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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Wed, 27 May 2015 00:09:02 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/May/27/t14326823207q9i2dqq6ho31dh.htm/, Retrieved Sat, 04 May 2024 13:04:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279448, Retrieved Sat, 04 May 2024 13:04:34 +0000

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Estimated Impact

151

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-       [Classical Decomposition] [] [2015-05-26 23:09:02] [efb69546851bccb1c0576f78d5afa44b] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279448&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279448&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279448&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	75.6	NA	NA	-4.45749	NA
2	74	NA	NA	-2.27654	NA
3	75.3	NA	NA	1.5937	NA
4	83.1	NA	NA	3.95918	NA
5	84.9	NA	NA	2.78537	NA
6	83.5	NA	NA	3.06334	NA
7	88.2	85.8372	79.6833	6.15382	2.36285
8	87.4	83.0485	79.5833	3.46513	4.35154
9	77.8	79.7729	79.8208	-0.0479663	-1.97287
10	74.5	76.1354	80.0375	-3.90213	-1.63537
11	75.3	75.6532	80.0708	-4.41761	-0.353224
12	78.7	74.2854	80.2042	-5.9188	4.41463
13	71.4	76.0758	80.5333	-4.45749	-4.67584
14	75.8	78.4776	80.7542	-2.27654	-2.67763
15	79.2	83.102	81.5083	1.5937	-3.90203
16	84.4	87.2758	83.3167	3.95918	-2.87584
17	84.4	88.6479	85.8625	2.78537	-4.24787
18	87.2	91.5883	88.525	3.06334	-4.38834
19	92.4	97.5538	91.4	6.15382	-5.15382
20	88.5	98.2276	94.7625	3.46513	-9.72763
21	94.8	98.3604	98.4083	-0.0479663	-3.56037
22	100.9	98.4104	102.312	-3.90213	2.48963
23	110	102.432	106.85	-4.41761	7.56761
24	107.9	106.348	112.267	-5.9188	1.55213
25	111.2	113.363	117.821	-4.45749	-2.16334
26	116.7	120.286	122.562	-2.27654	-3.58596
27	125.8	127.29	125.696	1.5937	-1.48953
28	131.5	130.268	126.308	3.95918	1.23249
29	146.2	126.919	124.133	2.78537	19.2813
30	155.4	123.38	120.317	3.06334	32.02
31	157.5	122.141	115.987	6.15382	35.3587
32	137.2	114.744	111.279	3.46513	22.4557
33	121.3	105.998	106.046	-0.0479663	15.3021
34	89.1	96.6354	100.538	-3.90213	-7.53537
35	69.6	90.2907	94.7083	-4.41761	-20.6907
36	56.7	82.7979	88.7167	-5.9188	-26.0979
37	58.5	78.0967	82.5542	-4.45749	-19.5967
38	56.4	75.0318	77.3083	-2.27654	-18.6318
39	60.5	75.3395	73.7458	1.5937	-14.8395
40	64.6	76.2467	72.2875	3.95918	-11.6467
41	73.2	76.1979	73.4125	2.78537	-2.99787
42	84.6	79.0467	75.9833	3.06334	5.55332
43	80.4	85.2413	79.0875	6.15382	-4.84132
44	88.4	85.6693	82.2042	3.46513	2.7307
45	84.6	85.2604	85.3083	-0.0479663	-0.660367
46	90.8	84.6645	88.5667	-3.90213	6.13547
47	94.9	86.7657	91.1833	-4.41761	8.13428
48	93.1	86.602	92.5208	-5.9188	6.49797
49	96.6	89.0883	93.5458	-4.45749	7.51166
50	93.1	92.2526	94.5292	-2.27654	0.847371
51	98.3	97.0479	95.4542	1.5937	1.25213
52	105	100.543	96.5833	3.95918	4.45749
53	95.6	100.473	97.6875	2.78537	-4.87287
54	94.3	102.172	99.1083	3.06334	-7.87168
