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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 28 Nov 2014 11:41:08 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/28/t1417174904ey60mw87ny22gwd.htm/, Retrieved Sun, 19 May 2024 13:00:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260852, Retrieved Sun, 19 May 2024 13:00:25 +0000

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-       [Classical Decomposition] [] [2014-11-28 11:41:08] [5cf6a598f846f655ef95f65053f7ffc6] [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=260852&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=260852&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260852&T=0

As an alternative you can also use a QR Code:

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	70.38	NA	NA	0.408056	NA
2	70.38	NA	NA	-0.194694	NA
3	70.29	NA	NA	-0.185861	NA
4	70.42	NA	NA	-0.220528	NA
5	70.29	NA	NA	-0.138111	NA
6	70.59	NA	NA	-0.0837778	NA
7	70.64	70.5786	70.6179	-0.0392778	0.0613611
8	70.64	70.6036	70.6821	-0.0785278	0.0364444
9	70.68	70.6592	70.75	-0.0907778	0.0207778
10	70.78	70.8025	70.8129	-0.0104444	-0.0224722
11	70.9	71.1065	70.8767	0.229806	-0.206472
12	71.04	71.3446	70.9404	0.404139	-0.304556
13	71.15	71.4001	70.9921	0.408056	-0.250139
14	71.15	70.8466	71.0412	-0.194694	0.303444
15	71.15	70.9029	71.0888	-0.185861	0.247111
16	71.07	70.9103	71.1308	-0.220528	0.159694
17	71.17	71.0277	71.1658	-0.138111	0.142278
18	71.24	71.1179	71.2017	-0.0837778	0.122111
19	71.23	71.1978	71.2371	-0.0392778	0.0321944
20	71.23	71.1894	71.2679	-0.0785278	0.0406111
21	71.23	71.2113	71.3021	-0.0907778	0.0186944
22	71.24	71.3329	71.3433	-0.0104444	-0.0928889
23	71.28	71.6211	71.3912	0.229806	-0.341056
24	71.52	71.8383	71.4342	0.404139	-0.318306
25	71.52	71.886	71.4779	0.408056	-0.365972
26	71.52	71.3357	71.5304	-0.194694	0.184278
27	71.6	71.3954	71.5812	-0.185861	0.204611
28	71.61	71.4086	71.6292	-0.220528	0.201361
29	71.78	71.5536	71.6917	-0.138111	0.226444
30	71.66	71.6883	71.7721	-0.0837778	-0.0283056
31	71.86	71.8174	71.8567	-0.0392778	0.0426111
32	71.86	71.8648	71.9433	-0.0785278	-0.00480556
33	71.82	71.9451	72.0358	-0.0907778	-0.125056
34	71.8	72.1275	72.1379	-0.0104444	-0.327472
35	72.22	72.4736	72.2437	0.229806	-0.253556
36	72.51	72.7575	72.3533	0.404139	-0.247472
37	72.56	72.8689	72.4608	0.408056	-0.308889
38	72.56	72.3678	72.5625	-0.194694	0.192194
39	72.78	72.4866	72.6725	-0.185861	0.293361
40	72.88	72.5953	72.8158	-0.220528	0.284694
41	73.05	72.8361	72.9742	-0.138111	0.213944
42	73.02	73.0421	73.1258	-0.0837778	-0.0220556
43	73.08	73.2399	73.2792	-0.0392778	-0.159889
44	73.08	73.3523	73.4308	-0.0785278	-0.272306
45	73.24	73.4817	73.5725	-0.0907778	-0.241722
