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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 18:15:05 +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/2016/Apr/25/t14616045350daacrlhsdfs3pm.htm/, Retrieved Mon, 06 May 2024 00:21:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294750, Retrieved Mon, 06 May 2024 00:21:32 +0000

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-       [Classical Decomposition] [Opgave9/oef1/stap2] [2016-04-25 17:15:05] [efea2b8bc7c91838390b884e612c3e3f] [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=294750&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=294750&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294750&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	92.94	NA	NA	-0.361972	NA
2	92.97	NA	NA	-0.164389	NA
3	93.37	NA	NA	0.533694	NA
4	92.6	NA	NA	0.0521944	NA
5	92.84	NA	NA	-0.0893056	NA
6	92.55	NA	NA	-0.111972	NA
7	92.93	92.5956	92.8267	-0.231056	0.334389
8	92.44	92.7275	92.7708	-0.0433056	-0.287528
9	93.36	93.2699	92.6463	0.623611	0.0901389
10	93.24	92.85	92.4775	0.372528	0.389972
11	92.65	92.4159	92.3079	0.108028	0.234056
12	92.06	91.5386	92.2267	-0.688056	0.521389
13	92.88	91.8093	92.1712	-0.361972	1.07072
14	91.69	91.9523	92.1167	-0.164389	-0.262278
15	91.66	92.6416	92.1079	0.533694	-0.981611
16	90.26	92.1718	92.1196	0.0521944	-1.91178
17	91.11	92.0711	92.1604	-0.0893056	-0.961111
18	92.33	92.0993	92.2112	-0.111972	0.230722
19	91.82	91.9831	92.2142	-0.231056	-0.163111
20	92.24	92.1913	92.2346	-0.0433056	0.0487222
21	93.35	93.0136	92.39	0.623611	0.336389
22	93.53	93.0171	92.6446	0.372528	0.512889
23	93.34	92.9864	92.8783	0.108028	0.353639
24	92.59	92.3269	93.015	-0.688056	0.263056
25	92.42	92.7739	93.1358	-0.361972	-0.353861
26	92.64	93.1835	93.3479	-0.164389	-0.543528
27	94.44	94.1691	93.6354	0.533694	0.270889
28	93.59	94.0159	93.9637	0.0521944	-0.425944
29	93.39	94.2253	94.3146	-0.0893056	-0.835278
30	93.33	94.5622	94.6742	-0.111972	-1.23219
31	93.72	94.8477	95.0788	-0.231056	-1.12769
32	95.43	95.5338	95.5771	-0.0433056	-0.103778
33	97.06	96.7349	96.1112	0.623611	0.325139
34	97.7	97.0004	96.6279	0.372528	0.699556
35	97.59	97.2493	97.1412	0.108028	0.340722
36	96.97	96.974	97.6621	-0.688056	-0.00402778
37	97.75	97.8184	98.1804	-0.361972	-0.0684444
38	99.27	98.466	98.6304	-0.164389	0.803972
39	100.63	99.5308	98.9971	0.533694	1.09922
40	99.8	99.3418	99.2896	0.0521944	0.458222
41	99.5	99.4715	99.5608	-0.0893056	0.0284722
42	99.72	99.7418	99.8537	-0.111972	-0.0217778
43	99.77	99.9285	100.16	-0.231056	-0.158528
44	100.18	100.403	100.446	-0.0433056	-0.222944
45	101.11	101.306	100.682	0.623611	-0.195694
46	100.67	101.363	100.99	0.372528	-0.692528
47	101.13	101.509	101.401	0.108028	-0.379278
48	100.46	101.13	101.818	-0.688056	-0.670278