55	95.3	107.066	100.912	6.15382	-11.7663
56	97.1	106.59	103.125	3.46513	-9.49013
57	98.1	105.865	105.912	-0.0479663	-7.76453
58	104.4	105.065	108.967	-3.90213	-0.664534
59	107.8	107.699	112.117	-4.41761	0.100942
60	114.3	109.319	115.237	-5.9188	4.9813
61	118.7	113.888	118.346	-4.45749	4.81166
62	124.1	118.848	121.125	-2.27654	5.25154
63	134.2	125.09	123.496	1.5937	9.11047
64	142.4	129.388	125.429	3.95918	13.0117
65	133.8	129.76	126.975	2.78537	4.03963
66	131	131.259	128.196	3.06334	-0.259177
67	133.2	135.175	129.021	6.15382	-1.97465
68	125.9	133.29	129.825	3.46513	-7.39013
69	126.2	130.385	130.433	-0.0479663	-4.18537
70	122.7	126.373	130.275	-3.90213	-3.67287
71	126.6	125.099	129.517	-4.41761	1.50094
72	124.8	122.331	128.25	-5.9188	2.4688
73	128	122.247	126.704	-4.45749	5.75332
74	134.1	123.69	125.967	-2.27654	10.4099
75	138.8	127.502	125.908	1.5937	11.298
76	134	129.863	125.904	3.95918	4.13666
77	124	128.427	125.642	2.78537	-4.42703
78	110.4	128.288	125.225	3.06334	-17.8883
79	116.7	131.12	124.967	6.15382	-14.4205
80	124.7	128.065	124.6	3.46513	-3.36513
81	126	123.594	123.642	-0.0479663	2.4063
82	122.8	118.352	122.254	-3.90213	4.44797
83	120.2	116.895	121.312	-4.41761	3.30511
84	121.2	115.452	121.371	-5.9188	5.74797
85	125.4	117.476	121.933	-4.45749	7.92416
86	127.9	119.948	122.225	-2.27654	7.95154
87	122	123.865	122.271	1.5937	-1.86453
88	117.5	126.251	122.292	3.95918	-8.75084
89	117.9	125.11	122.325	2.78537	-7.21037
90	117.9	125.501	122.438	3.06334	-7.60084
91	122.7	NA	NA	6.15382	NA
92	125.7	NA	NA	3.46513	NA
93	126.1	NA	NA	-0.0479663	NA
94	123.2	NA	NA	-3.90213	NA
95	120.6	NA	NA	-4.41761	NA
96	123.5	NA	NA	-5.9188	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 75.6 & NA & NA & -4.45749 & NA \tabularnewline
2 & 74 & NA & NA & -2.27654 & NA \tabularnewline
3 & 75.3 & NA & NA & 1.5937 & NA \tabularnewline
4 & 83.1 & NA & NA & 3.95918 & NA \tabularnewline
5 & 84.9 & NA & NA & 2.78537 & NA \tabularnewline
6 & 83.5 & NA & NA & 3.06334 & NA \tabularnewline
7 & 88.2 & 85.8372 & 79.6833 & 6.15382 & 2.36285 \tabularnewline
8 & 87.4 & 83.0485 & 79.5833 & 3.46513 & 4.35154 \tabularnewline
9 & 77.8 & 79.7729 & 79.8208 & -0.0479663 & -1.97287 \tabularnewline
10 & 74.5 & 76.1354 & 80.0375 & -3.90213 & -1.63537 \tabularnewline
11 & 75.3 & 75.6532 & 80.0708 & -4.41761 & -0.353224 \tabularnewline
12 & 78.7 & 74.2854 & 80.2042 & -5.9188 & 4.41463 \tabularnewline
13 & 71.4 & 76.0758 & 80.5333 & -4.45749 & -4.67584 \tabularnewline
14 & 75.8 & 78.4776 & 80.7542 & -2.27654 & -2.67763 \tabularnewline
15 & 79.2 & 83.102 & 81.5083 & 1.5937 & -3.90203 \tabularnewline
16 & 84.4 & 87.2758 & 83.3167 & 3.95918 & -2.87584 \tabularnewline
17 & 84.4 & 88.6479 & 85.8625 & 2.78537 & -4.24787 \tabularnewline
18 & 87.2 & 91.5883 & 88.525 & 3.06334 & -4.38834 \tabularnewline
19 & 92.4 & 97.5538 & 91.4 & 6.15382 & -5.15382 \tabularnewline
20 & 88.5 & 98.2276 & 94.7625 & 3.46513 & -9.72763 \tabularnewline
