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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 13 Jan 2014 05:08:18 -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/2014/Jan/13/t1389607713f3ws9h53d2zmfm6.htm/, Retrieved Sun, 19 May 2024 09:21:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=233131, Retrieved Sun, 19 May 2024 09:21:15 +0000

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Estimated Impact

138

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-       [Classical Decomposition] [] [2014-01-13 10:08:18] [ffc6217b42a6800413892efb2ef7f057] [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	7 seconds
R Server	'Herman Ole Andreas Wold' @ wold.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 & 7 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233131&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233131&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	7 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	59.8	NA	NA	1.66435	NA
2	60.7	NA	NA	2.8581	NA
3	59.7	NA	NA	1.11713	NA
4	60.2	NA	NA	0.383102	NA
5	61.3	NA	NA	0.380324	NA
6	59.8	NA	NA	1.91782	NA
7	61.2	63.6081	62.2583	1.34977	-2.4081
8	59.3	63.1025	63.1875	-0.0849537	-3.80255
9	59.4	63.4102	64.2	-0.789815	-4.01019
10	63.1	61.206	65.1125	-3.90648	1.89398
11	68	62.7387	65.9333	-3.19468	5.26134
12	69.4	65.3262	67.0208	-1.69468	4.07384
13	70.2	69.9644	68.3	1.66435	0.235648
14	72.6	72.4873	69.6292	2.8581	0.112731
15	72.1	72.4755	71.3583	1.11713	-0.375463
16	69.7	73.7206	73.3375	0.383102	-4.0206
17	71.5	75.5345	75.1542	0.380324	-4.03449
18	75.7	79.0303	77.1125	1.91782	-3.33032
19	76	80.9373	79.5875	1.34977	-4.93727
20	76.4	82.5775	82.6625	-0.0849537	-6.17755
21	83.8	85.3935	86.1833	-0.789815	-1.59352
22	86.2	85.9019	89.8083	-3.90648	0.298148
23	88.5	90.1387	93.3333	-3.19468	-1.63866
24	95.9	95.2803	96.975	-1.69468	0.619676
25	103.1	102.41	100.746	1.66435	0.689815
26	113.5	106.796	103.938	2.8581	6.7044
27	115.7	107.192	106.075	1.11713	8.50787
28	113.1	107.133	106.75	0.383102	5.9669
29	112.7	106.634	106.254	0.380324	6.06551
30	121.9	107.039	105.121	1.91782	14.8613
31	120.3	104.991	103.642	1.34977	15.3086
32	108.7	101.569	101.654	-0.0849537	7.13079
33	102.8	98.1977	98.9875	-0.789815	4.60231
34	83.4	92.5852	96.4917	-3.90648	-9.18519
35	79.4	91.497	94.6917	-3.19468	-12.097
36	77.8	91.2887	92.9833	-1.69468	-13.4887
37	85.7	92.356	90.6917	1.66435	-6.65602
38	83.2	91.5414	88.6833	2.8581	-8.34144
39	82	88.4171	87.3	1.11713	-6.41713
40	86.9	87.3331	86.95	0.383102	-0.433102
41	95.7	88.247	87.8667	0.380324	7.45301
42	97.9	91.1762	89.2583	1.91782	6.72384
