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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 09 Dec 2013 10:01:43 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/09/t1386601335ebmr8i52zheat1m.htm/, Retrieved Tue, 23 Apr 2024 09:11:54 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231671, Retrieved Tue, 23 Apr 2024 09:11:54 +0000

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-       [Classical Decomposition] [] [2013-12-09 15:01:43] [629d05b8910d8b56ad89862016f2bc6c] [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	5 seconds
R Server	'Sir Maurice George Kendall' @ kendall.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 & 5 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231671&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231671&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	5 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	120.6	NA	NA	13.7752	NA
2	119.9	NA	NA	11.1026	NA
3	119.48	NA	NA	8.66937	NA
4	117.45	NA	NA	6.31326	NA
5	118.37	NA	NA	3.68361	NA
6	117.07	NA	NA	1.0584	NA
7	114.98	112.677	114.92	-2.24383	2.30341
8	112.59	109.213	114.022	-4.80966	3.37716
9	111.7	107.267	113.18	-5.91244	4.43285
10	112.04	104.567	112.374	-7.80723	7.47306
11	110.79	100.861	111.536	-10.6749	9.92862
12	109.82	97.4939	110.648	-13.1545	12.3261
13	109.11	123.581	109.805	13.7752	-14.4706
14	109.84	120.157	109.054	11.1026	-10.3168
15	109.31	117.127	108.458	8.66937	-7.81729
16	108.29	114.268	107.955	6.31326	-5.97826
17	107.42	111.183	107.5	3.68361	-3.76319
18	106.71	108.162	107.104	1.0584	-1.45215
19	105.11	104.486	106.73	-2.24383	0.623825
20	104.43	101.516	106.326	-4.80966	2.91383
21	105.55	100.04	105.952	-5.91244	5.50994
22	106.12	97.9565	105.764	-7.80723	8.16348
23	105.78	95.0601	105.735	-10.6749	10.7199
24	105.33	92.6285	105.783	-13.1545	12.7015
25	104.63	119.67	105.895	13.7752	-15.0398
26	104.62	117.139	106.037	11.1026	-12.5193
27	105.57	114.789	106.12	8.66937	-9.21937
28	107.5	112.407	106.094	6.31326	-4.90701
29	107.52	109.682	105.999	3.68361	-2.16236
30	107.76	106.922	105.864	1.0584	0.837853
31	106.74	103.447	105.69	-2.24383	3.29341
32	106.21	100.629	105.439	-4.80966	5.58091
33	105.77	99.1838	105.096	-5.91244	6.58619
34	105.27	96.7857	104.593	-7.80723	8.48431
35	104.35	93.2714	103.946	-10.6749	11.0786
36	103.52	90.118	103.272	-13.1545	13.402
37	102.28	116.384	102.609	13.7752	-14.104
38	100.93	113.074	101.971	11.1026	-12.1439
39	101.04	110.042	101.373	8.66937	-9.00229
40	99.95	107.217	100.904	6.31326	-7.26701
41	99.55	104.233	100.55	3.68361	-4.68319
42	99.56	101.323	100.265	1.0584	-1.7634
43	99.01	105.343	107.587	-2.24383	-6.33284