46	73.82	73.6921	73.7025	-0.0104444	0.127944
47	74	74.0606	73.8308	0.229806	-0.0606389
48	74.37	74.3846	73.9804	0.404139	-0.0145556
49	74.38	74.5618	74.1537	0.408056	-0.181806
50	74.38	74.1349	74.3296	-0.194694	0.245111
51	74.36	74.3137	74.4996	-0.185861	0.0462778
52	74.42	74.4178	74.6383	-0.220528	0.00219444
53	74.59	74.6344	74.7725	-0.138111	-0.0443889
54	75.07	74.8312	74.915	-0.0837778	0.238778
55	75.19	75.0086	75.0479	-0.0392778	0.181361
56	75.19	74.9894	75.0679	-0.0785278	0.200611
57	75.21	74.8821	74.9729	-0.0907778	0.327861
58	75.18	74.8646	74.875	-0.0104444	0.315444
59	75.86	74.9977	74.7679	0.229806	0.862278
60	75.93	75.0446	74.6404	0.404139	0.885444
61	76.01	74.9026	74.4946	0.408056	1.10736
62	73.23	74.1545	74.3492	-0.194694	-0.924472
63	73.23	74.0208	74.2067	-0.185861	-0.790806
64	73.2	73.8474	74.0679	-0.220528	-0.647389
65	73.24	73.7777	73.9158	-0.138111	-0.537722
66	73.36	73.67	73.7538	-0.0837778	-0.309972
67	73.4	73.557	73.5963	-0.0392778	-0.156972
68	73.49	NA	NA	-0.0785278	NA
69	73.49	NA	NA	-0.0907778	NA
70	73.57	NA	NA	-0.0104444	NA
71	73.82	NA	NA	0.229806	NA
72	74.08	NA	NA	0.404139	NA
73	74.08	NA	NA	0.408056	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 70.38 & NA & NA & 0.408056 & NA \tabularnewline
2 & 70.38 & NA & NA & -0.194694 & NA \tabularnewline
3 & 70.29 & NA & NA & -0.185861 & NA \tabularnewline
4 & 70.42 & NA & NA & -0.220528 & NA \tabularnewline
5 & 70.29 & NA & NA & -0.138111 & NA \tabularnewline
6 & 70.59 & NA & NA & -0.0837778 & NA \tabularnewline
7 & 70.64 & 70.5786 & 70.6179 & -0.0392778 & 0.0613611 \tabularnewline
8 & 70.64 & 70.6036 & 70.6821 & -0.0785278 & 0.0364444 \tabularnewline
9 & 70.68 & 70.6592 & 70.75 & -0.0907778 & 0.0207778 \tabularnewline
10 & 70.78 & 70.8025 & 70.8129 & -0.0104444 & -0.0224722 \tabularnewline
11 & 70.9 & 71.1065 & 70.8767 & 0.229806 & -0.206472 \tabularnewline
12 & 71.04 & 71.3446 & 70.9404 & 0.404139 & -0.304556 \tabularnewline
13 & 71.15 & 71.4001 & 70.9921 & 0.408056 & -0.250139 \tabularnewline
14 & 71.15 & 70.8466 & 71.0412 & -0.194694 & 0.303444 \tabularnewline
15 & 71.15 & 70.9029 & 71.0888 & -0.185861 & 0.247111 \tabularnewline
16 & 71.07 & 70.9103 & 71.1308 & -0.220528 & 0.159694 \tabularnewline
17 & 71.17 & 71.0277 & 71.1658 & -0.138111 & 0.142278 \tabularnewline
18 & 71.24 & 71.1179 & 71.2017 & -0.0837778 & 0.122111 \tabularnewline
19 & 71.23 & 71.1978 & 71.2371 & -0.0392778 & 0.0321944 \tabularnewline
20 & 71.23 & 71.1894 & 71.2679 & -0.0785278 & 0.0406111 \tabularnewline
21 & 71.23 & 71.2113 & 71.3021 & -0.0907778 & 0.0186944 \tabularnewline
22 & 71.24 & 71.3329 & 71.3433 & -0.0104444 & -0.0928889 \tabularnewline
23 & 71.28 & 71.6211 & 71.3912 & 0.229806 & -0.341056 \tabularnewline
