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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 29 Nov 2014 17:45:14 +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/29/t1417283130le7itlffii5eelk.htm/, Retrieved Sun, 19 May 2024 13:38:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261246, Retrieved Sun, 19 May 2024 13:38:51 +0000

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-       [Classical Decomposition] [] [2014-11-29 17:45:14] [3b96c46cffecdf3c11148678d326f85c] [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	'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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261246&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261246&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261246&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 Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	111.4	NA	NA	-10.2809	NA
2	117	NA	NA	-1.9559	NA
3	141.7	NA	NA	13.8983	NA
4	120	NA	NA	0.246181	NA
5	132.1	NA	NA	4.51007	NA
6	146.7	NA	NA	17.0622	NA
7	122.5	118.173	125.629	-7.4566	4.32743
8	99.6	103.16	126.771	-23.6108	-3.56007
9	122.7	129.701	126.325	3.37604	-7.00104
10	139	128.705	125.604	3.10035	10.2955
11	117.8	115.995	125.129	-9.13368	1.80451
12	125.5	134.386	124.142	10.2448	-8.88646
13	134.5	112.861	123.142	-10.2809	21.6392
14	121.3	120.361	122.317	-1.9559	0.939236
15	126.7	135.74	121.842	13.8983	-9.03993
16	117.7	120.642	120.396	0.246181	-2.94201
17	123	122.148	117.637	4.51007	0.852431
18	132.1	132.504	115.442	17.0622	-0.403819
19	113.1	104.548	112.004	-7.4566	8.55243
20	89.2	84.5809	108.192	-23.6108	4.6191
21	121.7	109.122	105.746	3.37604	12.5781
22	105.3	105.988	102.887	3.10035	-0.687847
23	85.3	90.2538	99.3875	-9.13368	-4.95382
24	105.3	106.132	95.8875	10.2448	-0.832292
25	72.2	82.6399	92.9208	-10.2809	-10.4399
26	92.1	88.6566	90.6125	-1.9559	3.4434
27	97.2	102.161	88.2625	13.8983	-4.96076
28	78.6	86.3128	86.0667	0.246181	-7.71285
29	78.1	89.3851	84.875	4.51007	-11.2851
30	93	101.208	84.1458	17.0622	-8.20799
31	81	76.5267	83.9833	-7.4566	4.47326
32	65.9	60.2934	83.9042	-23.6108	5.6066
33	88.6	87.926	84.55	3.37604	0.673958
34	85.7	89.1003	86	3.10035	-3.40035
35	76.3	78.133	87.2667	-9.13368	-1.83299
36	96.8	99.049	88.8042	10.2448	-2.24896
37	76.8	79.9191	90.2	-10.2809	-3.1191
38	85.6	89.5399	91.4958	-1.9559	-3.93993
39	119.2	107.044	93.1458	13.8983	12.1559
40	91.4	95.2753	95.0292	0.246181	-3.87535
41	95.7	101.339	96.8292	4.51007	-5.63924
42	112.3	115.904	98.8417	17.0622	-3.60382
43	95.2	93.4726	100.929	-7.4566	1.72743
44	82.8	79.5892	103.2	-23.6108	3.21076