44	98.64	117.693	122.503	-4.80966	-19.0533
45	98.98	131.542	137.454	-5.91244	-32.5617
46	100.8	144.635	152.442	-7.80723	-43.8349
47	100.32	156.842	167.517	-10.6749	-56.5222
48	100.72	169.479	182.633	-13.1545	-68.7589
49	280.8	211.493	197.718	13.7752	69.3069
50	280.4	224.035	212.933	11.1026	56.3649
51	280.4	237.272	228.603	8.66937	43.1281
52	280.3	250.85	244.537	6.31326	29.4501
53	281	264.144	260.461	3.68361	16.8556
54	280.9	277.455	276.397	1.0584	3.44494
55	279.7	282.569	284.812	-2.24383	-2.86867
56	283.1	280.92	285.729	-4.80966	2.18049
57	290.6	280.75	286.662	-5.91244	9.84994
58	291.6	279.872	287.679	-7.80723	11.7281
59	291.7	278.054	288.729	-10.6749	13.6457
60	291.8	276.587	289.742	-13.1545	15.2128
61	291.7	304.563	290.787	13.7752	-12.8627
62	291.5	302.803	291.7	11.1026	-11.3026
63	291.7	300.811	292.142	8.66937	-9.11104
64	293.4	298.538	292.225	6.31326	-5.13826
65	293.1	295.942	292.258	3.68361	-2.84194
66	293.1	293.4	292.342	1.0584	-0.300064
67	292.6	290.185	292.429	-2.24383	2.41466
68	292.1	287.665	292.475	-4.80966	4.43466
69	292.2	286.583	292.496	-5.91244	5.6166
70	292	284.58	292.388	-7.80723	7.41973
71	292.1	281.517	292.192	-10.6749	10.5832
72	293.4	278.85	292.004	-13.1545	14.5503
73	292.2	305.596	291.821	13.7752	-13.396
74	292.1	302.748	291.646	11.1026	-10.6485
75	291.6	300.144	291.475	8.66937	-8.54437
76	290.9	297.626	291.312	6.31326	-6.72576
77	290.9	294.871	291.188	3.68361	-3.97111
78	290.8	292.133	291.075	1.0584	-1.3334
79	290.5	NA	NA	-2.24383	NA
80	290	NA	NA	-4.80966	NA
81	290.2	NA	NA	-5.91244	NA
82	290.1	NA	NA	-7.80723	NA
83	291	NA	NA	-10.6749	NA
84	291.8	NA	NA	-13.1545	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 120.6 & NA & NA & 13.7752 & NA \tabularnewline
2 & 119.9 & NA & NA & 11.1026 & NA \tabularnewline
3 & 119.48 & NA & NA & 8.66937 & NA \tabularnewline
4 & 117.45 & NA & NA & 6.31326 & NA \tabularnewline
5 & 118.37 & NA & NA & 3.68361 & NA \tabularnewline
6 & 117.07 & NA & NA & 1.0584 & NA \tabularnewline
7 & 114.98 & 112.677 & 114.92 & -2.24383 & 2.30341 \tabularnewline
8 & 112.59 & 109.213 & 114.022 & -4.80966 & 3.37716 \tabularnewline
9 & 111.7 & 107.267 & 113.18 & -5.91244 & 4.43285 \tabularnewline
10 & 112.04 & 104.567 & 112.374 & -7.80723 & 7.47306 \tabularnewline
11 & 110.79 & 100.861 & 111.536 & -10.6749 & 9.92862 \tabularnewline
12 & 109.82 & 97.4939 & 110.648 & -13.1545 & 12.3261 \tabularnewline
13 & 109.11 & 123.581 & 109.805 & 13.7752 & -14.4706 \tabularnewline
14 & 109.84 & 120.157 & 109.054 & 11.1026 & -10.3168 \tabularnewline
15 & 109.31 & 117.127 & 108.458 & 8.66937 & -7.81729 \tabularnewline