43	89.3	91.8164	90.4667	1.34977	-2.51644
44	91.5	91.14	91.225	-0.0849537	0.359954
45	86.8	91.056	91.8458	-0.789815	-4.25602
46	91	88.2727	92.1792	-3.90648	2.72731
47	93.8	88.7053	91.9	-3.19468	5.09468
48	96.8	89.522	91.2167	-1.69468	7.27801
49	95.7	92.7935	91.1292	1.66435	2.90648
50	91.4	94.6248	91.7667	2.8581	-3.22477
51	88.7	94.0713	92.9542	1.11713	-5.3713
52	88.2	95.0248	94.6417	0.383102	-6.82477
53	87.7	96.8928	96.5125	0.380324	-9.19282
54	89.5	100.601	98.6833	1.91782	-11.1012
55	95.6	102.737	101.387	1.34977	-7.13727
56	100.5	104.778	104.862	-0.0849537	-4.27755
57	106.3	107.935	108.725	-0.789815	-1.63519
58	112	108.756	112.662	-3.90648	3.24398
59	117.7	113.43	116.625	-3.19468	4.26968
60	125	118.626	120.321	-1.69468	6.37384
61	132.4	125.164	123.5	1.66435	7.23565
62	138.1	129.091	126.233	2.8581	9.00856
63	134.7	129.638	128.521	1.11713	5.06204
64	136.7	130.191	129.808	0.383102	6.50856
65	134.3	130.455	130.075	0.380324	3.84468
66	131.6	131.443	129.525	1.91782	0.157176
67	129.8	129.683	128.333	1.34977	0.116898
68	131.9	126.707	126.792	-0.0849537	5.19329
69	129.8	124.481	125.271	-0.789815	5.31898
70	119.4	119.952	123.858	-3.90648	-0.551852
71	116.7	119.164	122.358	-3.19468	-2.46366
72	112.8	119.23	120.925	-1.69468	-6.43032
73	116	121.985	120.321	1.66435	-5.98519
74	117.5	123.333	120.475	2.8581	-5.8331
75	118.8	121.78	120.663	1.11713	-2.97963
76	118.7	121.471	121.088	0.383102	-2.7706
77	116.3	122.009	121.629	0.380324	-5.70949
78	115.2	124.084	122.167	1.91782	-8.88449
79	131.7	NA	NA	1.34977	NA
80	133.7	NA	NA	-0.0849537	NA
81	132.5	NA	NA	-0.789815	NA
82	126.9	NA	NA	-3.90648	NA
83	122.2	NA	NA	-3.19468	NA
84	120.2	NA	NA	-1.69468	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 59.8 & NA & NA & 1.66435 & NA \tabularnewline
2 & 60.7 & NA & NA & 2.8581 & NA \tabularnewline
3 & 59.7 & NA & NA & 1.11713 & NA \tabularnewline
4 & 60.2 & NA & NA & 0.383102 & NA \tabularnewline
5 & 61.3 & NA & NA & 0.380324 & NA \tabularnewline
6 & 59.8 & NA & NA & 1.91782 & NA \tabularnewline
7 & 61.2 & 63.6081 & 62.2583 & 1.34977 & -2.4081 \tabularnewline
8 & 59.3 & 63.1025 & 63.1875 & -0.0849537 & -3.80255 \tabularnewline
9 & 59.4 & 63.4102 & 64.2 & -0.789815 & -4.01019 \tabularnewline
10 & 63.1 & 61.206 & 65.1125 & -3.90648 & 1.89398 \tabularnewline
11 & 68 & 62.7387 & 65.9333 & -3.19468 & 5.26134 \tabularnewline
12 & 69.4 & 65.3262 & 67.0208 & -1.69468 & 4.07384 \tabularnewline
13 & 70.2 & 69.9644 & 68.3 & 1.66435 & 0.235648 \tabularnewline
14 & 72.6 & 72.4873 & 69.6292 & 2.8581 & 0.112731 \tabularnewline
15 & 72.1 & 72.4755 & 71.3583 & 1.11713 & -0.375463 \tabularnewline