45	111.3	108.422	105.046	3.37604	2.87813
46	108.2	109.609	106.508	3.10035	-1.40868
47	97	99.2038	108.338	-9.13368	-2.20382
48	124.4	119.636	109.392	10.2448	4.76354
49	99.3	99.7108	109.992	-10.2809	-0.410764
50	117.6	108.727	110.683	-1.9559	8.87257
51	131.5	125.036	111.138	13.8983	6.46424
52	114.2	111.705	111.458	0.246181	2.49549
53	116.8	116.493	111.983	4.51007	0.306597
54	116.5	129.604	112.542	17.0622	-13.1038
55	105.4	105.602	113.058	-7.4566	-0.201736
56	89.2	89.5226	113.133	-23.6108	-0.322569
57	115.8	116.164	112.788	3.37604	-0.363542
58	111.4	116.496	113.396	3.10035	-5.09618
59	106.4	106.029	115.162	-9.13368	0.371181
60	128.4	128.303	118.058	10.2448	0.096875
61	107.7	108.698	118.979	-10.2809	-0.998264
62	111	115.544	117.5	-1.9559	-4.5441
63	129.8	130.177	116.279	13.8983	-0.377431
64	130.5	115.705	115.458	0.246181	14.7955
65	142.9	119.402	114.892	4.51007	23.4983
66	159.9	130.937	113.875	17.0622	28.9628
67	84.1	104.493	111.95	-7.4566	-20.3934
68	75	86.0684	109.679	-23.6108	-11.0684
69	100.7	110.98	107.604	3.37604	-10.2802
70	106.8	108.017	104.917	3.10035	-1.21701
71	97.4	92.0997	101.233	-9.13368	5.30035
72	113	107.407	97.1625	10.2448	5.59271
73	76.9	85.0858	95.3667	-10.2809	-8.18576
74	87.3	93.5858	95.5417	-1.9559	-6.28576
75	103.7	109.457	95.5583	13.8983	-5.7566
76	92.1	96.3753	96.1292	0.246181	-4.27535
77	92.9	102.148	97.6375	4.51007	-9.24757
78	112.2	117.358	100.296	17.0622	-5.15799
79	88.7	NA	NA	-7.4566	NA
80	74.6	NA	NA	-23.6108	NA
81	101.5	NA	NA	3.37604	NA
82	119.7	NA	NA	3.10035	NA
83	120.7	NA	NA	-9.13368	NA
84	153.5	NA	NA	10.2448	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 111.4 & NA & NA & -10.2809 & NA \tabularnewline
2 & 117 & NA & NA & -1.9559 & NA \tabularnewline
3 & 141.7 & NA & NA & 13.8983 & NA \tabularnewline
4 & 120 & NA & NA & 0.246181 & NA \tabularnewline
5 & 132.1 & NA & NA & 4.51007 & NA \tabularnewline
6 & 146.7 & NA & NA & 17.0622 & NA \tabularnewline
7 & 122.5 & 118.173 & 125.629 & -7.4566 & 4.32743 \tabularnewline
8 & 99.6 & 103.16 & 126.771 & -23.6108 & -3.56007 \tabularnewline
9 & 122.7 & 129.701 & 126.325 & 3.37604 & -7.00104 \tabularnewline
10 & 139 & 128.705 & 125.604 & 3.10035 & 10.2955 \tabularnewline
11 & 117.8 & 115.995 & 125.129 & -9.13368 & 1.80451 \tabularnewline
12 & 125.5 & 134.386 & 124.142 & 10.2448 & -8.88646 \tabularnewline
13 & 134.5 & 112.861 & 123.142 & -10.2809 & 21.6392 \tabularnewline
14 & 121.3 & 120.361 & 122.317 & -1.9559 & 0.939236 \tabularnewline
15 & 126.7 & 135.74 & 121.842 & 13.8983 & -9.03993 \tabularnewline
16 & 117.7 & 120.642 & 120.396 & 0.246181 & -2.94201 \tabularnewline