21 & 94.8 & 98.3604 & 98.4083 & -0.0479663 & -3.56037 \tabularnewline
22 & 100.9 & 98.4104 & 102.312 & -3.90213 & 2.48963 \tabularnewline
23 & 110 & 102.432 & 106.85 & -4.41761 & 7.56761 \tabularnewline
24 & 107.9 & 106.348 & 112.267 & -5.9188 & 1.55213 \tabularnewline
25 & 111.2 & 113.363 & 117.821 & -4.45749 & -2.16334 \tabularnewline
26 & 116.7 & 120.286 & 122.562 & -2.27654 & -3.58596 \tabularnewline
27 & 125.8 & 127.29 & 125.696 & 1.5937 & -1.48953 \tabularnewline
28 & 131.5 & 130.268 & 126.308 & 3.95918 & 1.23249 \tabularnewline
29 & 146.2 & 126.919 & 124.133 & 2.78537 & 19.2813 \tabularnewline
30 & 155.4 & 123.38 & 120.317 & 3.06334 & 32.02 \tabularnewline
31 & 157.5 & 122.141 & 115.987 & 6.15382 & 35.3587 \tabularnewline
32 & 137.2 & 114.744 & 111.279 & 3.46513 & 22.4557 \tabularnewline
33 & 121.3 & 105.998 & 106.046 & -0.0479663 & 15.3021 \tabularnewline
34 & 89.1 & 96.6354 & 100.538 & -3.90213 & -7.53537 \tabularnewline
35 & 69.6 & 90.2907 & 94.7083 & -4.41761 & -20.6907 \tabularnewline
36 & 56.7 & 82.7979 & 88.7167 & -5.9188 & -26.0979 \tabularnewline
37 & 58.5 & 78.0967 & 82.5542 & -4.45749 & -19.5967 \tabularnewline
38 & 56.4 & 75.0318 & 77.3083 & -2.27654 & -18.6318 \tabularnewline
39 & 60.5 & 75.3395 & 73.7458 & 1.5937 & -14.8395 \tabularnewline
40 & 64.6 & 76.2467 & 72.2875 & 3.95918 & -11.6467 \tabularnewline
41 & 73.2 & 76.1979 & 73.4125 & 2.78537 & -2.99787 \tabularnewline
42 & 84.6 & 79.0467 & 75.9833 & 3.06334 & 5.55332 \tabularnewline
43 & 80.4 & 85.2413 & 79.0875 & 6.15382 & -4.84132 \tabularnewline
44 & 88.4 & 85.6693 & 82.2042 & 3.46513 & 2.7307 \tabularnewline
45 & 84.6 & 85.2604 & 85.3083 & -0.0479663 & -0.660367 \tabularnewline
46 & 90.8 & 84.6645 & 88.5667 & -3.90213 & 6.13547 \tabularnewline
47 & 94.9 & 86.7657 & 91.1833 & -4.41761 & 8.13428 \tabularnewline
48 & 93.1 & 86.602 & 92.5208 & -5.9188 & 6.49797 \tabularnewline
49 & 96.6 & 89.0883 & 93.5458 & -4.45749 & 7.51166 \tabularnewline
50 & 93.1 & 92.2526 & 94.5292 & -2.27654 & 0.847371 \tabularnewline
51 & 98.3 & 97.0479 & 95.4542 & 1.5937 & 1.25213 \tabularnewline
52 & 105 & 100.543 & 96.5833 & 3.95918 & 4.45749 \tabularnewline
53 & 95.6 & 100.473 & 97.6875 & 2.78537 & -4.87287 \tabularnewline
54 & 94.3 & 102.172 & 99.1083 & 3.06334 & -7.87168 \tabularnewline
55 & 95.3 & 107.066 & 100.912 & 6.15382 & -11.7663 \tabularnewline
56 & 97.1 & 106.59 & 103.125 & 3.46513 & -9.49013 \tabularnewline
57 & 98.1 & 105.865 & 105.912 & -0.0479663 & -7.76453 \tabularnewline
58 & 104.4 & 105.065 & 108.967 & -3.90213 & -0.664534 \tabularnewline
59 & 107.8 & 107.699 & 112.117 & -4.41761 & 0.100942 \tabularnewline
60 & 114.3 & 109.319 & 115.237 & -5.9188 & 4.9813 \tabularnewline
61 & 118.7 & 113.888 & 118.346 & -4.45749 & 4.81166 \tabularnewline
62 & 124.1 & 118.848 & 121.125 & -2.27654 & 5.25154 \tabularnewline
63 & 134.2 & 125.09 & 123.496 & 1.5937 & 9.11047 \tabularnewline
64 & 142.4 & 129.388 & 125.429 & 3.95918 & 13.0117 \tabularnewline