24 & 71.52 & 71.8383 & 71.4342 & 0.404139 & -0.318306 \tabularnewline
25 & 71.52 & 71.886 & 71.4779 & 0.408056 & -0.365972 \tabularnewline
26 & 71.52 & 71.3357 & 71.5304 & -0.194694 & 0.184278 \tabularnewline
27 & 71.6 & 71.3954 & 71.5812 & -0.185861 & 0.204611 \tabularnewline
28 & 71.61 & 71.4086 & 71.6292 & -0.220528 & 0.201361 \tabularnewline
29 & 71.78 & 71.5536 & 71.6917 & -0.138111 & 0.226444 \tabularnewline
30 & 71.66 & 71.6883 & 71.7721 & -0.0837778 & -0.0283056 \tabularnewline
31 & 71.86 & 71.8174 & 71.8567 & -0.0392778 & 0.0426111 \tabularnewline
32 & 71.86 & 71.8648 & 71.9433 & -0.0785278 & -0.00480556 \tabularnewline
33 & 71.82 & 71.9451 & 72.0358 & -0.0907778 & -0.125056 \tabularnewline
34 & 71.8 & 72.1275 & 72.1379 & -0.0104444 & -0.327472 \tabularnewline
35 & 72.22 & 72.4736 & 72.2437 & 0.229806 & -0.253556 \tabularnewline
36 & 72.51 & 72.7575 & 72.3533 & 0.404139 & -0.247472 \tabularnewline
37 & 72.56 & 72.8689 & 72.4608 & 0.408056 & -0.308889 \tabularnewline
38 & 72.56 & 72.3678 & 72.5625 & -0.194694 & 0.192194 \tabularnewline
39 & 72.78 & 72.4866 & 72.6725 & -0.185861 & 0.293361 \tabularnewline
40 & 72.88 & 72.5953 & 72.8158 & -0.220528 & 0.284694 \tabularnewline
41 & 73.05 & 72.8361 & 72.9742 & -0.138111 & 0.213944 \tabularnewline
42 & 73.02 & 73.0421 & 73.1258 & -0.0837778 & -0.0220556 \tabularnewline
43 & 73.08 & 73.2399 & 73.2792 & -0.0392778 & -0.159889 \tabularnewline
44 & 73.08 & 73.3523 & 73.4308 & -0.0785278 & -0.272306 \tabularnewline
45 & 73.24 & 73.4817 & 73.5725 & -0.0907778 & -0.241722 \tabularnewline
46 & 73.82 & 73.6921 & 73.7025 & -0.0104444 & 0.127944 \tabularnewline
47 & 74 & 74.0606 & 73.8308 & 0.229806 & -0.0606389 \tabularnewline
48 & 74.37 & 74.3846 & 73.9804 & 0.404139 & -0.0145556 \tabularnewline
49 & 74.38 & 74.5618 & 74.1537 & 0.408056 & -0.181806 \tabularnewline
50 & 74.38 & 74.1349 & 74.3296 & -0.194694 & 0.245111 \tabularnewline
51 & 74.36 & 74.3137 & 74.4996 & -0.185861 & 0.0462778 \tabularnewline
52 & 74.42 & 74.4178 & 74.6383 & -0.220528 & 0.00219444 \tabularnewline
53 & 74.59 & 74.6344 & 74.7725 & -0.138111 & -0.0443889 \tabularnewline
54 & 75.07 & 74.8312 & 74.915 & -0.0837778 & 0.238778 \tabularnewline
55 & 75.19 & 75.0086 & 75.0479 & -0.0392778 & 0.181361 \tabularnewline
56 & 75.19 & 74.9894 & 75.0679 & -0.0785278 & 0.200611 \tabularnewline
57 & 75.21 & 74.8821 & 74.9729 & -0.0907778 & 0.327861 \tabularnewline
58 & 75.18 & 74.8646 & 74.875 & -0.0104444 & 0.315444 \tabularnewline
59 & 75.86 & 74.9977 & 74.7679 & 0.229806 & 0.862278 \tabularnewline
60 & 75.93 & 75.0446 & 74.6404 & 0.404139 & 0.885444 \tabularnewline
61 & 76.01 & 74.9026 & 74.4946 & 0.408056 & 1.10736 \tabularnewline