49	101.6	101.88	102.242	-0.361972	-0.279694
50	102.3	102.494	102.659	-0.164389	-0.194361
51	103.26	103.541	103.008	0.533694	-0.281194
52	104.56	103.363	103.311	0.0521944	1.19697
53	104.61	103.519	103.608	-0.0893056	1.09139
54	104.62	103.805	103.917	-0.111972	0.814889
55	105.03	103.977	104.208	-0.231056	1.05314
56	104.93	104.426	104.47	-0.0433056	0.503722
57	104.73	105.348	104.724	0.623611	-0.617778
58	104.33	105.302	104.929	0.372528	-0.971694
59	104.6	105.211	105.103	0.108028	-0.610944
60	104.41	104.582	105.27	-0.688056	-0.171944
61	104.63	105.061	105.422	-0.361972	-0.430528
62	105.55	105.416	105.58	-0.164389	0.134389
63	106.12	106.289	105.755	0.533694	-0.169111
64	106.62	105.999	105.947	0.0521944	0.620722
65	106.72	106.105	106.195	-0.0893056	0.614722
66	106.52	106.373	106.485	-0.111972	0.146556
67	106.79	NA	NA	-0.231056	NA
68	106.95	NA	NA	-0.0433056	NA
69	106.92	NA	NA	0.623611	NA
70	106.74	NA	NA	0.372528	NA
71	108.13	NA	NA	0.108028	NA
72	107.86	NA	NA	-0.688056	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 92.94 & NA & NA & -0.361972 & NA \tabularnewline
2 & 92.97 & NA & NA & -0.164389 & NA \tabularnewline
3 & 93.37 & NA & NA & 0.533694 & NA \tabularnewline
4 & 92.6 & NA & NA & 0.0521944 & NA \tabularnewline
5 & 92.84 & NA & NA & -0.0893056 & NA \tabularnewline
6 & 92.55 & NA & NA & -0.111972 & NA \tabularnewline
7 & 92.93 & 92.5956 & 92.8267 & -0.231056 & 0.334389 \tabularnewline
8 & 92.44 & 92.7275 & 92.7708 & -0.0433056 & -0.287528 \tabularnewline
9 & 93.36 & 93.2699 & 92.6463 & 0.623611 & 0.0901389 \tabularnewline
10 & 93.24 & 92.85 & 92.4775 & 0.372528 & 0.389972 \tabularnewline
11 & 92.65 & 92.4159 & 92.3079 & 0.108028 & 0.234056 \tabularnewline
12 & 92.06 & 91.5386 & 92.2267 & -0.688056 & 0.521389 \tabularnewline
13 & 92.88 & 91.8093 & 92.1712 & -0.361972 & 1.07072 \tabularnewline
14 & 91.69 & 91.9523 & 92.1167 & -0.164389 & -0.262278 \tabularnewline
15 & 91.66 & 92.6416 & 92.1079 & 0.533694 & -0.981611 \tabularnewline
16 & 90.26 & 92.1718 & 92.1196 & 0.0521944 & -1.91178 \tabularnewline
17 & 91.11 & 92.0711 & 92.1604 & -0.0893056 & -0.961111 \tabularnewline
18 & 92.33 & 92.0993 & 92.2112 & -0.111972 & 0.230722 \tabularnewline
19 & 91.82 & 91.9831 & 92.2142 & -0.231056 & -0.163111 \tabularnewline
20 & 92.24 & 92.1913 & 92.2346 & -0.0433056 & 0.0487222 \tabularnewline
21 & 93.35 & 93.0136 & 92.39 & 0.623611 & 0.336389 \tabularnewline
22 & 93.53 & 93.0171 & 92.6446 & 0.372528 & 0.512889 \tabularnewline
23 & 93.34 & 92.9864 & 92.8783 & 0.108028 & 0.353639 \tabularnewline
24 & 92.59 & 92.3269 & 93.015 & -0.688056 & 0.263056 \tabularnewline
25 & 92.42 & 92.7739 & 93.1358 & -0.361972 & -0.353861 \tabularnewline
26 & 92.64 & 93.1835 & 93.3479 & -0.164389 & -0.543528 \tabularnewline
27 & 94.44 & 94.1691 & 93.6354 & 0.533694 & 0.270889 \tabularnewline