16 & 108.29 & 114.268 & 107.955 & 6.31326 & -5.97826 \tabularnewline
17 & 107.42 & 111.183 & 107.5 & 3.68361 & -3.76319 \tabularnewline
18 & 106.71 & 108.162 & 107.104 & 1.0584 & -1.45215 \tabularnewline
19 & 105.11 & 104.486 & 106.73 & -2.24383 & 0.623825 \tabularnewline
20 & 104.43 & 101.516 & 106.326 & -4.80966 & 2.91383 \tabularnewline
21 & 105.55 & 100.04 & 105.952 & -5.91244 & 5.50994 \tabularnewline
22 & 106.12 & 97.9565 & 105.764 & -7.80723 & 8.16348 \tabularnewline
23 & 105.78 & 95.0601 & 105.735 & -10.6749 & 10.7199 \tabularnewline
24 & 105.33 & 92.6285 & 105.783 & -13.1545 & 12.7015 \tabularnewline
25 & 104.63 & 119.67 & 105.895 & 13.7752 & -15.0398 \tabularnewline
26 & 104.62 & 117.139 & 106.037 & 11.1026 & -12.5193 \tabularnewline
27 & 105.57 & 114.789 & 106.12 & 8.66937 & -9.21937 \tabularnewline
28 & 107.5 & 112.407 & 106.094 & 6.31326 & -4.90701 \tabularnewline
29 & 107.52 & 109.682 & 105.999 & 3.68361 & -2.16236 \tabularnewline
30 & 107.76 & 106.922 & 105.864 & 1.0584 & 0.837853 \tabularnewline
31 & 106.74 & 103.447 & 105.69 & -2.24383 & 3.29341 \tabularnewline
32 & 106.21 & 100.629 & 105.439 & -4.80966 & 5.58091 \tabularnewline
33 & 105.77 & 99.1838 & 105.096 & -5.91244 & 6.58619 \tabularnewline
34 & 105.27 & 96.7857 & 104.593 & -7.80723 & 8.48431 \tabularnewline
35 & 104.35 & 93.2714 & 103.946 & -10.6749 & 11.0786 \tabularnewline
36 & 103.52 & 90.118 & 103.272 & -13.1545 & 13.402 \tabularnewline
37 & 102.28 & 116.384 & 102.609 & 13.7752 & -14.104 \tabularnewline
38 & 100.93 & 113.074 & 101.971 & 11.1026 & -12.1439 \tabularnewline
39 & 101.04 & 110.042 & 101.373 & 8.66937 & -9.00229 \tabularnewline
40 & 99.95 & 107.217 & 100.904 & 6.31326 & -7.26701 \tabularnewline
41 & 99.55 & 104.233 & 100.55 & 3.68361 & -4.68319 \tabularnewline
42 & 99.56 & 101.323 & 100.265 & 1.0584 & -1.7634 \tabularnewline
43 & 99.01 & 105.343 & 107.587 & -2.24383 & -6.33284 \tabularnewline
44 & 98.64 & 117.693 & 122.503 & -4.80966 & -19.0533 \tabularnewline
45 & 98.98 & 131.542 & 137.454 & -5.91244 & -32.5617 \tabularnewline
46 & 100.8 & 144.635 & 152.442 & -7.80723 & -43.8349 \tabularnewline
47 & 100.32 & 156.842 & 167.517 & -10.6749 & -56.5222 \tabularnewline
48 & 100.72 & 169.479 & 182.633 & -13.1545 & -68.7589 \tabularnewline
49 & 280.8 & 211.493 & 197.718 & 13.7752 & 69.3069 \tabularnewline
50 & 280.4 & 224.035 & 212.933 & 11.1026 & 56.3649 \tabularnewline
51 & 280.4 & 237.272 & 228.603 & 8.66937 & 43.1281 \tabularnewline
52 & 280.3 & 250.85 & 244.537 & 6.31326 & 29.4501 \tabularnewline
53 & 281 & 264.144 & 260.461 & 3.68361 & 16.8556 \tabularnewline
54 & 280.9 & 277.455 & 276.397 & 1.0584 & 3.44494 \tabularnewline