62 & 73.23 & 74.1545 & 74.3492 & -0.194694 & -0.924472 \tabularnewline
63 & 73.23 & 74.0208 & 74.2067 & -0.185861 & -0.790806 \tabularnewline
64 & 73.2 & 73.8474 & 74.0679 & -0.220528 & -0.647389 \tabularnewline
65 & 73.24 & 73.7777 & 73.9158 & -0.138111 & -0.537722 \tabularnewline
66 & 73.36 & 73.67 & 73.7538 & -0.0837778 & -0.309972 \tabularnewline
67 & 73.4 & 73.557 & 73.5963 & -0.0392778 & -0.156972 \tabularnewline
68 & 73.49 & NA & NA & -0.0785278 & NA \tabularnewline
69 & 73.49 & NA & NA & -0.0907778 & NA \tabularnewline
70 & 73.57 & NA & NA & -0.0104444 & NA \tabularnewline
71 & 73.82 & NA & NA & 0.229806 & NA \tabularnewline
72 & 74.08 & NA & NA & 0.404139 & NA \tabularnewline
73 & 74.08 & NA & NA & 0.408056 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260852&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]70.38[/C][C]NA[/C][C]NA[/C][C]0.408056[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]70.38[/C][C]NA[/C][C]NA[/C][C]-0.194694[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]70.29[/C][C]NA[/C][C]NA[/C][C]-0.185861[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]70.42[/C][C]NA[/C][C]NA[/C][C]-0.220528[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]70.29[/C][C]NA[/C][C]NA[/C][C]-0.138111[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]70.59[/C][C]NA[/C][C]NA[/C][C]-0.0837778[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]70.64[/C][C]70.5786[/C][C]70.6179[/C][C]-0.0392778[/C][C]0.0613611[/C][/ROW]
[ROW][C]8[/C][C]70.64[/C][C]70.6036[/C][C]70.6821[/C][C]-0.0785278[/C][C]0.0364444[/C][/ROW]
[ROW][C]9[/C][C]70.68[/C][C]70.6592[/C][C]70.75[/C][C]-0.0907778[/C][C]0.0207778[/C][/ROW]
[ROW][C]10[/C][C]70.78[/C][C]70.8025[/C][C]70.8129[/C][C]-0.0104444[/C][C]-0.0224722[/C][/ROW]
[ROW][C]11[/C][C]70.9[/C][C]71.1065[/C][C]70.8767[/C][C]0.229806[/C][C]-0.206472[/C][/ROW]
[ROW][C]12[/C][C]71.04[/C][C]71.3446[/C][C]70.9404[/C][C]0.404139[/C][C]-0.304556[/C][/ROW]
[ROW][C]13[/C][C]71.15[/C][C]71.4001[/C][C]70.9921[/C][C]0.408056[/C][C]-0.250139[/C][/ROW]
[ROW][C]14[/C][C]71.15[/C][C]70.8466[/C][C]71.0412[/C][C]-0.194694[/C][C]0.303444[/C][/ROW]
[ROW][C]15[/C][C]71.15[/C][C]70.9029[/C][C]71.0888[/C][C]-0.185861[/C][C]0.247111[/C][/ROW]
[ROW][C]16[/C][C]71.07[/C][C]70.9103[/C][C]71.1308[/C][C]-0.220528[/C][C]0.159694[/C][/ROW]
[ROW][C]17[/C][C]71.17[/C][C]71.0277[/C][C]71.1658[/C][C]-0.138111[/C][C]0.142278[/C][/ROW]
[ROW][C]18[/C][C]71.24[/C][C]71.1179[/C][C]71.2017[/C][C]-0.0837778[/C][C]0.122111[/C][/ROW]
[ROW][C]19[/C][C]71.23[/C][C]71.1978[/C][C]71.2371[/C][C]-0.0392778[/C][C]0.0321944[/C][/ROW]
[ROW][C]20[/C][C]71.23[/C][C]71.1894[/C][C]71.2679[/C][C]-0.0785278[/C][C]0.0406111[/C][/ROW]