28 & 93.59 & 94.0159 & 93.9637 & 0.0521944 & -0.425944 \tabularnewline
29 & 93.39 & 94.2253 & 94.3146 & -0.0893056 & -0.835278 \tabularnewline
30 & 93.33 & 94.5622 & 94.6742 & -0.111972 & -1.23219 \tabularnewline
31 & 93.72 & 94.8477 & 95.0788 & -0.231056 & -1.12769 \tabularnewline
32 & 95.43 & 95.5338 & 95.5771 & -0.0433056 & -0.103778 \tabularnewline
33 & 97.06 & 96.7349 & 96.1112 & 0.623611 & 0.325139 \tabularnewline
34 & 97.7 & 97.0004 & 96.6279 & 0.372528 & 0.699556 \tabularnewline
35 & 97.59 & 97.2493 & 97.1412 & 0.108028 & 0.340722 \tabularnewline
36 & 96.97 & 96.974 & 97.6621 & -0.688056 & -0.00402778 \tabularnewline
37 & 97.75 & 97.8184 & 98.1804 & -0.361972 & -0.0684444 \tabularnewline
38 & 99.27 & 98.466 & 98.6304 & -0.164389 & 0.803972 \tabularnewline
39 & 100.63 & 99.5308 & 98.9971 & 0.533694 & 1.09922 \tabularnewline
40 & 99.8 & 99.3418 & 99.2896 & 0.0521944 & 0.458222 \tabularnewline
41 & 99.5 & 99.4715 & 99.5608 & -0.0893056 & 0.0284722 \tabularnewline
42 & 99.72 & 99.7418 & 99.8537 & -0.111972 & -0.0217778 \tabularnewline
43 & 99.77 & 99.9285 & 100.16 & -0.231056 & -0.158528 \tabularnewline
44 & 100.18 & 100.403 & 100.446 & -0.0433056 & -0.222944 \tabularnewline
45 & 101.11 & 101.306 & 100.682 & 0.623611 & -0.195694 \tabularnewline
46 & 100.67 & 101.363 & 100.99 & 0.372528 & -0.692528 \tabularnewline
47 & 101.13 & 101.509 & 101.401 & 0.108028 & -0.379278 \tabularnewline
48 & 100.46 & 101.13 & 101.818 & -0.688056 & -0.670278 \tabularnewline
49 & 101.6 & 101.88 & 102.242 & -0.361972 & -0.279694 \tabularnewline
50 & 102.3 & 102.494 & 102.659 & -0.164389 & -0.194361 \tabularnewline
51 & 103.26 & 103.541 & 103.008 & 0.533694 & -0.281194 \tabularnewline
52 & 104.56 & 103.363 & 103.311 & 0.0521944 & 1.19697 \tabularnewline
53 & 104.61 & 103.519 & 103.608 & -0.0893056 & 1.09139 \tabularnewline
54 & 104.62 & 103.805 & 103.917 & -0.111972 & 0.814889 \tabularnewline
55 & 105.03 & 103.977 & 104.208 & -0.231056 & 1.05314 \tabularnewline
56 & 104.93 & 104.426 & 104.47 & -0.0433056 & 0.503722 \tabularnewline
57 & 104.73 & 105.348 & 104.724 & 0.623611 & -0.617778 \tabularnewline
58 & 104.33 & 105.302 & 104.929 & 0.372528 & -0.971694 \tabularnewline
59 & 104.6 & 105.211 & 105.103 & 0.108028 & -0.610944 \tabularnewline
60 & 104.41 & 104.582 & 105.27 & -0.688056 & -0.171944 \tabularnewline
61 & 104.63 & 105.061 & 105.422 & -0.361972 & -0.430528 \tabularnewline
62 & 105.55 & 105.416 & 105.58 & -0.164389 & 0.134389 \tabularnewline
63 & 106.12 & 106.289 & 105.755 & 0.533694 & -0.169111 \tabularnewline
64 & 106.62 & 105.999 & 105.947 & 0.0521944 & 0.620722 \tabularnewline
65 & 106.72 & 106.105 & 106.195 & -0.0893056 & 0.614722 \tabularnewline
66 & 106.52 & 106.373 & 106.485 & -0.111972 & 0.146556 \tabularnewline