17 & 123 & 122.148 & 117.637 & 4.51007 & 0.852431 \tabularnewline
18 & 132.1 & 132.504 & 115.442 & 17.0622 & -0.403819 \tabularnewline
19 & 113.1 & 104.548 & 112.004 & -7.4566 & 8.55243 \tabularnewline
20 & 89.2 & 84.5809 & 108.192 & -23.6108 & 4.6191 \tabularnewline
21 & 121.7 & 109.122 & 105.746 & 3.37604 & 12.5781 \tabularnewline
22 & 105.3 & 105.988 & 102.887 & 3.10035 & -0.687847 \tabularnewline
23 & 85.3 & 90.2538 & 99.3875 & -9.13368 & -4.95382 \tabularnewline
24 & 105.3 & 106.132 & 95.8875 & 10.2448 & -0.832292 \tabularnewline
25 & 72.2 & 82.6399 & 92.9208 & -10.2809 & -10.4399 \tabularnewline
26 & 92.1 & 88.6566 & 90.6125 & -1.9559 & 3.4434 \tabularnewline
27 & 97.2 & 102.161 & 88.2625 & 13.8983 & -4.96076 \tabularnewline
28 & 78.6 & 86.3128 & 86.0667 & 0.246181 & -7.71285 \tabularnewline
29 & 78.1 & 89.3851 & 84.875 & 4.51007 & -11.2851 \tabularnewline
30 & 93 & 101.208 & 84.1458 & 17.0622 & -8.20799 \tabularnewline
31 & 81 & 76.5267 & 83.9833 & -7.4566 & 4.47326 \tabularnewline
32 & 65.9 & 60.2934 & 83.9042 & -23.6108 & 5.6066 \tabularnewline
33 & 88.6 & 87.926 & 84.55 & 3.37604 & 0.673958 \tabularnewline
34 & 85.7 & 89.1003 & 86 & 3.10035 & -3.40035 \tabularnewline
35 & 76.3 & 78.133 & 87.2667 & -9.13368 & -1.83299 \tabularnewline
36 & 96.8 & 99.049 & 88.8042 & 10.2448 & -2.24896 \tabularnewline
37 & 76.8 & 79.9191 & 90.2 & -10.2809 & -3.1191 \tabularnewline
38 & 85.6 & 89.5399 & 91.4958 & -1.9559 & -3.93993 \tabularnewline
39 & 119.2 & 107.044 & 93.1458 & 13.8983 & 12.1559 \tabularnewline
40 & 91.4 & 95.2753 & 95.0292 & 0.246181 & -3.87535 \tabularnewline
41 & 95.7 & 101.339 & 96.8292 & 4.51007 & -5.63924 \tabularnewline
42 & 112.3 & 115.904 & 98.8417 & 17.0622 & -3.60382 \tabularnewline
43 & 95.2 & 93.4726 & 100.929 & -7.4566 & 1.72743 \tabularnewline
44 & 82.8 & 79.5892 & 103.2 & -23.6108 & 3.21076 \tabularnewline
45 & 111.3 & 108.422 & 105.046 & 3.37604 & 2.87813 \tabularnewline
46 & 108.2 & 109.609 & 106.508 & 3.10035 & -1.40868 \tabularnewline
47 & 97 & 99.2038 & 108.338 & -9.13368 & -2.20382 \tabularnewline
48 & 124.4 & 119.636 & 109.392 & 10.2448 & 4.76354 \tabularnewline
49 & 99.3 & 99.7108 & 109.992 & -10.2809 & -0.410764 \tabularnewline
50 & 117.6 & 108.727 & 110.683 & -1.9559 & 8.87257 \tabularnewline
51 & 131.5 & 125.036 & 111.138 & 13.8983 & 6.46424 \tabularnewline
52 & 114.2 & 111.705 & 111.458 & 0.246181 & 2.49549 \tabularnewline
53 & 116.8 & 116.493 & 111.983 & 4.51007 & 0.306597 \tabularnewline
54 & 116.5 & 129.604 & 112.542 & 17.0622 & -13.1038 \tabularnewline
55 & 105.4 & 105.602 & 113.058 & -7.4566 & -0.201736 \tabularnewline