[ROW][C]21[/C][C]71.23[/C][C]71.2113[/C][C]71.3021[/C][C]-0.0907778[/C][C]0.0186944[/C][/ROW]
[ROW][C]22[/C][C]71.24[/C][C]71.3329[/C][C]71.3433[/C][C]-0.0104444[/C][C]-0.0928889[/C][/ROW]
[ROW][C]23[/C][C]71.28[/C][C]71.6211[/C][C]71.3912[/C][C]0.229806[/C][C]-0.341056[/C][/ROW]
[ROW][C]24[/C][C]71.52[/C][C]71.8383[/C][C]71.4342[/C][C]0.404139[/C][C]-0.318306[/C][/ROW]
[ROW][C]25[/C][C]71.52[/C][C]71.886[/C][C]71.4779[/C][C]0.408056[/C][C]-0.365972[/C][/ROW]
[ROW][C]26[/C][C]71.52[/C][C]71.3357[/C][C]71.5304[/C][C]-0.194694[/C][C]0.184278[/C][/ROW]
[ROW][C]27[/C][C]71.6[/C][C]71.3954[/C][C]71.5812[/C][C]-0.185861[/C][C]0.204611[/C][/ROW]
[ROW][C]28[/C][C]71.61[/C][C]71.4086[/C][C]71.6292[/C][C]-0.220528[/C][C]0.201361[/C][/ROW]
[ROW][C]29[/C][C]71.78[/C][C]71.5536[/C][C]71.6917[/C][C]-0.138111[/C][C]0.226444[/C][/ROW]
[ROW][C]30[/C][C]71.66[/C][C]71.6883[/C][C]71.7721[/C][C]-0.0837778[/C][C]-0.0283056[/C][/ROW]
[ROW][C]31[/C][C]71.86[/C][C]71.8174[/C][C]71.8567[/C][C]-0.0392778[/C][C]0.0426111[/C][/ROW]
[ROW][C]32[/C][C]71.86[/C][C]71.8648[/C][C]71.9433[/C][C]-0.0785278[/C][C]-0.00480556[/C][/ROW]
[ROW][C]33[/C][C]71.82[/C][C]71.9451[/C][C]72.0358[/C][C]-0.0907778[/C][C]-0.125056[/C][/ROW]
[ROW][C]34[/C][C]71.8[/C][C]72.1275[/C][C]72.1379[/C][C]-0.0104444[/C][C]-0.327472[/C][/ROW]
[ROW][C]35[/C][C]72.22[/C][C]72.4736[/C][C]72.2437[/C][C]0.229806[/C][C]-0.253556[/C][/ROW]
[ROW][C]36[/C][C]72.51[/C][C]72.7575[/C][C]72.3533[/C][C]0.404139[/C][C]-0.247472[/C][/ROW]
[ROW][C]37[/C][C]72.56[/C][C]72.8689[/C][C]72.4608[/C][C]0.408056[/C][C]-0.308889[/C][/ROW]
[ROW][C]38[/C][C]72.56[/C][C]72.3678[/C][C]72.5625[/C][C]-0.194694[/C][C]0.192194[/C][/ROW]
[ROW][C]39[/C][C]72.78[/C][C]72.4866[/C][C]72.6725[/C][C]-0.185861[/C][C]0.293361[/C][/ROW]
[ROW][C]40[/C][C]72.88[/C][C]72.5953[/C][C]72.8158[/C][C]-0.220528[/C][C]0.284694[/C][/ROW]
[ROW][C]41[/C][C]73.05[/C][C]72.8361[/C][C]72.9742[/C][C]-0.138111[/C][C]0.213944[/C][/ROW]
[ROW][C]42[/C][C]73.02[/C][C]73.0421[/C][C]73.1258[/C][C]-0.0837778[/C][C]-0.0220556[/C][/ROW]
[ROW][C]43[/C][C]73.08[/C][C]73.2399[/C][C]73.2792[/C][C]-0.0392778[/C][C]-0.159889[/C][/ROW]
[ROW][C]44[/C][C]73.08[/C][C]73.3523[/C][C]73.4308[/C][C]-0.0785278[/C][C]-0.272306[/C][/ROW]
[ROW][C]45[/C][C]73.24[/C][C]73.4817[/C][C]73.5725[/C][C]-0.0907778[/C][C]-0.241722[/C][/ROW]
[ROW][C]46[/C][C]73.82[/C][C]73.6921[/C][C]73.7025[/C][C]-0.0104444[/C][C]0.127944[/C][/ROW]
[ROW][C]47[/C][C]74[/C][C]74.0606[/C][C]73.8308[/C][C]0.229806[/C][C]-0.0606389[/C][/ROW]
[ROW][C]48[/C][C]74.37[/C][C]74.3846[/C][C]73.9804[/C][C]0.404139[/C][C]-0.0145556[/C][/ROW]
[ROW][C]49[/C][C]74.38[/C][C]74.5618[/C][C]74.1537[/C][C]0.408056[/C][C]-0.181806[/C][/ROW]
[ROW][C]50[/C][C]74.38[/C][C]74.1349[/C][C]74.3296[/C][C]-0.194694[/C][C]0.245111[/C][/ROW]