65 & 133.8 & 129.76 & 126.975 & 2.78537 & 4.03963 \tabularnewline
66 & 131 & 131.259 & 128.196 & 3.06334 & -0.259177 \tabularnewline
67 & 133.2 & 135.175 & 129.021 & 6.15382 & -1.97465 \tabularnewline
68 & 125.9 & 133.29 & 129.825 & 3.46513 & -7.39013 \tabularnewline
69 & 126.2 & 130.385 & 130.433 & -0.0479663 & -4.18537 \tabularnewline
70 & 122.7 & 126.373 & 130.275 & -3.90213 & -3.67287 \tabularnewline
71 & 126.6 & 125.099 & 129.517 & -4.41761 & 1.50094 \tabularnewline
72 & 124.8 & 122.331 & 128.25 & -5.9188 & 2.4688 \tabularnewline
73 & 128 & 122.247 & 126.704 & -4.45749 & 5.75332 \tabularnewline
74 & 134.1 & 123.69 & 125.967 & -2.27654 & 10.4099 \tabularnewline
75 & 138.8 & 127.502 & 125.908 & 1.5937 & 11.298 \tabularnewline
76 & 134 & 129.863 & 125.904 & 3.95918 & 4.13666 \tabularnewline
77 & 124 & 128.427 & 125.642 & 2.78537 & -4.42703 \tabularnewline
78 & 110.4 & 128.288 & 125.225 & 3.06334 & -17.8883 \tabularnewline
79 & 116.7 & 131.12 & 124.967 & 6.15382 & -14.4205 \tabularnewline
80 & 124.7 & 128.065 & 124.6 & 3.46513 & -3.36513 \tabularnewline
81 & 126 & 123.594 & 123.642 & -0.0479663 & 2.4063 \tabularnewline
82 & 122.8 & 118.352 & 122.254 & -3.90213 & 4.44797 \tabularnewline
83 & 120.2 & 116.895 & 121.312 & -4.41761 & 3.30511 \tabularnewline
84 & 121.2 & 115.452 & 121.371 & -5.9188 & 5.74797 \tabularnewline
85 & 125.4 & 117.476 & 121.933 & -4.45749 & 7.92416 \tabularnewline
86 & 127.9 & 119.948 & 122.225 & -2.27654 & 7.95154 \tabularnewline
87 & 122 & 123.865 & 122.271 & 1.5937 & -1.86453 \tabularnewline
88 & 117.5 & 126.251 & 122.292 & 3.95918 & -8.75084 \tabularnewline
89 & 117.9 & 125.11 & 122.325 & 2.78537 & -7.21037 \tabularnewline
90 & 117.9 & 125.501 & 122.438 & 3.06334 & -7.60084 \tabularnewline
91 & 122.7 & NA & NA & 6.15382 & NA \tabularnewline
92 & 125.7 & NA & NA & 3.46513 & NA \tabularnewline
93 & 126.1 & NA & NA & -0.0479663 & NA \tabularnewline
94 & 123.2 & NA & NA & -3.90213 & NA \tabularnewline
95 & 120.6 & NA & NA & -4.41761 & NA \tabularnewline
96 & 123.5 & NA & NA & -5.9188 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279448&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]75.6[/C][C]NA[/C][C]NA[/C][C]-4.45749[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]74[/C][C]NA[/C][C]NA[/C][C]-2.27654[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]75.3[/C][C]NA[/C][C]NA[/C][C]1.5937[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]83.1[/C][C]NA[/C][C]NA[/C][C]3.95918[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]84.9[/C][C]NA[/C][C]NA[/C][C]2.78537[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]83.5[/C][C]NA[/C][C]NA[/C][C]3.06334[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]88.2[/C][C]85.8372[/C][C]79.6833[/C][C]6.15382[/C][C]2.36285[/C][/ROW]
[ROW][C]8[/C][C]87.4[/C][C]83.0485[/C][C]79.5833[/C][C]3.46513[/C][C]4.35154[/C][/ROW]
[ROW][C]9[/C][C]77.8[/C][C]79.7729[/C][C]79.8208[/C][C]-0.0479663[/C][C]-1.97287[/C][/ROW]