56 & 89.2 & 89.5226 & 113.133 & -23.6108 & -0.322569 \tabularnewline
57 & 115.8 & 116.164 & 112.788 & 3.37604 & -0.363542 \tabularnewline
58 & 111.4 & 116.496 & 113.396 & 3.10035 & -5.09618 \tabularnewline
59 & 106.4 & 106.029 & 115.162 & -9.13368 & 0.371181 \tabularnewline
60 & 128.4 & 128.303 & 118.058 & 10.2448 & 0.096875 \tabularnewline
61 & 107.7 & 108.698 & 118.979 & -10.2809 & -0.998264 \tabularnewline
62 & 111 & 115.544 & 117.5 & -1.9559 & -4.5441 \tabularnewline
63 & 129.8 & 130.177 & 116.279 & 13.8983 & -0.377431 \tabularnewline
64 & 130.5 & 115.705 & 115.458 & 0.246181 & 14.7955 \tabularnewline
65 & 142.9 & 119.402 & 114.892 & 4.51007 & 23.4983 \tabularnewline
66 & 159.9 & 130.937 & 113.875 & 17.0622 & 28.9628 \tabularnewline
67 & 84.1 & 104.493 & 111.95 & -7.4566 & -20.3934 \tabularnewline
68 & 75 & 86.0684 & 109.679 & -23.6108 & -11.0684 \tabularnewline
69 & 100.7 & 110.98 & 107.604 & 3.37604 & -10.2802 \tabularnewline
70 & 106.8 & 108.017 & 104.917 & 3.10035 & -1.21701 \tabularnewline
71 & 97.4 & 92.0997 & 101.233 & -9.13368 & 5.30035 \tabularnewline
72 & 113 & 107.407 & 97.1625 & 10.2448 & 5.59271 \tabularnewline
73 & 76.9 & 85.0858 & 95.3667 & -10.2809 & -8.18576 \tabularnewline
74 & 87.3 & 93.5858 & 95.5417 & -1.9559 & -6.28576 \tabularnewline
75 & 103.7 & 109.457 & 95.5583 & 13.8983 & -5.7566 \tabularnewline
76 & 92.1 & 96.3753 & 96.1292 & 0.246181 & -4.27535 \tabularnewline
77 & 92.9 & 102.148 & 97.6375 & 4.51007 & -9.24757 \tabularnewline
78 & 112.2 & 117.358 & 100.296 & 17.0622 & -5.15799 \tabularnewline
79 & 88.7 & NA & NA & -7.4566 & NA \tabularnewline
80 & 74.6 & NA & NA & -23.6108 & NA \tabularnewline
81 & 101.5 & NA & NA & 3.37604 & NA \tabularnewline
82 & 119.7 & NA & NA & 3.10035 & NA \tabularnewline
83 & 120.7 & NA & NA & -9.13368 & NA \tabularnewline
84 & 153.5 & NA & NA & 10.2448 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261246&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]111.4[/C][C]NA[/C][C]NA[/C][C]-10.2809[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]117[/C][C]NA[/C][C]NA[/C][C]-1.9559[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]141.7[/C][C]NA[/C][C]NA[/C][C]13.8983[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]120[/C][C]NA[/C][C]NA[/C][C]0.246181[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]132.1[/C][C]NA[/C][C]NA[/C][C]4.51007[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]146.7[/C][C]NA[/C][C]NA[/C][C]17.0622[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]122.5[/C][C]118.173[/C][C]125.629[/C][C]-7.4566[/C][C]4.32743[/C][/ROW]