16 & 69.7 & 73.7206 & 73.3375 & 0.383102 & -4.0206 \tabularnewline
17 & 71.5 & 75.5345 & 75.1542 & 0.380324 & -4.03449 \tabularnewline
18 & 75.7 & 79.0303 & 77.1125 & 1.91782 & -3.33032 \tabularnewline
19 & 76 & 80.9373 & 79.5875 & 1.34977 & -4.93727 \tabularnewline
20 & 76.4 & 82.5775 & 82.6625 & -0.0849537 & -6.17755 \tabularnewline
21 & 83.8 & 85.3935 & 86.1833 & -0.789815 & -1.59352 \tabularnewline
22 & 86.2 & 85.9019 & 89.8083 & -3.90648 & 0.298148 \tabularnewline
23 & 88.5 & 90.1387 & 93.3333 & -3.19468 & -1.63866 \tabularnewline
24 & 95.9 & 95.2803 & 96.975 & -1.69468 & 0.619676 \tabularnewline
25 & 103.1 & 102.41 & 100.746 & 1.66435 & 0.689815 \tabularnewline
26 & 113.5 & 106.796 & 103.938 & 2.8581 & 6.7044 \tabularnewline
27 & 115.7 & 107.192 & 106.075 & 1.11713 & 8.50787 \tabularnewline
28 & 113.1 & 107.133 & 106.75 & 0.383102 & 5.9669 \tabularnewline
29 & 112.7 & 106.634 & 106.254 & 0.380324 & 6.06551 \tabularnewline
30 & 121.9 & 107.039 & 105.121 & 1.91782 & 14.8613 \tabularnewline
31 & 120.3 & 104.991 & 103.642 & 1.34977 & 15.3086 \tabularnewline
32 & 108.7 & 101.569 & 101.654 & -0.0849537 & 7.13079 \tabularnewline
33 & 102.8 & 98.1977 & 98.9875 & -0.789815 & 4.60231 \tabularnewline
34 & 83.4 & 92.5852 & 96.4917 & -3.90648 & -9.18519 \tabularnewline
35 & 79.4 & 91.497 & 94.6917 & -3.19468 & -12.097 \tabularnewline
36 & 77.8 & 91.2887 & 92.9833 & -1.69468 & -13.4887 \tabularnewline
37 & 85.7 & 92.356 & 90.6917 & 1.66435 & -6.65602 \tabularnewline
38 & 83.2 & 91.5414 & 88.6833 & 2.8581 & -8.34144 \tabularnewline
39 & 82 & 88.4171 & 87.3 & 1.11713 & -6.41713 \tabularnewline
40 & 86.9 & 87.3331 & 86.95 & 0.383102 & -0.433102 \tabularnewline
41 & 95.7 & 88.247 & 87.8667 & 0.380324 & 7.45301 \tabularnewline
42 & 97.9 & 91.1762 & 89.2583 & 1.91782 & 6.72384 \tabularnewline
43 & 89.3 & 91.8164 & 90.4667 & 1.34977 & -2.51644 \tabularnewline
44 & 91.5 & 91.14 & 91.225 & -0.0849537 & 0.359954 \tabularnewline
45 & 86.8 & 91.056 & 91.8458 & -0.789815 & -4.25602 \tabularnewline
46 & 91 & 88.2727 & 92.1792 & -3.90648 & 2.72731 \tabularnewline
47 & 93.8 & 88.7053 & 91.9 & -3.19468 & 5.09468 \tabularnewline
48 & 96.8 & 89.522 & 91.2167 & -1.69468 & 7.27801 \tabularnewline
49 & 95.7 & 92.7935 & 91.1292 & 1.66435 & 2.90648 \tabularnewline
50 & 91.4 & 94.6248 & 91.7667 & 2.8581 & -3.22477 \tabularnewline
51 & 88.7 & 94.0713 & 92.9542 & 1.11713 & -5.3713 \tabularnewline
52 & 88.2 & 95.0248 & 94.6417 & 0.383102 & -6.82477 \tabularnewline
53 & 87.7 & 96.8928 & 96.5125 & 0.380324 & -9.19282 \tabularnewline
54 & 89.5 & 100.601 & 98.6833 & 1.91782 & -11.1012 \tabularnewline
