewline
71 & 101.54 & NA & NA & 1.11523 & NA \tabularnewline
72 & 99.47 & NA & NA & 0.396896 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]134.93[/C][C]NA[/C][C]NA[/C][C]-0.560687[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]134.37[/C][C]NA[/C][C]NA[/C][C]-1.51394[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]132.98[/C][C]NA[/C][C]NA[/C][C]-2.43294[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]130.1[/C][C]NA[/C][C]NA[/C][C]-2.88202[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]128.24[/C][C]NA[/C][C]NA[/C][C]-1.43627[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]127.52[/C][C]NA[/C][C]NA[/C][C]0.704729[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]126.94[/C][C]130.41[/C][C]129.332[/C][C]1.07815[/C][C]-3.46981[/C][/ROW]
[ROW][C]8[/C][C]127.38[/C][C]130.097[/C][C]128.528[/C][C]1.56898[/C][C]-2.7169[/C][/ROW]
[ROW][C]9[/C][C]130.95[/C][C]130.074[/C][C]127.622[/C][C]2.45215[/C][C]0.875771[/C][/ROW]
[ROW][C]10[/C][C]128.65[/C][C]128.227[/C][C]126.717[/C][C]1.50973[/C][C]0.422771[/C][/ROW]
[ROW][C]11[/C][C]127.37[/C][C]127.027[/C][C]125.912[/C][C]1.11523[/C][C]0.342688[/C][/ROW]
[ROW][C]12[/C][C]127.04[/C][C]125.567[/C][C]125.17[/C][C]0.396896[/C][C]1.47269[/C][/ROW]
[ROW][C]13[/C][C]125.95[/C][C]123.886[/C][C]124.446[/C][C]-0.560687[/C][C]2.06444[/C][/ROW]
[ROW][C]14[/C][C]124.06[/C][C]122.243[/C][C]123.757[/C][C]-1.51394[/C][C]1.81685[/C][/ROW]
[ROW][C]15[/C][C]121.55[/C][C]120.53[/C][C]122.962[/C][C]-2.43294[/C][C]1.02044[/C][/ROW]
[ROW][C]16[/C][C]119.82[/C][C]119.149[/C][C]122.031[/C][C]-2.88202[/C][C]0.670771[/C][/ROW]
[ROW][C]17[/C][C]119.19[/C][C]119.644[/C][C]121.08[/C][C]-1.43627[/C][C]-0.454146[/C][/ROW]
[ROW][C]18[/C][C]118.77[/C][C]120.798[/C][C]120.093[/C][C]0.704729[/C][C]-2.02765[/C][/ROW]
[ROW][C]19[/C][C]118.31[/C][C]120.121[/C][C]119.043[/C][C]1.07815[/C][C]-1.81148[/C][/ROW]
[ROW][C]20[/C][C]119.47[/C][C]119.54[/C][C]117.971[/C][C]1.56898[/C][C]-0.0698125[/C][/ROW]
[ROW][C]21[/C][C]119.79[/C][C]119.441[/C][C]116.989[/C][C]2.45215[/C][C]0.349104[/C][/ROW]
[ROW][C]22[/C][C]117.46[/C][C]117.619[/C][C]116.11[/C][C]1.50973[/C][C]-0.159312[/C][/ROW]
[ROW][C]23[/C][C]115.74[/C][C]116.334[/C][C]115.219[/C][C]1.11523[/C][C]-0.593979[/C][/ROW]
[ROW][C]24[/C][C]114.97[/C][C]114.681[/C][C]114.284[/C][C]0.396896[/C][C]0.289354[/C][/ROW]
[ROW][C]25[/C][C]112.83[/C][C]113.165[/C][C]113.725[/C][C]-0.560687[/C][C]-0.334729[/C][/ROW]