[ROW][C]10[/C][C]74.5[/C][C]76.1354[/C][C]80.0375[/C][C]-3.90213[/C][C]-1.63537[/C][/ROW]
[ROW][C]11[/C][C]75.3[/C][C]75.6532[/C][C]80.0708[/C][C]-4.41761[/C][C]-0.353224[/C][/ROW]
[ROW][C]12[/C][C]78.7[/C][C]74.2854[/C][C]80.2042[/C][C]-5.9188[/C][C]4.41463[/C][/ROW]
[ROW][C]13[/C][C]71.4[/C][C]76.0758[/C][C]80.5333[/C][C]-4.45749[/C][C]-4.67584[/C][/ROW]
[ROW][C]14[/C][C]75.8[/C][C]78.4776[/C][C]80.7542[/C][C]-2.27654[/C][C]-2.67763[/C][/ROW]
[ROW][C]15[/C][C]79.2[/C][C]83.102[/C][C]81.5083[/C][C]1.5937[/C][C]-3.90203[/C][/ROW]
[ROW][C]16[/C][C]84.4[/C][C]87.2758[/C][C]83.3167[/C][C]3.95918[/C][C]-2.87584[/C][/ROW]
[ROW][C]17[/C][C]84.4[/C][C]88.6479[/C][C]85.8625[/C][C]2.78537[/C][C]-4.24787[/C][/ROW]
[ROW][C]18[/C][C]87.2[/C][C]91.5883[/C][C]88.525[/C][C]3.06334[/C][C]-4.38834[/C][/ROW]
[ROW][C]19[/C][C]92.4[/C][C]97.5538[/C][C]91.4[/C][C]6.15382[/C][C]-5.15382[/C][/ROW]
[ROW][C]20[/C][C]88.5[/C][C]98.2276[/C][C]94.7625[/C][C]3.46513[/C][C]-9.72763[/C][/ROW]
[ROW][C]21[/C][C]94.8[/C][C]98.3604[/C][C]98.4083[/C][C]-0.0479663[/C][C]-3.56037[/C][/ROW]
[ROW][C]22[/C][C]100.9[/C][C]98.4104[/C][C]102.312[/C][C]-3.90213[/C][C]2.48963[/C][/ROW]
[ROW][C]23[/C][C]110[/C][C]102.432[/C][C]106.85[/C][C]-4.41761[/C][C]7.56761[/C][/ROW]
[ROW][C]24[/C][C]107.9[/C][C]106.348[/C][C]112.267[/C][C]-5.9188[/C][C]1.55213[/C][/ROW]
[ROW][C]25[/C][C]111.2[/C][C]113.363[/C][C]117.821[/C][C]-4.45749[/C][C]-2.16334[/C][/ROW]
[ROW][C]26[/C][C]116.7[/C][C]120.286[/C][C]122.562[/C][C]-2.27654[/C][C]-3.58596[/C][/ROW]
[ROW][C]27[/C][C]125.8[/C][C]127.29[/C][C]125.696[/C][C]1.5937[/C][C]-1.48953[/C][/ROW]
[ROW][C]28[/C][C]131.5[/C][C]130.268[/C][C]126.308[/C][C]3.95918[/C][C]1.23249[/C][/ROW]
[ROW][C]29[/C][C]146.2[/C][C]126.919[/C][C]124.133[/C][C]2.78537[/C][C]19.2813[/C][/ROW]
[ROW][C]30[/C][C]155.4[/C][C]123.38[/C][C]120.317[/C][C]3.06334[/C][C]32.02[/C][/ROW]
[ROW][C]31[/C][C]157.5[/C][C]122.141[/C][C]115.987[/C][C]6.15382[/C][C]35.3587[/C][/ROW]
[ROW][C]32[/C][C]137.2[/C][C]114.744[/C][C]111.279[/C][C]3.46513[/C][C]22.4557[/C][/ROW]
[ROW][C]33[/C][C]121.3[/C][C]105.998[/C][C]106.046[/C][C]-0.0479663[/C][C]15.3021[/C][/ROW]
[ROW][C]34[/C][C]89.1[/C][C]96.6354[/C][C]100.538[/C][C]-3.90213[/C][C]-7.53537[/C][/ROW]
[ROW][C]35[/C][C]69.6[/C][C]90.2907[/C][C]94.7083[/C][C]-4.41761[/C][C]-20.6907[/C][/ROW]
[ROW][C]36[/C][C]56.7[/C][C]82.7979[/C][C]88.7167[/C][C]-5.9188[/C][C]-26.0979[/C][/ROW]
[ROW][C]37[/C][C]58.5[/C][C]78.0967[/C][C]82.5542[/C][C]-4.45749[/C][C]-19.5967[/C][/ROW]
[ROW][C]38[/C][C]56.4[/C][C]75.0318[/C][C]77.3083[/C][C]-2.27654[/C][C]-18.6318[/C][/ROW]
[ROW][C]39[/C][C]60.5[/C][C]75.3395[/C][C]73.7458[/C][C]1.5937[/C][C]-14.8395[/C][/ROW]
[ROW][C]40[/C][C]64.6[/C][C]76.2467[/C][C]72.2875[/C][C]3.95918[/C][C]-11.6467[/C][/ROW]
[ROW][C]41[/C][C]73.2[/C][C]76.1979[/C][C]73.4125[/C][C]2.78537[/C][C]-2.99787[/C][/ROW]
[ROW][C]42[/C][C]84.6[/C][C]79.0467[/C][C]75.9833[/C][C]3.06334[/C][C]5.55332[/C][/ROW]