55 & 95.6 & 102.737 & 101.387 & 1.34977 & -7.13727 \tabularnewline
56 & 100.5 & 104.778 & 104.862 & -0.0849537 & -4.27755 \tabularnewline
57 & 106.3 & 107.935 & 108.725 & -0.789815 & -1.63519 \tabularnewline
58 & 112 & 108.756 & 112.662 & -3.90648 & 3.24398 \tabularnewline
59 & 117.7 & 113.43 & 116.625 & -3.19468 & 4.26968 \tabularnewline
60 & 125 & 118.626 & 120.321 & -1.69468 & 6.37384 \tabularnewline
61 & 132.4 & 125.164 & 123.5 & 1.66435 & 7.23565 \tabularnewline
62 & 138.1 & 129.091 & 126.233 & 2.8581 & 9.00856 \tabularnewline
63 & 134.7 & 129.638 & 128.521 & 1.11713 & 5.06204 \tabularnewline
64 & 136.7 & 130.191 & 129.808 & 0.383102 & 6.50856 \tabularnewline
65 & 134.3 & 130.455 & 130.075 & 0.380324 & 3.84468 \tabularnewline
66 & 131.6 & 131.443 & 129.525 & 1.91782 & 0.157176 \tabularnewline
67 & 129.8 & 129.683 & 128.333 & 1.34977 & 0.116898 \tabularnewline
68 & 131.9 & 126.707 & 126.792 & -0.0849537 & 5.19329 \tabularnewline
69 & 129.8 & 124.481 & 125.271 & -0.789815 & 5.31898 \tabularnewline
70 & 119.4 & 119.952 & 123.858 & -3.90648 & -0.551852 \tabularnewline
71 & 116.7 & 119.164 & 122.358 & -3.19468 & -2.46366 \tabularnewline
72 & 112.8 & 119.23 & 120.925 & -1.69468 & -6.43032 \tabularnewline
73 & 116 & 121.985 & 120.321 & 1.66435 & -5.98519 \tabularnewline
74 & 117.5 & 123.333 & 120.475 & 2.8581 & -5.8331 \tabularnewline
75 & 118.8 & 121.78 & 120.663 & 1.11713 & -2.97963 \tabularnewline
76 & 118.7 & 121.471 & 121.088 & 0.383102 & -2.7706 \tabularnewline
77 & 116.3 & 122.009 & 121.629 & 0.380324 & -5.70949 \tabularnewline
78 & 115.2 & 124.084 & 122.167 & 1.91782 & -8.88449 \tabularnewline
79 & 131.7 & NA & NA & 1.34977 & NA \tabularnewline
80 & 133.7 & NA & NA & -0.0849537 & NA \tabularnewline
81 & 132.5 & NA & NA & -0.789815 & NA \tabularnewline
82 & 126.9 & NA & NA & -3.90648 & NA \tabularnewline
83 & 122.2 & NA & NA & -3.19468 & NA \tabularnewline
84 & 120.2 & NA & NA & -1.69468 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=233131&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]59.8[/C][C]NA[/C][C]NA[/C][C]1.66435[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]60.7[/C][C]NA[/C][C]NA[/C][C]2.8581[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]59.7[/C][C]NA[/C][C]NA[/C][C]1.11713[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]60.2[/C][C]NA[/C][C]NA[/C][C]0.383102[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]61.3[/C][C]NA[/C][C]NA[/C][C]0.380324[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]59.8[/C][C]NA[/C][C]NA[/C][C]1.91782[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]61.2[/C][C]63.6081[/C][C]62.2583[/C][C]1.34977[/C][C]-2.4081[/C][/ROW]