55 & 279.7 & 282.569 & 284.812 & -2.24383 & -2.86867 \tabularnewline
56 & 283.1 & 280.92 & 285.729 & -4.80966 & 2.18049 \tabularnewline
57 & 290.6 & 280.75 & 286.662 & -5.91244 & 9.84994 \tabularnewline
58 & 291.6 & 279.872 & 287.679 & -7.80723 & 11.7281 \tabularnewline
59 & 291.7 & 278.054 & 288.729 & -10.6749 & 13.6457 \tabularnewline
60 & 291.8 & 276.587 & 289.742 & -13.1545 & 15.2128 \tabularnewline
61 & 291.7 & 304.563 & 290.787 & 13.7752 & -12.8627 \tabularnewline
62 & 291.5 & 302.803 & 291.7 & 11.1026 & -11.3026 \tabularnewline
63 & 291.7 & 300.811 & 292.142 & 8.66937 & -9.11104 \tabularnewline
64 & 293.4 & 298.538 & 292.225 & 6.31326 & -5.13826 \tabularnewline
65 & 293.1 & 295.942 & 292.258 & 3.68361 & -2.84194 \tabularnewline
66 & 293.1 & 293.4 & 292.342 & 1.0584 & -0.300064 \tabularnewline
67 & 292.6 & 290.185 & 292.429 & -2.24383 & 2.41466 \tabularnewline
68 & 292.1 & 287.665 & 292.475 & -4.80966 & 4.43466 \tabularnewline
69 & 292.2 & 286.583 & 292.496 & -5.91244 & 5.6166 \tabularnewline
70 & 292 & 284.58 & 292.388 & -7.80723 & 7.41973 \tabularnewline
71 & 292.1 & 281.517 & 292.192 & -10.6749 & 10.5832 \tabularnewline
72 & 293.4 & 278.85 & 292.004 & -13.1545 & 14.5503 \tabularnewline
73 & 292.2 & 305.596 & 291.821 & 13.7752 & -13.396 \tabularnewline
74 & 292.1 & 302.748 & 291.646 & 11.1026 & -10.6485 \tabularnewline
75 & 291.6 & 300.144 & 291.475 & 8.66937 & -8.54437 \tabularnewline
76 & 290.9 & 297.626 & 291.312 & 6.31326 & -6.72576 \tabularnewline
77 & 290.9 & 294.871 & 291.188 & 3.68361 & -3.97111 \tabularnewline
78 & 290.8 & 292.133 & 291.075 & 1.0584 & -1.3334 \tabularnewline
79 & 290.5 & NA & NA & -2.24383 & NA \tabularnewline
80 & 290 & NA & NA & -4.80966 & NA \tabularnewline
81 & 290.2 & NA & NA & -5.91244 & NA \tabularnewline
82 & 290.1 & NA & NA & -7.80723 & NA \tabularnewline
83 & 291 & NA & NA & -10.6749 & NA \tabularnewline
84 & 291.8 & NA & NA & -13.1545 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231671&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]120.6[/C][C]NA[/C][C]NA[/C][C]13.7752[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]119.9[/C][C]NA[/C][C]NA[/C][C]11.1026[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]119.48[/C][C]NA[/C][C]NA[/C][C]8.66937[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]117.45[/C][C]NA[/C][C]NA[/C][C]6.31326[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]118.37[/C][C]NA[/C][C]NA[/C][C]3.68361[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]117.07[/C][C]NA[/C][C]NA[/C][C]1.0584[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]114.98[/C][C]112.677[/C][C]114.92[/C][C]-2.24383[/C][C]2.30341[/C][/ROW]