[ROW][C]8[/C][C]99.6[/C][C]103.16[/C][C]126.771[/C][C]-23.6108[/C][C]-3.56007[/C][/ROW]
[ROW][C]9[/C][C]122.7[/C][C]129.701[/C][C]126.325[/C][C]3.37604[/C][C]-7.00104[/C][/ROW]
[ROW][C]10[/C][C]139[/C][C]128.705[/C][C]125.604[/C][C]3.10035[/C][C]10.2955[/C][/ROW]
[ROW][C]11[/C][C]117.8[/C][C]115.995[/C][C]125.129[/C][C]-9.13368[/C][C]1.80451[/C][/ROW]
[ROW][C]12[/C][C]125.5[/C][C]134.386[/C][C]124.142[/C][C]10.2448[/C][C]-8.88646[/C][/ROW]
[ROW][C]13[/C][C]134.5[/C][C]112.861[/C][C]123.142[/C][C]-10.2809[/C][C]21.6392[/C][/ROW]
[ROW][C]14[/C][C]121.3[/C][C]120.361[/C][C]122.317[/C][C]-1.9559[/C][C]0.939236[/C][/ROW]
[ROW][C]15[/C][C]126.7[/C][C]135.74[/C][C]121.842[/C][C]13.8983[/C][C]-9.03993[/C][/ROW]
[ROW][C]16[/C][C]117.7[/C][C]120.642[/C][C]120.396[/C][C]0.246181[/C][C]-2.94201[/C][/ROW]
[ROW][C]17[/C][C]123[/C][C]122.148[/C][C]117.637[/C][C]4.51007[/C][C]0.852431[/C][/ROW]
[ROW][C]18[/C][C]132.1[/C][C]132.504[/C][C]115.442[/C][C]17.0622[/C][C]-0.403819[/C][/ROW]
[ROW][C]19[/C][C]113.1[/C][C]104.548[/C][C]112.004[/C][C]-7.4566[/C][C]8.55243[/C][/ROW]
[ROW][C]20[/C][C]89.2[/C][C]84.5809[/C][C]108.192[/C][C]-23.6108[/C][C]4.6191[/C][/ROW]
[ROW][C]21[/C][C]121.7[/C][C]109.122[/C][C]105.746[/C][C]3.37604[/C][C]12.5781[/C][/ROW]
[ROW][C]22[/C][C]105.3[/C][C]105.988[/C][C]102.887[/C][C]3.10035[/C][C]-0.687847[/C][/ROW]
[ROW][C]23[/C][C]85.3[/C][C]90.2538[/C][C]99.3875[/C][C]-9.13368[/C][C]-4.95382[/C][/ROW]
[ROW][C]24[/C][C]105.3[/C][C]106.132[/C][C]95.8875[/C][C]10.2448[/C][C]-0.832292[/C][/ROW]
[ROW][C]25[/C][C]72.2[/C][C]82.6399[/C][C]92.9208[/C][C]-10.2809[/C][C]-10.4399[/C][/ROW]
[ROW][C]26[/C][C]92.1[/C][C]88.6566[/C][C]90.6125[/C][C]-1.9559[/C][C]3.4434[/C][/ROW]
[ROW][C]27[/C][C]97.2[/C][C]102.161[/C][C]88.2625[/C][C]13.8983[/C][C]-4.96076[/C][/ROW]
[ROW][C]28[/C][C]78.6[/C][C]86.3128[/C][C]86.0667[/C][C]0.246181[/C][C]-7.71285[/C][/ROW]
[ROW][C]29[/C][C]78.1[/C][C]89.3851[/C][C]84.875[/C][C]4.51007[/C][C]-11.2851[/C][/ROW]
[ROW][C]30[/C][C]93[/C][C]101.208[/C][C]84.1458[/C][C]17.0622[/C][C]-8.20799[/C][/ROW]
[ROW][C]31[/C][C]81[/C][C]76.5267[/C][C]83.9833[/C][C]-7.4566[/C][C]4.47326[/C][/ROW]
[ROW][C]32[/C][C]65.9[/C][C]60.2934[/C][C]83.9042[/C][C]-23.6108[/C][C]5.6066[/C][/ROW]
[ROW][C]33[/C][C]88.6[/C][C]87.926[/C][C]84.55[/C][C]3.37604[/C][C]0.673958[/C][/ROW]
[ROW][C]34[/C][C]85.7[/C][C]89.1003[/C][C]86[/C][C]3.10035[/C][C]-3.40035[/C][/ROW]
[ROW][C]35[/C][C]76.3[/C][C]78.133[/C][C]87.2667[/C][C]-9.13368[/C][C]-1.83299[/C][/ROW]
[ROW][C]36[/C][C]96.8[/C][C]99.049[/C][C]88.8042[/C][C]10.2448[/C][C]-2.24896[/C][/ROW]