[ROW][C]8[/C][C]59.3[/C][C]63.1025[/C][C]63.1875[/C][C]-0.0849537[/C][C]-3.80255[/C][/ROW]
[ROW][C]9[/C][C]59.4[/C][C]63.4102[/C][C]64.2[/C][C]-0.789815[/C][C]-4.01019[/C][/ROW]
[ROW][C]10[/C][C]63.1[/C][C]61.206[/C][C]65.1125[/C][C]-3.90648[/C][C]1.89398[/C][/ROW]
[ROW][C]11[/C][C]68[/C][C]62.7387[/C][C]65.9333[/C][C]-3.19468[/C][C]5.26134[/C][/ROW]
[ROW][C]12[/C][C]69.4[/C][C]65.3262[/C][C]67.0208[/C][C]-1.69468[/C][C]4.07384[/C][/ROW]
[ROW][C]13[/C][C]70.2[/C][C]69.9644[/C][C]68.3[/C][C]1.66435[/C][C]0.235648[/C][/ROW]
[ROW][C]14[/C][C]72.6[/C][C]72.4873[/C][C]69.6292[/C][C]2.8581[/C][C]0.112731[/C][/ROW]
[ROW][C]15[/C][C]72.1[/C][C]72.4755[/C][C]71.3583[/C][C]1.11713[/C][C]-0.375463[/C][/ROW]
[ROW][C]16[/C][C]69.7[/C][C]73.7206[/C][C]73.3375[/C][C]0.383102[/C][C]-4.0206[/C][/ROW]
[ROW][C]17[/C][C]71.5[/C][C]75.5345[/C][C]75.1542[/C][C]0.380324[/C][C]-4.03449[/C][/ROW]
[ROW][C]18[/C][C]75.7[/C][C]79.0303[/C][C]77.1125[/C][C]1.91782[/C][C]-3.33032[/C][/ROW]
[ROW][C]19[/C][C]76[/C][C]80.9373[/C][C]79.5875[/C][C]1.34977[/C][C]-4.93727[/C][/ROW]
[ROW][C]20[/C][C]76.4[/C][C]82.5775[/C][C]82.6625[/C][C]-0.0849537[/C][C]-6.17755[/C][/ROW]
[ROW][C]21[/C][C]83.8[/C][C]85.3935[/C][C]86.1833[/C][C]-0.789815[/C][C]-1.59352[/C][/ROW]
[ROW][C]22[/C][C]86.2[/C][C]85.9019[/C][C]89.8083[/C][C]-3.90648[/C][C]0.298148[/C][/ROW]
[ROW][C]23[/C][C]88.5[/C][C]90.1387[/C][C]93.3333[/C][C]-3.19468[/C][C]-1.63866[/C][/ROW]
[ROW][C]24[/C][C]95.9[/C][C]95.2803[/C][C]96.975[/C][C]-1.69468[/C][C]0.619676[/C][/ROW]
[ROW][C]25[/C][C]103.1[/C][C]102.41[/C][C]100.746[/C][C]1.66435[/C][C]0.689815[/C][/ROW]
[ROW][C]26[/C][C]113.5[/C][C]106.796[/C][C]103.938[/C][C]2.8581[/C][C]6.7044[/C][/ROW]
[ROW][C]27[/C][C]115.7[/C][C]107.192[/C][C]106.075[/C][C]1.11713[/C][C]8.50787[/C][/ROW]
[ROW][C]28[/C][C]113.1[/C][C]107.133[/C][C]106.75[/C][C]0.383102[/C][C]5.9669[/C][/ROW]
[ROW][C]29[/C][C]112.7[/C][C]106.634[/C][C]106.254[/C][C]0.380324[/C][C]6.06551[/C][/ROW]
[ROW][C]30[/C][C]121.9[/C][C]107.039[/C][C]105.121[/C][C]1.91782[/C][C]14.8613[/C][/ROW]
[ROW][C]31[/C][C]120.3[/C][C]104.991[/C][C]103.642[/C][C]1.34977[/C][C]15.3086[/C][/ROW]
[ROW][C]32[/C][C]108.7[/C][C]101.569[/C][C]101.654[/C][C]-0.0849537[/C][C]7.13079[/C][/ROW]
[ROW][C]33[/C][C]102.8[/C][C]98.1977[/C][C]98.9875[/C][C]-0.789815[/C][C]4.60231[/C][/ROW]
[ROW][C]34[/C][C]83.4[/C][C]92.5852[/C][C]96.4917[/C][C]-3.90648[/C][C]-9.18519[/C][/ROW]
[ROW][C]35[/C][C]79.4[/C][C]91.497[/C][C]94.6917[/C][C]-3.19468[/C][C]-12.097[/C][/ROW]
[ROW][C]36[/C][C]77.8[/C][C]91.2887[/C][C]92.9833[/C][C]-1.69468[/C][C]-13.4887[/C][/ROW]