[ROW][C]8[/C][C]112.59[/C][C]109.213[/C][C]114.022[/C][C]-4.80966[/C][C]3.37716[/C][/ROW]
[ROW][C]9[/C][C]111.7[/C][C]107.267[/C][C]113.18[/C][C]-5.91244[/C][C]4.43285[/C][/ROW]
[ROW][C]10[/C][C]112.04[/C][C]104.567[/C][C]112.374[/C][C]-7.80723[/C][C]7.47306[/C][/ROW]
[ROW][C]11[/C][C]110.79[/C][C]100.861[/C][C]111.536[/C][C]-10.6749[/C][C]9.92862[/C][/ROW]
[ROW][C]12[/C][C]109.82[/C][C]97.4939[/C][C]110.648[/C][C]-13.1545[/C][C]12.3261[/C][/ROW]
[ROW][C]13[/C][C]109.11[/C][C]123.581[/C][C]109.805[/C][C]13.7752[/C][C]-14.4706[/C][/ROW]
[ROW][C]14[/C][C]109.84[/C][C]120.157[/C][C]109.054[/C][C]11.1026[/C][C]-10.3168[/C][/ROW]
[ROW][C]15[/C][C]109.31[/C][C]117.127[/C][C]108.458[/C][C]8.66937[/C][C]-7.81729[/C][/ROW]
[ROW][C]16[/C][C]108.29[/C][C]114.268[/C][C]107.955[/C][C]6.31326[/C][C]-5.97826[/C][/ROW]
[ROW][C]17[/C][C]107.42[/C][C]111.183[/C][C]107.5[/C][C]3.68361[/C][C]-3.76319[/C][/ROW]
[ROW][C]18[/C][C]106.71[/C][C]108.162[/C][C]107.104[/C][C]1.0584[/C][C]-1.45215[/C][/ROW]
[ROW][C]19[/C][C]105.11[/C][C]104.486[/C][C]106.73[/C][C]-2.24383[/C][C]0.623825[/C][/ROW]
[ROW][C]20[/C][C]104.43[/C][C]101.516[/C][C]106.326[/C][C]-4.80966[/C][C]2.91383[/C][/ROW]
[ROW][C]21[/C][C]105.55[/C][C]100.04[/C][C]105.952[/C][C]-5.91244[/C][C]5.50994[/C][/ROW]
[ROW][C]22[/C][C]106.12[/C][C]97.9565[/C][C]105.764[/C][C]-7.80723[/C][C]8.16348[/C][/ROW]
[ROW][C]23[/C][C]105.78[/C][C]95.0601[/C][C]105.735[/C][C]-10.6749[/C][C]10.7199[/C][/ROW]
[ROW][C]24[/C][C]105.33[/C][C]92.6285[/C][C]105.783[/C][C]-13.1545[/C][C]12.7015[/C][/ROW]
[ROW][C]25[/C][C]104.63[/C][C]119.67[/C][C]105.895[/C][C]13.7752[/C][C]-15.0398[/C][/ROW]
[ROW][C]26[/C][C]104.62[/C][C]117.139[/C][C]106.037[/C][C]11.1026[/C][C]-12.5193[/C][/ROW]
[ROW][C]27[/C][C]105.57[/C][C]114.789[/C][C]106.12[/C][C]8.66937[/C][C]-9.21937[/C][/ROW]
[ROW][C]28[/C][C]107.5[/C][C]112.407[/C][C]106.094[/C][C]6.31326[/C][C]-4.90701[/C][/ROW]
[ROW][C]29[/C][C]107.52[/C][C]109.682[/C][C]105.999[/C][C]3.68361[/C][C]-2.16236[/C][/ROW]
[ROW][C]30[/C][C]107.76[/C][C]106.922[/C][C]105.864[/C][C]1.0584[/C][C]0.837853[/C][/ROW]
[ROW][C]31[/C][C]106.74[/C][C]103.447[/C][C]105.69[/C][C]-2.24383[/C][C]3.29341[/C][/ROW]
[ROW][C]32[/C][C]106.21[/C][C]100.629[/C][C]105.439[/C][C]-4.80966[/C][C]5.58091[/C][/ROW]
[ROW][C]33[/C][C]105.77[/C][C]99.1838[/C][C]105.096[/C][C]-5.91244[/C][C]6.58619[/C][/ROW]
[ROW][C]34[/C][C]105.27[/C][C]96.7857[/C][C]104.593[/C][C]-7.80723[/C][C]8.48431[/C][/ROW]
[ROW][C]35[/C][C]104.35[/C][C]93.2714[/C][C]103.946[/C][C]-10.6749[/C][C]11.0786[/C][/ROW]