[ROW][C]26[/C][C]111.44[/C][C]111.908[/C][C]113.422[/C][C]-1.51394[/C][C]-0.468146[/C][/ROW]
[ROW][C]27[/C][C]110.6[/C][C]110.534[/C][C]112.967[/C][C]-2.43294[/C][C]0.0658542[/C][/ROW]
[ROW][C]28[/C][C]109.67[/C][C]109.696[/C][C]112.578[/C][C]-2.88202[/C][C]-0.0258958[/C][/ROW]
[ROW][C]29[/C][C]107.96[/C][C]110.964[/C][C]112.4[/C][C]-1.43627[/C][C]-3.00415[/C][/ROW]
[ROW][C]30[/C][C]107.56[/C][C]113.018[/C][C]112.314[/C][C]0.704729[/C][C]-5.45848[/C][/ROW]
[ROW][C]31[/C][C]116.12[/C][C]113.324[/C][C]112.246[/C][C]1.07815[/C][C]2.79602[/C][/ROW]
[ROW][C]32[/C][C]114.38[/C][C]113.767[/C][C]112.198[/C][C]1.56898[/C][C]0.613104[/C][/ROW]
[ROW][C]33[/C][C]113.96[/C][C]114.594[/C][C]112.142[/C][C]2.45215[/C][C]-0.633813[/C][/ROW]
[ROW][C]34[/C][C]113.95[/C][C]113.618[/C][C]112.109[/C][C]1.50973[/C][C]0.331521[/C][/ROW]
[ROW][C]35[/C][C]114.99[/C][C]113.315[/C][C]112.2[/C][C]1.11523[/C][C]1.67519[/C][/ROW]
[ROW][C]36[/C][C]113.64[/C][C]112.996[/C][C]112.599[/C][C]0.396896[/C][C]0.644354[/C][/ROW]
[ROW][C]37[/C][C]112.53[/C][C]112.266[/C][C]112.827[/C][C]-0.560687[/C][C]0.264021[/C][/ROW]
[ROW][C]38[/C][C]110.59[/C][C]111.26[/C][C]112.774[/C][C]-1.51394[/C][C]-0.670229[/C][/ROW]
[ROW][C]39[/C][C]110.1[/C][C]110.328[/C][C]112.761[/C][C]-2.43294[/C][C]-0.228312[/C][/ROW]
[ROW][C]40[/C][C]109.38[/C][C]109.751[/C][C]112.633[/C][C]-2.88202[/C][C]-0.370896[/C][/ROW]
[ROW][C]41[/C][C]110.43[/C][C]110.885[/C][C]112.321[/C][C]-1.43627[/C][C]-0.454562[/C][/ROW]
[ROW][C]42[/C][C]114.67[/C][C]112.58[/C][C]111.875[/C][C]0.704729[/C][C]2.09027[/C][/ROW]
[ROW][C]43[/C][C]114.48[/C][C]112.511[/C][C]111.433[/C][C]1.07815[/C][C]1.96852[/C][/ROW]
[ROW][C]44[/C][C]114.76[/C][C]112.607[/C][C]111.038[/C][C]1.56898[/C][C]2.15269[/C][/ROW]
[ROW][C]45[/C][C]113.27[/C][C]113.054[/C][C]110.602[/C][C]2.45215[/C][C]0.215771[/C][/ROW]
[ROW][C]46[/C][C]111.56[/C][C]111.596[/C][C]110.087[/C][C]1.50973[/C][C]-0.0363958[/C][/ROW]
[ROW][C]47[/C][C]109.89[/C][C]110.699[/C][C]109.584[/C][C]1.11523[/C][C]-0.808979[/C][/ROW]
[ROW][C]48[/C][C]108.04[/C][C]109.305[/C][C]108.908[/C][C]0.396896[/C][C]-1.26481[/C][/ROW]
[ROW][C]49[/C][C]107.53[/C][C]107.388[/C][C]107.948[/C][C]-0.560687[/C][C]0.142354[/C][/ROW]
[ROW][C]50[/C][C]106.11[/C][C]105.336[/C][C]106.85[/C][C]-1.51394[/C][C]0.773521[/C][/ROW]
[ROW][C]51[/C][C]104.11[/C][C]103.288[/C][C]105.721[/C][C]-2.43294[/C][C]0.821688[/C][/ROW]