[ROW][C]37[/C][C]85.7[/C][C]92.356[/C][C]90.6917[/C][C]1.66435[/C][C]-6.65602[/C][/ROW]
[ROW][C]38[/C][C]83.2[/C][C]91.5414[/C][C]88.6833[/C][C]2.8581[/C][C]-8.34144[/C][/ROW]
[ROW][C]39[/C][C]82[/C][C]88.4171[/C][C]87.3[/C][C]1.11713[/C][C]-6.41713[/C][/ROW]
[ROW][C]40[/C][C]86.9[/C][C]87.3331[/C][C]86.95[/C][C]0.383102[/C][C]-0.433102[/C][/ROW]
[ROW][C]41[/C][C]95.7[/C][C]88.247[/C][C]87.8667[/C][C]0.380324[/C][C]7.45301[/C][/ROW]
[ROW][C]42[/C][C]97.9[/C][C]91.1762[/C][C]89.2583[/C][C]1.91782[/C][C]6.72384[/C][/ROW]
[ROW][C]43[/C][C]89.3[/C][C]91.8164[/C][C]90.4667[/C][C]1.34977[/C][C]-2.51644[/C][/ROW]
[ROW][C]44[/C][C]91.5[/C][C]91.14[/C][C]91.225[/C][C]-0.0849537[/C][C]0.359954[/C][/ROW]
[ROW][C]45[/C][C]86.8[/C][C]91.056[/C][C]91.8458[/C][C]-0.789815[/C][C]-4.25602[/C][/ROW]
[ROW][C]46[/C][C]91[/C][C]88.2727[/C][C]92.1792[/C][C]-3.90648[/C][C]2.72731[/C][/ROW]
[ROW][C]47[/C][C]93.8[/C][C]88.7053[/C][C]91.9[/C][C]-3.19468[/C][C]5.09468[/C][/ROW]
[ROW][C]48[/C][C]96.8[/C][C]89.522[/C][C]91.2167[/C][C]-1.69468[/C][C]7.27801[/C][/ROW]
[ROW][C]49[/C][C]95.7[/C][C]92.7935[/C][C]91.1292[/C][C]1.66435[/C][C]2.90648[/C][/ROW]
[ROW][C]50[/C][C]91.4[/C][C]94.6248[/C][C]91.7667[/C][C]2.8581[/C][C]-3.22477[/C][/ROW]
[ROW][C]51[/C][C]88.7[/C][C]94.0713[/C][C]92.9542[/C][C]1.11713[/C][C]-5.3713[/C][/ROW]
[ROW][C]52[/C][C]88.2[/C][C]95.0248[/C][C]94.6417[/C][C]0.383102[/C][C]-6.82477[/C][/ROW]
[ROW][C]53[/C][C]87.7[/C][C]96.8928[/C][C]96.5125[/C][C]0.380324[/C][C]-9.19282[/C][/ROW]
[ROW][C]54[/C][C]89.5[/C][C]100.601[/C][C]98.6833[/C][C]1.91782[/C][C]-11.1012[/C][/ROW]
[ROW][C]55[/C][C]95.6[/C][C]102.737[/C][C]101.387[/C][C]1.34977[/C][C]-7.13727[/C][/ROW]
[ROW][C]56[/C][C]100.5[/C][C]104.778[/C][C]104.862[/C][C]-0.0849537[/C][C]-4.27755[/C][/ROW]
[ROW][C]57[/C][C]106.3[/C][C]107.935[/C][C]108.725[/C][C]-0.789815[/C][C]-1.63519[/C][/ROW]
[ROW][C]58[/C][C]112[/C][C]108.756[/C][C]112.662[/C][C]-3.90648[/C][C]3.24398[/C][/ROW]
[ROW][C]59[/C][C]117.7[/C][C]113.43[/C][C]116.625[/C][C]-3.19468[/C][C]4.26968[/C][/ROW]
[ROW][C]60[/C][C]125[/C][C]118.626[/C][C]120.321[/C][C]-1.69468[/C][C]6.37384[/C][/ROW]
[ROW][C]61[/C][C]132.4[/C][C]125.164[/C][C]123.5[/C][C]1.66435[/C][C]7.23565[/C][/ROW]
[ROW][C]62[/C][C]138.1[/C][C]129.091[/C][C]126.233[/C][C]2.8581[/C][C]9.00856[/C][/ROW]
[ROW][C]63[/C][C]134.7[/C][C]129.638[/C][C]128.521[/C][C]1.11713[/C][C]5.06204[/C][/ROW]
[ROW][C]64[/C][C]136.7[/C][C]130.191[/C][C]129.808[/C][C]0.383102[/C][C]6.50856[/C][/ROW]
[ROW][C]65[/C][C]134.3[/C][C]130.455[/C][C]130.075[/C][C]0.380324[/C][C]3.84468[/C][/ROW]