[ROW][C]37[/C][C]76.8[/C][C]79.9191[/C][C]90.2[/C][C]-10.2809[/C][C]-3.1191[/C][/ROW]
[ROW][C]38[/C][C]85.6[/C][C]89.5399[/C][C]91.4958[/C][C]-1.9559[/C][C]-3.93993[/C][/ROW]
[ROW][C]39[/C][C]119.2[/C][C]107.044[/C][C]93.1458[/C][C]13.8983[/C][C]12.1559[/C][/ROW]
[ROW][C]40[/C][C]91.4[/C][C]95.2753[/C][C]95.0292[/C][C]0.246181[/C][C]-3.87535[/C][/ROW]
[ROW][C]41[/C][C]95.7[/C][C]101.339[/C][C]96.8292[/C][C]4.51007[/C][C]-5.63924[/C][/ROW]
[ROW][C]42[/C][C]112.3[/C][C]115.904[/C][C]98.8417[/C][C]17.0622[/C][C]-3.60382[/C][/ROW]
[ROW][C]43[/C][C]95.2[/C][C]93.4726[/C][C]100.929[/C][C]-7.4566[/C][C]1.72743[/C][/ROW]
[ROW][C]44[/C][C]82.8[/C][C]79.5892[/C][C]103.2[/C][C]-23.6108[/C][C]3.21076[/C][/ROW]
[ROW][C]45[/C][C]111.3[/C][C]108.422[/C][C]105.046[/C][C]3.37604[/C][C]2.87813[/C][/ROW]
[ROW][C]46[/C][C]108.2[/C][C]109.609[/C][C]106.508[/C][C]3.10035[/C][C]-1.40868[/C][/ROW]
[ROW][C]47[/C][C]97[/C][C]99.2038[/C][C]108.338[/C][C]-9.13368[/C][C]-2.20382[/C][/ROW]
[ROW][C]48[/C][C]124.4[/C][C]119.636[/C][C]109.392[/C][C]10.2448[/C][C]4.76354[/C][/ROW]
[ROW][C]49[/C][C]99.3[/C][C]99.7108[/C][C]109.992[/C][C]-10.2809[/C][C]-0.410764[/C][/ROW]
[ROW][C]50[/C][C]117.6[/C][C]108.727[/C][C]110.683[/C][C]-1.9559[/C][C]8.87257[/C][/ROW]
[ROW][C]51[/C][C]131.5[/C][C]125.036[/C][C]111.138[/C][C]13.8983[/C][C]6.46424[/C][/ROW]
[ROW][C]52[/C][C]114.2[/C][C]111.705[/C][C]111.458[/C][C]0.246181[/C][C]2.49549[/C][/ROW]
[ROW][C]53[/C][C]116.8[/C][C]116.493[/C][C]111.983[/C][C]4.51007[/C][C]0.306597[/C][/ROW]
[ROW][C]54[/C][C]116.5[/C][C]129.604[/C][C]112.542[/C][C]17.0622[/C][C]-13.1038[/C][/ROW]
[ROW][C]55[/C][C]105.4[/C][C]105.602[/C][C]113.058[/C][C]-7.4566[/C][C]-0.201736[/C][/ROW]
[ROW][C]56[/C][C]89.2[/C][C]89.5226[/C][C]113.133[/C][C]-23.6108[/C][C]-0.322569[/C][/ROW]
[ROW][C]57[/C][C]115.8[/C][C]116.164[/C][C]112.788[/C][C]3.37604[/C][C]-0.363542[/C][/ROW]
[ROW][C]58[/C][C]111.4[/C][C]116.496[/C][C]113.396[/C][C]3.10035[/C][C]-5.09618[/C][/ROW]
[ROW][C]59[/C][C]106.4[/C][C]106.029[/C][C]115.162[/C][C]-9.13368[/C][C]0.371181[/C][/ROW]
[ROW][C]60[/C][C]128.4[/C][C]128.303[/C][C]118.058[/C][C]10.2448[/C][C]0.096875[/C][/ROW]
[ROW][C]61[/C][C]107.7[/C][C]108.698[/C][C]118.979[/C][C]-10.2809[/C][C]-0.998264[/C][/ROW]
[ROW][C]62[/C][C]111[/C][C]115.544[/C][C]117.5[/C][C]-1.9559[/C][C]-4.5441[/C][/ROW]
[ROW][C]63[/C][C]129.8[/C][C]130.177[/C][C]116.279[/C][C]13.8983[/C][C]-0.377431[/C][/ROW]
[ROW][C]64[/C][C]130.5[/C][C]115.705[/C][C]115.458[/C][C]0.246181[/C][C]14.7955[/C][/ROW]
[ROW][C]65[/C][C]142.9[/C][C]119.402[/C][C]114.892[/C][C]4.51007[/C][C]23.4983[/C][/ROW]