[ROW][C]51[/C][C]74.36[/C][C]74.3137[/C][C]74.4996[/C][C]-0.185861[/C][C]0.0462778[/C][/ROW]
[ROW][C]52[/C][C]74.42[/C][C]74.4178[/C][C]74.6383[/C][C]-0.220528[/C][C]0.00219444[/C][/ROW]
[ROW][C]53[/C][C]74.59[/C][C]74.6344[/C][C]74.7725[/C][C]-0.138111[/C][C]-0.0443889[/C][/ROW]
[ROW][C]54[/C][C]75.07[/C][C]74.8312[/C][C]74.915[/C][C]-0.0837778[/C][C]0.238778[/C][/ROW]
[ROW][C]55[/C][C]75.19[/C][C]75.0086[/C][C]75.0479[/C][C]-0.0392778[/C][C]0.181361[/C][/ROW]
[ROW][C]56[/C][C]75.19[/C][C]74.9894[/C][C]75.0679[/C][C]-0.0785278[/C][C]0.200611[/C][/ROW]
[ROW][C]57[/C][C]75.21[/C][C]74.8821[/C][C]74.9729[/C][C]-0.0907778[/C][C]0.327861[/C][/ROW]
[ROW][C]58[/C][C]75.18[/C][C]74.8646[/C][C]74.875[/C][C]-0.0104444[/C][C]0.315444[/C][/ROW]
[ROW][C]59[/C][C]75.86[/C][C]74.9977[/C][C]74.7679[/C][C]0.229806[/C][C]0.862278[/C][/ROW]
[ROW][C]60[/C][C]75.93[/C][C]75.0446[/C][C]74.6404[/C][C]0.404139[/C][C]0.885444[/C][/ROW]
[ROW][C]61[/C][C]76.01[/C][C]74.9026[/C][C]74.4946[/C][C]0.408056[/C][C]1.10736[/C][/ROW]
[ROW][C]62[/C][C]73.23[/C][C]74.1545[/C][C]74.3492[/C][C]-0.194694[/C][C]-0.924472[/C][/ROW]
[ROW][C]63[/C][C]73.23[/C][C]74.0208[/C][C]74.2067[/C][C]-0.185861[/C][C]-0.790806[/C][/ROW]
[ROW][C]64[/C][C]73.2[/C][C]73.8474[/C][C]74.0679[/C][C]-0.220528[/C][C]-0.647389[/C][/ROW]
[ROW][C]65[/C][C]73.24[/C][C]73.7777[/C][C]73.9158[/C][C]-0.138111[/C][C]-0.537722[/C][/ROW]
[ROW][C]66[/C][C]73.36[/C][C]73.67[/C][C]73.7538[/C][C]-0.0837778[/C][C]-0.309972[/C][/ROW]
[ROW][C]67[/C][C]73.4[/C][C]73.557[/C][C]73.5963[/C][C]-0.0392778[/C][C]-0.156972[/C][/ROW]
[ROW][C]68[/C][C]73.49[/C][C]NA[/C][C]NA[/C][C]-0.0785278[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]73.49[/C][C]NA[/C][C]NA[/C][C]-0.0907778[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]73.57[/C][C]NA[/C][C]NA[/C][C]-0.0104444[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]73.82[/C][C]NA[/C][C]NA[/C][C]0.229806[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]74.08[/C][C]NA[/C][C]NA[/C][C]0.404139[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]74.08[/C][C]NA[/C][C]NA[/C][C]0.408056[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260852&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260852&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	70.38	NA	NA	0.408056	NA
2	70.38	NA	NA	-0.194694	NA
3	70.29	NA	NA	-0.185861	NA
4	70.42	NA	NA	-0.220528	NA
5	70.29	NA	NA	-0.138111	NA
6	70.59	NA	NA	-0.0837778	NA
7	70.64	70.5786	70.6179	-0.0392778	0.0613611
8	70.64	70.6036	70.6821	-0.0785278	0.0364444
9	70.68	70.6592	70.75	-0.0907778	0.0207778
10	70.78	70.8025	70.8129	-0.0104444	-0.0224722
11	70.9	71.1065	70.8767	0.229806	-0.206472