[ROW][C]43[/C][C]80.4[/C][C]85.2413[/C][C]79.0875[/C][C]6.15382[/C][C]-4.84132[/C][/ROW]
[ROW][C]44[/C][C]88.4[/C][C]85.6693[/C][C]82.2042[/C][C]3.46513[/C][C]2.7307[/C][/ROW]
[ROW][C]45[/C][C]84.6[/C][C]85.2604[/C][C]85.3083[/C][C]-0.0479663[/C][C]-0.660367[/C][/ROW]
[ROW][C]46[/C][C]90.8[/C][C]84.6645[/C][C]88.5667[/C][C]-3.90213[/C][C]6.13547[/C][/ROW]
[ROW][C]47[/C][C]94.9[/C][C]86.7657[/C][C]91.1833[/C][C]-4.41761[/C][C]8.13428[/C][/ROW]
[ROW][C]48[/C][C]93.1[/C][C]86.602[/C][C]92.5208[/C][C]-5.9188[/C][C]6.49797[/C][/ROW]
[ROW][C]49[/C][C]96.6[/C][C]89.0883[/C][C]93.5458[/C][C]-4.45749[/C][C]7.51166[/C][/ROW]
[ROW][C]50[/C][C]93.1[/C][C]92.2526[/C][C]94.5292[/C][C]-2.27654[/C][C]0.847371[/C][/ROW]
[ROW][C]51[/C][C]98.3[/C][C]97.0479[/C][C]95.4542[/C][C]1.5937[/C][C]1.25213[/C][/ROW]
[ROW][C]52[/C][C]105[/C][C]100.543[/C][C]96.5833[/C][C]3.95918[/C][C]4.45749[/C][/ROW]
[ROW][C]53[/C][C]95.6[/C][C]100.473[/C][C]97.6875[/C][C]2.78537[/C][C]-4.87287[/C][/ROW]
[ROW][C]54[/C][C]94.3[/C][C]102.172[/C][C]99.1083[/C][C]3.06334[/C][C]-7.87168[/C][/ROW]
[ROW][C]55[/C][C]95.3[/C][C]107.066[/C][C]100.912[/C][C]6.15382[/C][C]-11.7663[/C][/ROW]
[ROW][C]56[/C][C]97.1[/C][C]106.59[/C][C]103.125[/C][C]3.46513[/C][C]-9.49013[/C][/ROW]
[ROW][C]57[/C][C]98.1[/C][C]105.865[/C][C]105.912[/C][C]-0.0479663[/C][C]-7.76453[/C][/ROW]
[ROW][C]58[/C][C]104.4[/C][C]105.065[/C][C]108.967[/C][C]-3.90213[/C][C]-0.664534[/C][/ROW]
[ROW][C]59[/C][C]107.8[/C][C]107.699[/C][C]112.117[/C][C]-4.41761[/C][C]0.100942[/C][/ROW]
[ROW][C]60[/C][C]114.3[/C][C]109.319[/C][C]115.237[/C][C]-5.9188[/C][C]4.9813[/C][/ROW]
[ROW][C]61[/C][C]118.7[/C][C]113.888[/C][C]118.346[/C][C]-4.45749[/C][C]4.81166[/C][/ROW]
[ROW][C]62[/C][C]124.1[/C][C]118.848[/C][C]121.125[/C][C]-2.27654[/C][C]5.25154[/C][/ROW]
[ROW][C]63[/C][C]134.2[/C][C]125.09[/C][C]123.496[/C][C]1.5937[/C][C]9.11047[/C][/ROW]
[ROW][C]64[/C][C]142.4[/C][C]129.388[/C][C]125.429[/C][C]3.95918[/C][C]13.0117[/C][/ROW]
[ROW][C]65[/C][C]133.8[/C][C]129.76[/C][C]126.975[/C][C]2.78537[/C][C]4.03963[/C][/ROW]
[ROW][C]66[/C][C]131[/C][C]131.259[/C][C]128.196[/C][C]3.06334[/C][C]-0.259177[/C][/ROW]
[ROW][C]67[/C][C]133.2[/C][C]135.175[/C][C]129.021[/C][C]6.15382[/C][C]-1.97465[/C][/ROW]
[ROW][C]68[/C][C]125.9[/C][C]133.29[/C][C]129.825[/C][C]3.46513[/C][C]-7.39013[/C][/ROW]
[ROW][C]69[/C][C]126.2[/C][C]130.385[/C][C]130.433[/C][C]-0.0479663[/C][C]-4.18537[/C][/ROW]
[ROW][C]70[/C][C]122.7[/C][C]126.373[/C][C]130.275[/C][C]-3.90213[/C][C]-3.67287[/C][/ROW]
[ROW][C]71[/C][C]126.6[/C][C]125.099[/C][C]129.517[/C][C]-4.41761[/C][C]1.50094[/C][/ROW]
[ROW][C]72[/C][C]124.8[/C][C]122.331[/C][C]128.25[/C][C]-5.9188[/C][C]2.4688[/C][/ROW]
[ROW][C]73[/C][C]128[/C][C]122.247[/C][C]126.704[/C][C]-4.45749[/C][C]5.75332[/C][/ROW]
[ROW][C]74[/C][C]134.1[/C][C]123.69[/C][C]125.967[/C][C]-2.27654[/C][C]10.4099[/C][/ROW]
[ROW][C]75[/C][C]138.8[/C][C]127.502[/C][C]125.908[/C][C]1.5937[/C][C]11.298[/C][/ROW]