[ROW][C]66[/C][C]159.9[/C][C]130.937[/C][C]113.875[/C][C]17.0622[/C][C]28.9628[/C][/ROW]
[ROW][C]67[/C][C]84.1[/C][C]104.493[/C][C]111.95[/C][C]-7.4566[/C][C]-20.3934[/C][/ROW]
[ROW][C]68[/C][C]75[/C][C]86.0684[/C][C]109.679[/C][C]-23.6108[/C][C]-11.0684[/C][/ROW]
[ROW][C]69[/C][C]100.7[/C][C]110.98[/C][C]107.604[/C][C]3.37604[/C][C]-10.2802[/C][/ROW]
[ROW][C]70[/C][C]106.8[/C][C]108.017[/C][C]104.917[/C][C]3.10035[/C][C]-1.21701[/C][/ROW]
[ROW][C]71[/C][C]97.4[/C][C]92.0997[/C][C]101.233[/C][C]-9.13368[/C][C]5.30035[/C][/ROW]
[ROW][C]72[/C][C]113[/C][C]107.407[/C][C]97.1625[/C][C]10.2448[/C][C]5.59271[/C][/ROW]
[ROW][C]73[/C][C]76.9[/C][C]85.0858[/C][C]95.3667[/C][C]-10.2809[/C][C]-8.18576[/C][/ROW]
[ROW][C]74[/C][C]87.3[/C][C]93.5858[/C][C]95.5417[/C][C]-1.9559[/C][C]-6.28576[/C][/ROW]
[ROW][C]75[/C][C]103.7[/C][C]109.457[/C][C]95.5583[/C][C]13.8983[/C][C]-5.7566[/C][/ROW]
[ROW][C]76[/C][C]92.1[/C][C]96.3753[/C][C]96.1292[/C][C]0.246181[/C][C]-4.27535[/C][/ROW]
[ROW][C]77[/C][C]92.9[/C][C]102.148[/C][C]97.6375[/C][C]4.51007[/C][C]-9.24757[/C][/ROW]
[ROW][C]78[/C][C]112.2[/C][C]117.358[/C][C]100.296[/C][C]17.0622[/C][C]-5.15799[/C][/ROW]
[ROW][C]79[/C][C]88.7[/C][C]NA[/C][C]NA[/C][C]-7.4566[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]74.6[/C][C]NA[/C][C]NA[/C][C]-23.6108[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]101.5[/C][C]NA[/C][C]NA[/C][C]3.37604[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]119.7[/C][C]NA[/C][C]NA[/C][C]3.10035[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]120.7[/C][C]NA[/C][C]NA[/C][C]-9.13368[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]153.5[/C][C]NA[/C][C]NA[/C][C]10.2448[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261246&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261246&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	111.4	NA	NA	-10.2809	NA
2	117	NA	NA	-1.9559	NA
3	141.7	NA	NA	13.8983	NA
4	120	NA	NA	0.246181	NA
5	132.1	NA	NA	4.51007	NA
6	146.7	NA	NA	17.0622	NA
7	122.5	118.173	125.629	-7.4566	4.32743
8	99.6	103.16	126.771	-23.6108	-3.56007
9	122.7	129.701	126.325	3.37604	-7.00104
10	139	128.705	125.604	3.10035	10.2955
11	117.8	115.995	125.129	-9.13368	1.80451
12	125.5	134.386	124.142	10.2448	-8.88646
13	134.5	112.861	123.142	-10.2809	21.6392
14	121.3	120.361	122.317	-1.9559	0.939236
15	126.7	135.74	121.842	13.8983	-9.03993
16	117.7	120.642	120.396	0.246181	-2.94201
17	123	122.148	117.637	4.51007	0.852431
18	132.1	132.504	115.442	17.0622	-0.403819
19	113.1	104.548	112.004	-7.4566	8.55243
20	89.2	84.5809	108.192	-23.6108	4.6191