12	71.04	71.3446	70.9404	0.404139	-0.304556
13	71.15	71.4001	70.9921	0.408056	-0.250139
14	71.15	70.8466	71.0412	-0.194694	0.303444
15	71.15	70.9029	71.0888	-0.185861	0.247111
16	71.07	70.9103	71.1308	-0.220528	0.159694
17	71.17	71.0277	71.1658	-0.138111	0.142278
18	71.24	71.1179	71.2017	-0.0837778	0.122111
19	71.23	71.1978	71.2371	-0.0392778	0.0321944
20	71.23	71.1894	71.2679	-0.0785278	0.0406111
21	71.23	71.2113	71.3021	-0.0907778	0.0186944
22	71.24	71.3329	71.3433	-0.0104444	-0.0928889
23	71.28	71.6211	71.3912	0.229806	-0.341056
24	71.52	71.8383	71.4342	0.404139	-0.318306
25	71.52	71.886	71.4779	0.408056	-0.365972
26	71.52	71.3357	71.5304	-0.194694	0.184278
27	71.6	71.3954	71.5812	-0.185861	0.204611
28	71.61	71.4086	71.6292	-0.220528	0.201361
29	71.78	71.5536	71.6917	-0.138111	0.226444
30	71.66	71.6883	71.7721	-0.0837778	-0.0283056
31	71.86	71.8174	71.8567	-0.0392778	0.0426111
32	71.86	71.8648	71.9433	-0.0785278	-0.00480556
33	71.82	71.9451	72.0358	-0.0907778	-0.125056
34	71.8	72.1275	72.1379	-0.0104444	-0.327472
35	72.22	72.4736	72.2437	0.229806	-0.253556
36	72.51	72.7575	72.3533	0.404139	-0.247472
37	72.56	72.8689	72.4608	0.408056	-0.308889
38	72.56	72.3678	72.5625	-0.194694	0.192194
39	72.78	72.4866	72.6725	-0.185861	0.293361
40	72.88	72.5953	72.8158	-0.220528	0.284694
41	73.05	72.8361	72.9742	-0.138111	0.213944
42	73.02	73.0421	73.1258	-0.0837778	-0.0220556
43	73.08	73.2399	73.2792	-0.0392778	-0.159889
44	73.08	73.3523	73.4308	-0.0785278	-0.272306
45	73.24	73.4817	73.5725	-0.0907778	-0.241722
46	73.82	73.6921	73.7025	-0.0104444	0.127944
47	74	74.0606	73.8308	0.229806	-0.0606389
48	74.37	74.3846	73.9804	0.404139	-0.0145556
49	74.38	74.5618	74.1537	0.408056	-0.181806
50	74.38	74.1349	74.3296	-0.194694	0.245111
51	74.36	74.3137	74.4996	-0.185861	0.0462778
52	74.42	74.4178	74.6383	-0.220528	0.00219444
53	74.59	74.6344	74.7725	-0.138111	-0.0443889
54	75.07	74.8312	74.915	-0.0837778	0.238778
55	75.19	75.0086	75.0479	-0.0392778	0.181361
56	75.19	74.9894	75.0679	-0.0785278	0.200611
57	75.21	74.8821	74.9729	-0.0907778	0.327861
58	75.18	74.8646	74.875	-0.0104444	0.315444
59	75.86	74.9977	74.7679	0.229806	0.862278
60	75.93	75.0446	74.6404	0.404139	0.885444
61	76.01	74.9026	74.4946	0.408056	1.10736
62	73.23	74.1545	74.3492	-0.194694	-0.924472
63	73.23	74.0208	74.2067	-0.185861	-0.790806
64	73.2	73.8474	74.0679	-0.220528	-0.647389
65	73.24	73.7777	73.9158	-0.138111	-0.537722
66	73.36	73.67	73.7538	-0.0837778	-0.309972
67	73.4	73.557	73.5963	-0.0392778	-0.156972
68	73.49	NA	NA	-0.0785278	NA
69	73.49	NA	NA	-0.0907778	NA
70	73.57	NA	NA	-0.0104444	NA
71	73.82	NA	NA	0.229806	NA
72	74.08	NA	NA	0.404139	NA
73	74.08	NA	NA	0.408056	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