[ROW][C]66[/C][C]131.6[/C][C]131.443[/C][C]129.525[/C][C]1.91782[/C][C]0.157176[/C][/ROW]
[ROW][C]67[/C][C]129.8[/C][C]129.683[/C][C]128.333[/C][C]1.34977[/C][C]0.116898[/C][/ROW]
[ROW][C]68[/C][C]131.9[/C][C]126.707[/C][C]126.792[/C][C]-0.0849537[/C][C]5.19329[/C][/ROW]
[ROW][C]69[/C][C]129.8[/C][C]124.481[/C][C]125.271[/C][C]-0.789815[/C][C]5.31898[/C][/ROW]
[ROW][C]70[/C][C]119.4[/C][C]119.952[/C][C]123.858[/C][C]-3.90648[/C][C]-0.551852[/C][/ROW]
[ROW][C]71[/C][C]116.7[/C][C]119.164[/C][C]122.358[/C][C]-3.19468[/C][C]-2.46366[/C][/ROW]
[ROW][C]72[/C][C]112.8[/C][C]119.23[/C][C]120.925[/C][C]-1.69468[/C][C]-6.43032[/C][/ROW]
[ROW][C]73[/C][C]116[/C][C]121.985[/C][C]120.321[/C][C]1.66435[/C][C]-5.98519[/C][/ROW]
[ROW][C]74[/C][C]117.5[/C][C]123.333[/C][C]120.475[/C][C]2.8581[/C][C]-5.8331[/C][/ROW]
[ROW][C]75[/C][C]118.8[/C][C]121.78[/C][C]120.663[/C][C]1.11713[/C][C]-2.97963[/C][/ROW]
[ROW][C]76[/C][C]118.7[/C][C]121.471[/C][C]121.088[/C][C]0.383102[/C][C]-2.7706[/C][/ROW]
[ROW][C]77[/C][C]116.3[/C][C]122.009[/C][C]121.629[/C][C]0.380324[/C][C]-5.70949[/C][/ROW]
[ROW][C]78[/C][C]115.2[/C][C]124.084[/C][C]122.167[/C][C]1.91782[/C][C]-8.88449[/C][/ROW]
[ROW][C]79[/C][C]131.7[/C][C]NA[/C][C]NA[/C][C]1.34977[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]133.7[/C][C]NA[/C][C]NA[/C][C]-0.0849537[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]132.5[/C][C]NA[/C][C]NA[/C][C]-0.789815[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]126.9[/C][C]NA[/C][C]NA[/C][C]-3.90648[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]122.2[/C][C]NA[/C][C]NA[/C][C]-3.19468[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]120.2[/C][C]NA[/C][C]NA[/C][C]-1.69468[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=233131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=233131&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	59.8	NA	NA	1.66435	NA
2	60.7	NA	NA	2.8581	NA
3	59.7	NA	NA	1.11713	NA
4	60.2	NA	NA	0.383102	NA
5	61.3	NA	NA	0.380324	NA
6	59.8	NA	NA	1.91782	NA
7	61.2	63.6081	62.2583	1.34977	-2.4081
8	59.3	63.1025	63.1875	-0.0849537	-3.80255
9	59.4	63.4102	64.2	-0.789815	-4.01019
10	63.1	61.206	65.1125	-3.90648	1.89398
11	68	62.7387	65.9333	-3.19468	5.26134
12	69.4	65.3262	67.0208	-1.69468	4.07384
13	70.2	69.9644	68.3	1.66435	0.235648
14	72.6	72.4873	69.6292	2.8581	0.112731
15	72.1	72.4755	71.3583	1.11713	-0.375463
16	69.7	73.7206	73.3375	0.383102	-4.0206
17	71.5	75.5345	75.1542	0.380324	-4.03449
18	75.7	79.0303	77.1125	1.91782	-3.33032
19	76	80.9373	79.5875	1.34977	-4.93727
20	76.4	82.5775	82.6625	-0.0849537	-6.17755