[ROW][C]52[/C][C]103[/C][C]101.743[/C][C]104.625[/C][C]-2.88202[/C][C]1.25744[/C][/ROW]
[ROW][C]53[/C][C]104.74[/C][C]102.122[/C][C]103.559[/C][C]-1.43627[/C][C]2.61752[/C][/ROW]
[ROW][C]54[/C][C]104.14[/C][C]103.235[/C][C]102.53[/C][C]0.704729[/C][C]0.905271[/C][/ROW]
[ROW][C]55[/C][C]101.98[/C][C]102.536[/C][C]101.458[/C][C]1.07815[/C][C]-0.556479[/C][/ROW]
[ROW][C]56[/C][C]100.91[/C][C]101.962[/C][C]100.393[/C][C]1.56898[/C][C]-1.05231[/C][/ROW]
[ROW][C]57[/C][C]100.02[/C][C]101.9[/C][C]99.4479[/C][C]2.45215[/C][C]-1.88006[/C][/ROW]
[ROW][C]58[/C][C]98.49[/C][C]100.122[/C][C]98.6121[/C][C]1.50973[/C][C]-1.63181[/C][/ROW]
[ROW][C]59[/C][C]97.38[/C][C]99.0681[/C][C]97.9529[/C][C]1.11523[/C][C]-1.68815[/C][/ROW]
[ROW][C]60[/C][C]95.86[/C][C]98.0748[/C][C]97.6779[/C][C]0.396896[/C][C]-2.21481[/C][/ROW]
[ROW][C]61[/C][C]93.99[/C][C]97.1993[/C][C]97.76[/C][C]-0.560687[/C][C]-3.20931[/C][/ROW]
[ROW][C]62[/C][C]94.09[/C][C]96.6152[/C][C]98.1292[/C][C]-1.51394[/C][C]-2.52523[/C][/ROW]
[ROW][C]63[/C][C]93.44[/C][C]96.1929[/C][C]98.6258[/C][C]-2.43294[/C][C]-2.7529[/C][/ROW]
[ROW][C]64[/C][C]93.61[/C][C]96.2146[/C][C]99.0967[/C][C]-2.88202[/C][C]-2.60465[/C][/ROW]
[ROW][C]65[/C][C]98.31[/C][C]98.0879[/C][C]99.5242[/C][C]-1.43627[/C][C]0.222104[/C][/ROW]
[ROW][C]66[/C][C]103.97[/C][C]100.553[/C][C]99.8479[/C][C]0.704729[/C][C]3.41735[/C][/ROW]
[ROW][C]67[/C][C]104.12[/C][C]NA[/C][C]NA[/C][C]1.07815[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]107.63[/C][C]NA[/C][C]NA[/C][C]1.56898[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]105.22[/C][C]NA[/C][C]NA[/C][C]2.45215[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]104.59[/C][C]NA[/C][C]NA[/C][C]1.50973[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]101.54[/C][C]NA[/C][C]NA[/C][C]1.11523[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]99.47[/C][C]NA[/C][C]NA[/C][C]0.396896[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	134.93	NA	NA	-0.560687	NA
2	134.37	NA	NA	-1.51394	NA
3	132.98	NA	NA	-2.43294	NA
4	130.1	NA	NA	-2.88202	NA
5	128.24	NA	NA	-1.43627	NA
6	127.52	NA	NA	0.704729	NA
7	126.94	130.41	129.332	1.07815	-3.46981
8	127.38	130.097	128.528	1.56898	-2.7169
9	130.95	130.074	127.622	2.45215	0.875771
10	128.65	128.227	126.717	1.50973	0.422771
11	127.37	127.027	125.912	1.11523	0.342688
12	127.04	125.567	125.17	0.396896	1.47269
13	125.95	123.886	124.446	-0.560687	2.06444
14	124.06	122.243	123.757	-1.51394	1.81685
15	121.55	120.53	122.962	-2.43294	1.02044