[ROW][C]36[/C][C]103.52[/C][C]90.118[/C][C]103.272[/C][C]-13.1545[/C][C]13.402[/C][/ROW]
[ROW][C]37[/C][C]102.28[/C][C]116.384[/C][C]102.609[/C][C]13.7752[/C][C]-14.104[/C][/ROW]
[ROW][C]38[/C][C]100.93[/C][C]113.074[/C][C]101.971[/C][C]11.1026[/C][C]-12.1439[/C][/ROW]
[ROW][C]39[/C][C]101.04[/C][C]110.042[/C][C]101.373[/C][C]8.66937[/C][C]-9.00229[/C][/ROW]
[ROW][C]40[/C][C]99.95[/C][C]107.217[/C][C]100.904[/C][C]6.31326[/C][C]-7.26701[/C][/ROW]
[ROW][C]41[/C][C]99.55[/C][C]104.233[/C][C]100.55[/C][C]3.68361[/C][C]-4.68319[/C][/ROW]
[ROW][C]42[/C][C]99.56[/C][C]101.323[/C][C]100.265[/C][C]1.0584[/C][C]-1.7634[/C][/ROW]
[ROW][C]43[/C][C]99.01[/C][C]105.343[/C][C]107.587[/C][C]-2.24383[/C][C]-6.33284[/C][/ROW]
[ROW][C]44[/C][C]98.64[/C][C]117.693[/C][C]122.503[/C][C]-4.80966[/C][C]-19.0533[/C][/ROW]
[ROW][C]45[/C][C]98.98[/C][C]131.542[/C][C]137.454[/C][C]-5.91244[/C][C]-32.5617[/C][/ROW]
[ROW][C]46[/C][C]100.8[/C][C]144.635[/C][C]152.442[/C][C]-7.80723[/C][C]-43.8349[/C][/ROW]
[ROW][C]47[/C][C]100.32[/C][C]156.842[/C][C]167.517[/C][C]-10.6749[/C][C]-56.5222[/C][/ROW]
[ROW][C]48[/C][C]100.72[/C][C]169.479[/C][C]182.633[/C][C]-13.1545[/C][C]-68.7589[/C][/ROW]
[ROW][C]49[/C][C]280.8[/C][C]211.493[/C][C]197.718[/C][C]13.7752[/C][C]69.3069[/C][/ROW]
[ROW][C]50[/C][C]280.4[/C][C]224.035[/C][C]212.933[/C][C]11.1026[/C][C]56.3649[/C][/ROW]
[ROW][C]51[/C][C]280.4[/C][C]237.272[/C][C]228.603[/C][C]8.66937[/C][C]43.1281[/C][/ROW]
[ROW][C]52[/C][C]280.3[/C][C]250.85[/C][C]244.537[/C][C]6.31326[/C][C]29.4501[/C][/ROW]
[ROW][C]53[/C][C]281[/C][C]264.144[/C][C]260.461[/C][C]3.68361[/C][C]16.8556[/C][/ROW]
[ROW][C]54[/C][C]280.9[/C][C]277.455[/C][C]276.397[/C][C]1.0584[/C][C]3.44494[/C][/ROW]
[ROW][C]55[/C][C]279.7[/C][C]282.569[/C][C]284.812[/C][C]-2.24383[/C][C]-2.86867[/C][/ROW]
[ROW][C]56[/C][C]283.1[/C][C]280.92[/C][C]285.729[/C][C]-4.80966[/C][C]2.18049[/C][/ROW]
[ROW][C]57[/C][C]290.6[/C][C]280.75[/C][C]286.662[/C][C]-5.91244[/C][C]9.84994[/C][/ROW]
[ROW][C]58[/C][C]291.6[/C][C]279.872[/C][C]287.679[/C][C]-7.80723[/C][C]11.7281[/C][/ROW]
[ROW][C]59[/C][C]291.7[/C][C]278.054[/C][C]288.729[/C][C]-10.6749[/C][C]13.6457[/C][/ROW]
[ROW][C]60[/C][C]291.8[/C][C]276.587[/C][C]289.742[/C][C]-13.1545[/C][C]15.2128[/C][/ROW]
[ROW][C]61[/C][C]291.7[/C][C]304.563[/C][C]290.787[/C][C]13.7752[/C][C]-12.8627[/C][/ROW]
[ROW][C]62[/C][C]291.5[/C][C]302.803[/C][C]291.7[/C][C]11.1026[/C][C]-11.3026[/C][/ROW]
[ROW][C]63[/C][C]291.7[/C][C]300.811[/C][C]292.142[/C][C]8.66937[/C][C]-9.11104[/C][/ROW]
[ROW][C]64[/C][C]293.4[/C][C]298.538[/C][C]292.225[/C][C]6.31326[/C][C]-5.13826[/C][/ROW]