21	83.8	85.3935	86.1833	-0.789815	-1.59352
22	86.2	85.9019	89.8083	-3.90648	0.298148
23	88.5	90.1387	93.3333	-3.19468	-1.63866
24	95.9	95.2803	96.975	-1.69468	0.619676
25	103.1	102.41	100.746	1.66435	0.689815
26	113.5	106.796	103.938	2.8581	6.7044
27	115.7	107.192	106.075	1.11713	8.50787
28	113.1	107.133	106.75	0.383102	5.9669
29	112.7	106.634	106.254	0.380324	6.06551
30	121.9	107.039	105.121	1.91782	14.8613
31	120.3	104.991	103.642	1.34977	15.3086
32	108.7	101.569	101.654	-0.0849537	7.13079
33	102.8	98.1977	98.9875	-0.789815	4.60231
34	83.4	92.5852	96.4917	-3.90648	-9.18519
35	79.4	91.497	94.6917	-3.19468	-12.097
36	77.8	91.2887	92.9833	-1.69468	-13.4887
37	85.7	92.356	90.6917	1.66435	-6.65602
38	83.2	91.5414	88.6833	2.8581	-8.34144
39	82	88.4171	87.3	1.11713	-6.41713
40	86.9	87.3331	86.95	0.383102	-0.433102
41	95.7	88.247	87.8667	0.380324	7.45301
42	97.9	91.1762	89.2583	1.91782	6.72384
43	89.3	91.8164	90.4667	1.34977	-2.51644
44	91.5	91.14	91.225	-0.0849537	0.359954
45	86.8	91.056	91.8458	-0.789815	-4.25602
46	91	88.2727	92.1792	-3.90648	2.72731
47	93.8	88.7053	91.9	-3.19468	5.09468
48	96.8	89.522	91.2167	-1.69468	7.27801
49	95.7	92.7935	91.1292	1.66435	2.90648
50	91.4	94.6248	91.7667	2.8581	-3.22477
51	88.7	94.0713	92.9542	1.11713	-5.3713
52	88.2	95.0248	94.6417	0.383102	-6.82477
53	87.7	96.8928	96.5125	0.380324	-9.19282
54	89.5	100.601	98.6833	1.91782	-11.1012
55	95.6	102.737	101.387	1.34977	-7.13727
56	100.5	104.778	104.862	-0.0849537	-4.27755
57	106.3	107.935	108.725	-0.789815	-1.63519
58	112	108.756	112.662	-3.90648	3.24398
59	117.7	113.43	116.625	-3.19468	4.26968
60	125	118.626	120.321	-1.69468	6.37384
61	132.4	125.164	123.5	1.66435	7.23565
62	138.1	129.091	126.233	2.8581	9.00856
63	134.7	129.638	128.521	1.11713	5.06204
64	136.7	130.191	129.808	0.383102	6.50856
65	134.3	130.455	130.075	0.380324	3.84468
66	131.6	131.443	129.525	1.91782	0.157176
67	129.8	129.683	128.333	1.34977	0.116898
68	131.9	126.707	126.792	-0.0849537	5.19329
69	129.8	124.481	125.271	-0.789815	5.31898
70	119.4	119.952	123.858	-3.90648	-0.551852
71	116.7	119.164	122.358	-3.19468	-2.46366
72	112.8	119.23	120.925	-1.69468	-6.43032
73	116	121.985	120.321	1.66435	-5.98519
74	117.5	123.333	120.475	2.8581	-5.8331
75	118.8	121.78	120.663	1.11713	-2.97963
76	118.7	121.471	121.088	0.383102	-2.7706
77	116.3	122.009	121.629	0.380324	-5.70949
78	115.2	124.084	122.167	1.91782	-8.88449
79	131.7	NA	NA	1.34977	NA
80	133.7	NA	NA	-0.0849537	NA
81	132.5	NA	NA	-0.789815	NA
82	126.9	NA	NA	-3.90648	NA
83	122.2	NA	NA	-3.19468	NA
84	120.2	NA	NA	-1.69468	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