21	121.7	109.122	105.746	3.37604	12.5781
22	105.3	105.988	102.887	3.10035	-0.687847
23	85.3	90.2538	99.3875	-9.13368	-4.95382
24	105.3	106.132	95.8875	10.2448	-0.832292
25	72.2	82.6399	92.9208	-10.2809	-10.4399
26	92.1	88.6566	90.6125	-1.9559	3.4434
27	97.2	102.161	88.2625	13.8983	-4.96076
28	78.6	86.3128	86.0667	0.246181	-7.71285
29	78.1	89.3851	84.875	4.51007	-11.2851
30	93	101.208	84.1458	17.0622	-8.20799
31	81	76.5267	83.9833	-7.4566	4.47326
32	65.9	60.2934	83.9042	-23.6108	5.6066
33	88.6	87.926	84.55	3.37604	0.673958
34	85.7	89.1003	86	3.10035	-3.40035
35	76.3	78.133	87.2667	-9.13368	-1.83299
36	96.8	99.049	88.8042	10.2448	-2.24896
37	76.8	79.9191	90.2	-10.2809	-3.1191
38	85.6	89.5399	91.4958	-1.9559	-3.93993
39	119.2	107.044	93.1458	13.8983	12.1559
40	91.4	95.2753	95.0292	0.246181	-3.87535
41	95.7	101.339	96.8292	4.51007	-5.63924
42	112.3	115.904	98.8417	17.0622	-3.60382
43	95.2	93.4726	100.929	-7.4566	1.72743
44	82.8	79.5892	103.2	-23.6108	3.21076
45	111.3	108.422	105.046	3.37604	2.87813
46	108.2	109.609	106.508	3.10035	-1.40868
47	97	99.2038	108.338	-9.13368	-2.20382
48	124.4	119.636	109.392	10.2448	4.76354
49	99.3	99.7108	109.992	-10.2809	-0.410764
50	117.6	108.727	110.683	-1.9559	8.87257
51	131.5	125.036	111.138	13.8983	6.46424
52	114.2	111.705	111.458	0.246181	2.49549
53	116.8	116.493	111.983	4.51007	0.306597
54	116.5	129.604	112.542	17.0622	-13.1038
55	105.4	105.602	113.058	-7.4566	-0.201736
56	89.2	89.5226	113.133	-23.6108	-0.322569
57	115.8	116.164	112.788	3.37604	-0.363542
58	111.4	116.496	113.396	3.10035	-5.09618
59	106.4	106.029	115.162	-9.13368	0.371181
60	128.4	128.303	118.058	10.2448	0.096875
61	107.7	108.698	118.979	-10.2809	-0.998264
62	111	115.544	117.5	-1.9559	-4.5441
63	129.8	130.177	116.279	13.8983	-0.377431
64	130.5	115.705	115.458	0.246181	14.7955
65	142.9	119.402	114.892	4.51007	23.4983
66	159.9	130.937	113.875	17.0622	28.9628
67	84.1	104.493	111.95	-7.4566	-20.3934
68	75	86.0684	109.679	-23.6108	-11.0684
69	100.7	110.98	107.604	3.37604	-10.2802
70	106.8	108.017	104.917	3.10035	-1.21701
71	97.4	92.0997	101.233	-9.13368	5.30035
72	113	107.407	97.1625	10.2448	5.59271
73	76.9	85.0858	95.3667	-10.2809	-8.18576
74	87.3	93.5858	95.5417	-1.9559	-6.28576
75	103.7	109.457	95.5583	13.8983	-5.7566
76	92.1	96.3753	96.1292	0.246181	-4.27535
77	92.9	102.148	97.6375	4.51007	-9.24757
78	112.2	117.358	100.296	17.0622	-5.15799
79	88.7	NA	NA	-7.4566	NA
80	74.6	NA	NA	-23.6108	NA
81	101.5	NA	NA	3.37604	NA
82	119.7	NA	NA	3.10035	NA
83	120.7	NA	NA	-9.13368	NA
84	153.5	NA	NA	10.2448	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