[ROW][C]65[/C][C]293.1[/C][C]295.942[/C][C]292.258[/C][C]3.68361[/C][C]-2.84194[/C][/ROW]
[ROW][C]66[/C][C]293.1[/C][C]293.4[/C][C]292.342[/C][C]1.0584[/C][C]-0.300064[/C][/ROW]
[ROW][C]67[/C][C]292.6[/C][C]290.185[/C][C]292.429[/C][C]-2.24383[/C][C]2.41466[/C][/ROW]
[ROW][C]68[/C][C]292.1[/C][C]287.665[/C][C]292.475[/C][C]-4.80966[/C][C]4.43466[/C][/ROW]
[ROW][C]69[/C][C]292.2[/C][C]286.583[/C][C]292.496[/C][C]-5.91244[/C][C]5.6166[/C][/ROW]
[ROW][C]70[/C][C]292[/C][C]284.58[/C][C]292.388[/C][C]-7.80723[/C][C]7.41973[/C][/ROW]
[ROW][C]71[/C][C]292.1[/C][C]281.517[/C][C]292.192[/C][C]-10.6749[/C][C]10.5832[/C][/ROW]
[ROW][C]72[/C][C]293.4[/C][C]278.85[/C][C]292.004[/C][C]-13.1545[/C][C]14.5503[/C][/ROW]
[ROW][C]73[/C][C]292.2[/C][C]305.596[/C][C]291.821[/C][C]13.7752[/C][C]-13.396[/C][/ROW]
[ROW][C]74[/C][C]292.1[/C][C]302.748[/C][C]291.646[/C][C]11.1026[/C][C]-10.6485[/C][/ROW]
[ROW][C]75[/C][C]291.6[/C][C]300.144[/C][C]291.475[/C][C]8.66937[/C][C]-8.54437[/C][/ROW]
[ROW][C]76[/C][C]290.9[/C][C]297.626[/C][C]291.312[/C][C]6.31326[/C][C]-6.72576[/C][/ROW]
[ROW][C]77[/C][C]290.9[/C][C]294.871[/C][C]291.188[/C][C]3.68361[/C][C]-3.97111[/C][/ROW]
[ROW][C]78[/C][C]290.8[/C][C]292.133[/C][C]291.075[/C][C]1.0584[/C][C]-1.3334[/C][/ROW]
[ROW][C]79[/C][C]290.5[/C][C]NA[/C][C]NA[/C][C]-2.24383[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]290[/C][C]NA[/C][C]NA[/C][C]-4.80966[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]290.2[/C][C]NA[/C][C]NA[/C][C]-5.91244[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]290.1[/C][C]NA[/C][C]NA[/C][C]-7.80723[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]291[/C][C]NA[/C][C]NA[/C][C]-10.6749[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]291.8[/C][C]NA[/C][C]NA[/C][C]-13.1545[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231671&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	120.6	NA	NA	13.7752	NA
2	119.9	NA	NA	11.1026	NA
3	119.48	NA	NA	8.66937	NA
4	117.45	NA	NA	6.31326	NA
5	118.37	NA	NA	3.68361	NA
6	117.07	NA	NA	1.0584	NA
7	114.98	112.677	114.92	-2.24383	2.30341
8	112.59	109.213	114.022	-4.80966	3.37716
9	111.7	107.267	113.18	-5.91244	4.43285
10	112.04	104.567	112.374	-7.80723	7.47306
11	110.79	100.861	111.536	-10.6749	9.92862
12	109.82	97.4939	110.648	-13.1545	12.3261
13	109.11	123.581	109.805	13.7752	-14.4706
14	109.84	120.157	109.054	11.1026	-10.3168
15	109.31	117.127	108.458	8.66937	-7.81729
16	108.29	114.268	107.955	6.31326	-5.97826
17	107.42	111.183	107.5	3.68361	-3.76319
18	106.71	108.162	107.104	1.0584	-1.45215
19	105.11	104.486	106.73	-2.24383	0.623825
20	104.43	101.516	106.326	-4.80966	2.91383
21	105.55	100.04	105.952	-5.91244	5.50994