[ROW][C]76[/C][C]134[/C][C]129.863[/C][C]125.904[/C][C]3.95918[/C][C]4.13666[/C][/ROW]
[ROW][C]77[/C][C]124[/C][C]128.427[/C][C]125.642[/C][C]2.78537[/C][C]-4.42703[/C][/ROW]
[ROW][C]78[/C][C]110.4[/C][C]128.288[/C][C]125.225[/C][C]3.06334[/C][C]-17.8883[/C][/ROW]
[ROW][C]79[/C][C]116.7[/C][C]131.12[/C][C]124.967[/C][C]6.15382[/C][C]-14.4205[/C][/ROW]
[ROW][C]80[/C][C]124.7[/C][C]128.065[/C][C]124.6[/C][C]3.46513[/C][C]-3.36513[/C][/ROW]
[ROW][C]81[/C][C]126[/C][C]123.594[/C][C]123.642[/C][C]-0.0479663[/C][C]2.4063[/C][/ROW]
[ROW][C]82[/C][C]122.8[/C][C]118.352[/C][C]122.254[/C][C]-3.90213[/C][C]4.44797[/C][/ROW]
[ROW][C]83[/C][C]120.2[/C][C]116.895[/C][C]121.312[/C][C]-4.41761[/C][C]3.30511[/C][/ROW]
[ROW][C]84[/C][C]121.2[/C][C]115.452[/C][C]121.371[/C][C]-5.9188[/C][C]5.74797[/C][/ROW]
[ROW][C]85[/C][C]125.4[/C][C]117.476[/C][C]121.933[/C][C]-4.45749[/C][C]7.92416[/C][/ROW]
[ROW][C]86[/C][C]127.9[/C][C]119.948[/C][C]122.225[/C][C]-2.27654[/C][C]7.95154[/C][/ROW]
[ROW][C]87[/C][C]122[/C][C]123.865[/C][C]122.271[/C][C]1.5937[/C][C]-1.86453[/C][/ROW]
[ROW][C]88[/C][C]117.5[/C][C]126.251[/C][C]122.292[/C][C]3.95918[/C][C]-8.75084[/C][/ROW]
[ROW][C]89[/C][C]117.9[/C][C]125.11[/C][C]122.325[/C][C]2.78537[/C][C]-7.21037[/C][/ROW]
[ROW][C]90[/C][C]117.9[/C][C]125.501[/C][C]122.438[/C][C]3.06334[/C][C]-7.60084[/C][/ROW]
[ROW][C]91[/C][C]122.7[/C][C]NA[/C][C]NA[/C][C]6.15382[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]125.7[/C][C]NA[/C][C]NA[/C][C]3.46513[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]126.1[/C][C]NA[/C][C]NA[/C][C]-0.0479663[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]123.2[/C][C]NA[/C][C]NA[/C][C]-3.90213[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]120.6[/C][C]NA[/C][C]NA[/C][C]-4.41761[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]123.5[/C][C]NA[/C][C]NA[/C][C]-5.9188[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279448&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279448&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	75.6	NA	NA	-4.45749	NA
2	74	NA	NA	-2.27654	NA
3	75.3	NA	NA	1.5937	NA
4	83.1	NA	NA	3.95918	NA
5	84.9	NA	NA	2.78537	NA
6	83.5	NA	NA	3.06334	NA
7	88.2	85.8372	79.6833	6.15382	2.36285
8	87.4	83.0485	79.5833	3.46513	4.35154
9	77.8	79.7729	79.8208	-0.0479663	-1.97287
10	74.5	76.1354	80.0375	-3.90213	-1.63537
11	75.3	75.6532	80.0708	-4.41761	-0.353224
12	78.7	74.2854	80.2042	-5.9188	4.41463
13	71.4	76.0758	80.5333	-4.45749	-4.67584
14	75.8	78.4776	80.7542	-2.27654	-2.67763
15	79.2	83.102	81.5083	1.5937	-3.90203
16	84.4	87.2758	83.3167	3.95918	-2.87584
17	84.4	88.6479	85.8625	2.78537	-4.24787
18	87.2	91.5883	88.525	3.06334	-4.38834
19	92.4	97.5538	91.4	6.15382	-5.15382
20	88.5	98.2276	94.7625	3.46513	-9.72763
21	94.8	98.3604	98.4083	-0.0479663	-3.56037
22	100.9	98.4104	102.312	-3.90213	2.48963
23	110	102.432	106.85	-4.41761	7.56761
24	107.9	106.348	112.267	-5.9188	1.55213