16	119.82	119.149	122.031	-2.88202	0.670771
17	119.19	119.644	121.08	-1.43627	-0.454146
18	118.77	120.798	120.093	0.704729	-2.02765
19	118.31	120.121	119.043	1.07815	-1.81148
20	119.47	119.54	117.971	1.56898	-0.0698125
21	119.79	119.441	116.989	2.45215	0.349104
22	117.46	117.619	116.11	1.50973	-0.159312
23	115.74	116.334	115.219	1.11523	-0.593979
24	114.97	114.681	114.284	0.396896	0.289354
25	112.83	113.165	113.725	-0.560687	-0.334729
26	111.44	111.908	113.422	-1.51394	-0.468146
27	110.6	110.534	112.967	-2.43294	0.0658542
28	109.67	109.696	112.578	-2.88202	-0.0258958
29	107.96	110.964	112.4	-1.43627	-3.00415
30	107.56	113.018	112.314	0.704729	-5.45848
31	116.12	113.324	112.246	1.07815	2.79602
32	114.38	113.767	112.198	1.56898	0.613104
33	113.96	114.594	112.142	2.45215	-0.633813
34	113.95	113.618	112.109	1.50973	0.331521
35	114.99	113.315	112.2	1.11523	1.67519
36	113.64	112.996	112.599	0.396896	0.644354
37	112.53	112.266	112.827	-0.560687	0.264021
38	110.59	111.26	112.774	-1.51394	-0.670229
39	110.1	110.328	112.761	-2.43294	-0.228312
40	109.38	109.751	112.633	-2.88202	-0.370896
41	110.43	110.885	112.321	-1.43627	-0.454562
42	114.67	112.58	111.875	0.704729	2.09027
43	114.48	112.511	111.433	1.07815	1.96852
44	114.76	112.607	111.038	1.56898	2.15269
45	113.27	113.054	110.602	2.45215	0.215771
46	111.56	111.596	110.087	1.50973	-0.0363958
47	109.89	110.699	109.584	1.11523	-0.808979
48	108.04	109.305	108.908	0.396896	-1.26481
49	107.53	107.388	107.948	-0.560687	0.142354
50	106.11	105.336	106.85	-1.51394	0.773521
51	104.11	103.288	105.721	-2.43294	0.821688
52	103	101.743	104.625	-2.88202	1.25744
53	104.74	102.122	103.559	-1.43627	2.61752
54	104.14	103.235	102.53	0.704729	0.905271
55	101.98	102.536	101.458	1.07815	-0.556479
56	100.91	101.962	100.393	1.56898	-1.05231
57	100.02	101.9	99.4479	2.45215	-1.88006
58	98.49	100.122	98.6121	1.50973	-1.63181
59	97.38	99.0681	97.9529	1.11523	-1.68815
60	95.86	98.0748	97.6779	0.396896	-2.21481
61	93.99	97.1993	97.76	-0.560687	-3.20931
62	94.09	96.6152	98.1292	-1.51394	-2.52523
63	93.44	96.1929	98.6258	-2.43294	-2.7529
64	93.61	96.2146	99.0967	-2.88202	-2.60465
65	98.31	98.0879	99.5242	-1.43627	0.222104
66	103.97	100.553	99.8479	0.704729	3.41735
67	104.12	NA	NA	1.07815	NA
68	107.63	NA	NA	1.56898	NA
69	105.22	NA	NA	2.45215	NA
70	104.59	NA	NA	1.50973	NA
71	101.54	NA	NA	1.11523	NA
72	99.47	NA	NA	0.396896	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