22	106.12	97.9565	105.764	-7.80723	8.16348
23	105.78	95.0601	105.735	-10.6749	10.7199
24	105.33	92.6285	105.783	-13.1545	12.7015
25	104.63	119.67	105.895	13.7752	-15.0398
26	104.62	117.139	106.037	11.1026	-12.5193
27	105.57	114.789	106.12	8.66937	-9.21937
28	107.5	112.407	106.094	6.31326	-4.90701
29	107.52	109.682	105.999	3.68361	-2.16236
30	107.76	106.922	105.864	1.0584	0.837853
31	106.74	103.447	105.69	-2.24383	3.29341
32	106.21	100.629	105.439	-4.80966	5.58091
33	105.77	99.1838	105.096	-5.91244	6.58619
34	105.27	96.7857	104.593	-7.80723	8.48431
35	104.35	93.2714	103.946	-10.6749	11.0786
36	103.52	90.118	103.272	-13.1545	13.402
37	102.28	116.384	102.609	13.7752	-14.104
38	100.93	113.074	101.971	11.1026	-12.1439
39	101.04	110.042	101.373	8.66937	-9.00229
40	99.95	107.217	100.904	6.31326	-7.26701
41	99.55	104.233	100.55	3.68361	-4.68319
42	99.56	101.323	100.265	1.0584	-1.7634
43	99.01	105.343	107.587	-2.24383	-6.33284
44	98.64	117.693	122.503	-4.80966	-19.0533
45	98.98	131.542	137.454	-5.91244	-32.5617
46	100.8	144.635	152.442	-7.80723	-43.8349
47	100.32	156.842	167.517	-10.6749	-56.5222
48	100.72	169.479	182.633	-13.1545	-68.7589
49	280.8	211.493	197.718	13.7752	69.3069
50	280.4	224.035	212.933	11.1026	56.3649
51	280.4	237.272	228.603	8.66937	43.1281
52	280.3	250.85	244.537	6.31326	29.4501
53	281	264.144	260.461	3.68361	16.8556
54	280.9	277.455	276.397	1.0584	3.44494
55	279.7	282.569	284.812	-2.24383	-2.86867
56	283.1	280.92	285.729	-4.80966	2.18049
57	290.6	280.75	286.662	-5.91244	9.84994
58	291.6	279.872	287.679	-7.80723	11.7281
59	291.7	278.054	288.729	-10.6749	13.6457
60	291.8	276.587	289.742	-13.1545	15.2128
61	291.7	304.563	290.787	13.7752	-12.8627
62	291.5	302.803	291.7	11.1026	-11.3026
63	291.7	300.811	292.142	8.66937	-9.11104
64	293.4	298.538	292.225	6.31326	-5.13826
65	293.1	295.942	292.258	3.68361	-2.84194
66	293.1	293.4	292.342	1.0584	-0.300064
67	292.6	290.185	292.429	-2.24383	2.41466
68	292.1	287.665	292.475	-4.80966	4.43466
69	292.2	286.583	292.496	-5.91244	5.6166
70	292	284.58	292.388	-7.80723	7.41973
71	292.1	281.517	292.192	-10.6749	10.5832
72	293.4	278.85	292.004	-13.1545	14.5503
73	292.2	305.596	291.821	13.7752	-13.396
74	292.1	302.748	291.646	11.1026	-10.6485
75	291.6	300.144	291.475	8.66937	-8.54437
76	290.9	297.626	291.312	6.31326	-6.72576
77	290.9	294.871	291.188	3.68361	-3.97111
78	290.8	292.133	291.075	1.0584	-1.3334
79	290.5	NA	NA	-2.24383	NA
80	290	NA	NA	-4.80966	NA
81	290.2	NA	NA	-5.91244	NA
82	290.1	NA	NA	-7.80723	NA
83	291	NA	NA	-10.6749	NA
84	291.8	NA	NA	-13.1545	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