25	111.2	113.363	117.821	-4.45749	-2.16334
26	116.7	120.286	122.562	-2.27654	-3.58596
27	125.8	127.29	125.696	1.5937	-1.48953
28	131.5	130.268	126.308	3.95918	1.23249
29	146.2	126.919	124.133	2.78537	19.2813
30	155.4	123.38	120.317	3.06334	32.02
31	157.5	122.141	115.987	6.15382	35.3587
32	137.2	114.744	111.279	3.46513	22.4557
33	121.3	105.998	106.046	-0.0479663	15.3021
34	89.1	96.6354	100.538	-3.90213	-7.53537
35	69.6	90.2907	94.7083	-4.41761	-20.6907
36	56.7	82.7979	88.7167	-5.9188	-26.0979
37	58.5	78.0967	82.5542	-4.45749	-19.5967
38	56.4	75.0318	77.3083	-2.27654	-18.6318
39	60.5	75.3395	73.7458	1.5937	-14.8395
40	64.6	76.2467	72.2875	3.95918	-11.6467
41	73.2	76.1979	73.4125	2.78537	-2.99787
42	84.6	79.0467	75.9833	3.06334	5.55332
43	80.4	85.2413	79.0875	6.15382	-4.84132
44	88.4	85.6693	82.2042	3.46513	2.7307
45	84.6	85.2604	85.3083	-0.0479663	-0.660367
46	90.8	84.6645	88.5667	-3.90213	6.13547
47	94.9	86.7657	91.1833	-4.41761	8.13428
48	93.1	86.602	92.5208	-5.9188	6.49797
49	96.6	89.0883	93.5458	-4.45749	7.51166
50	93.1	92.2526	94.5292	-2.27654	0.847371
51	98.3	97.0479	95.4542	1.5937	1.25213
52	105	100.543	96.5833	3.95918	4.45749
53	95.6	100.473	97.6875	2.78537	-4.87287
54	94.3	102.172	99.1083	3.06334	-7.87168
55	95.3	107.066	100.912	6.15382	-11.7663
56	97.1	106.59	103.125	3.46513	-9.49013
57	98.1	105.865	105.912	-0.0479663	-7.76453
58	104.4	105.065	108.967	-3.90213	-0.664534
59	107.8	107.699	112.117	-4.41761	0.100942
60	114.3	109.319	115.237	-5.9188	4.9813
61	118.7	113.888	118.346	-4.45749	4.81166
62	124.1	118.848	121.125	-2.27654	5.25154
63	134.2	125.09	123.496	1.5937	9.11047
64	142.4	129.388	125.429	3.95918	13.0117
65	133.8	129.76	126.975	2.78537	4.03963
66	131	131.259	128.196	3.06334	-0.259177
67	133.2	135.175	129.021	6.15382	-1.97465
68	125.9	133.29	129.825	3.46513	-7.39013
69	126.2	130.385	130.433	-0.0479663	-4.18537
70	122.7	126.373	130.275	-3.90213	-3.67287
71	126.6	125.099	129.517	-4.41761	1.50094
72	124.8	122.331	128.25	-5.9188	2.4688
73	128	122.247	126.704	-4.45749	5.75332
74	134.1	123.69	125.967	-2.27654	10.4099
75	138.8	127.502	125.908	1.5937	11.298
76	134	129.863	125.904	3.95918	4.13666
77	124	128.427	125.642	2.78537	-4.42703
78	110.4	128.288	125.225	3.06334	-17.8883
79	116.7	131.12	124.967	6.15382	-14.4205
80	124.7	128.065	124.6	3.46513	-3.36513
81	126	123.594	123.642	-0.0479663	2.4063
82	122.8	118.352	122.254	-3.90213	4.44797
83	120.2	116.895	121.312	-4.41761	3.30511
84	121.2	115.452	121.371	-5.9188	5.74797
85	125.4	117.476	121.933	-4.45749	7.92416
86	127.9	119.948	122.225	-2.27654	7.95154
87	122	123.865	122.271	1.5937	-1.86453
88	117.5	126.251	122.292	3.95918	-8.75084
89	117.9	125.11	122.325	2.78537	-7.21037
90	117.9	125.501	122.438	3.06334	-7.60084
91	122.7	NA	NA	6.15382	NA
92	125.7	NA	NA	3.46513	NA
93	126.1	NA	NA	-0.0479663	NA
94	123.2	NA	NA	-3.90213	NA
95	120.6	NA	NA	-4.41761	NA
96	123.5	NA	NA	-5.9188	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