67 & 106.79 & NA & NA & -0.231056 & NA \tabularnewline
68 & 106.95 & NA & NA & -0.0433056 & NA \tabularnewline
69 & 106.92 & NA & NA & 0.623611 & NA \tabularnewline
70 & 106.74 & NA & NA & 0.372528 & NA \tabularnewline
71 & 108.13 & NA & NA & 0.108028 & NA \tabularnewline
72 & 107.86 & NA & NA & -0.688056 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294750&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]92.94[/C][C]NA[/C][C]NA[/C][C]-0.361972[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]92.97[/C][C]NA[/C][C]NA[/C][C]-0.164389[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]93.37[/C][C]NA[/C][C]NA[/C][C]0.533694[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]92.6[/C][C]NA[/C][C]NA[/C][C]0.0521944[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.84[/C][C]NA[/C][C]NA[/C][C]-0.0893056[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.55[/C][C]NA[/C][C]NA[/C][C]-0.111972[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]92.93[/C][C]92.5956[/C][C]92.8267[/C][C]-0.231056[/C][C]0.334389[/C][/ROW]
[ROW][C]8[/C][C]92.44[/C][C]92.7275[/C][C]92.7708[/C][C]-0.0433056[/C][C]-0.287528[/C][/ROW]
[ROW][C]9[/C][C]93.36[/C][C]93.2699[/C][C]92.6463[/C][C]0.623611[/C][C]0.0901389[/C][/ROW]
[ROW][C]10[/C][C]93.24[/C][C]92.85[/C][C]92.4775[/C][C]0.372528[/C][C]0.389972[/C][/ROW]
[ROW][C]11[/C][C]92.65[/C][C]92.4159[/C][C]92.3079[/C][C]0.108028[/C][C]0.234056[/C][/ROW]
[ROW][C]12[/C][C]92.06[/C][C]91.5386[/C][C]92.2267[/C][C]-0.688056[/C][C]0.521389[/C][/ROW]
[ROW][C]13[/C][C]92.88[/C][C]91.8093[/C][C]92.1712[/C][C]-0.361972[/C][C]1.07072[/C][/ROW]
[ROW][C]14[/C][C]91.69[/C][C]91.9523[/C][C]92.1167[/C][C]-0.164389[/C][C]-0.262278[/C][/ROW]
[ROW][C]15[/C][C]91.66[/C][C]92.6416[/C][C]92.1079[/C][C]0.533694[/C][C]-0.981611[/C][/ROW]
[ROW][C]16[/C][C]90.26[/C][C]92.1718[/C][C]92.1196[/C][C]0.0521944[/C][C]-1.91178[/C][/ROW]
[ROW][C]17[/C][C]91.11[/C][C]92.0711[/C][C]92.1604[/C][C]-0.0893056[/C][C]-0.961111[/C][/ROW]
[ROW][C]18[/C][C]92.33[/C][C]92.0993[/C][C]92.2112[/C][C]-0.111972[/C][C]0.230722[/C][/ROW]
[ROW][C]19[/C][C]91.82[/C][C]91.9831[/C][C]92.2142[/C][C]-0.231056[/C][C]-0.163111[/C][/ROW]
[ROW][C]20[/C][C]92.24[/C][C]92.1913[/C][C]92.2346[/C][C]-0.0433056[/C][C]0.0487222[/C][/ROW]
[ROW][C]21[/C][C]93.35[/C][C]93.0136[/C][C]92.39[/C][C]0.623611[/C][C]0.336389[/C][/ROW]
[ROW][C]22[/C][C]93.53[/C][C]93.0171[/C][C]92.6446[/C][C]0.372528[/C][C]0.512889[/C][/ROW]
[ROW][C]23[/C][C]93.34[/C][C]92.9864[/C][C]92.8783[/C][C]0.108028[/C][C]0.353639[/C][/ROW]
[ROW][C]24[/C][C]92.59[/C][C]92.3269[/C][C]93.015[/C][C]-0.688056[/C][C]0.263056[/C][/ROW]
[ROW][C]25[/C][C]92.42[/C][C]92.7739[/C][C]93.1358[/C][C]-0.361972[/C][C]-0.353861[/C][/ROW]
[ROW][C]26[/C][C]92.64[/C][C]93.1835[/C][C]93.3479[/C][C]-0.164389[/C][C]-0.543528[/C][/ROW]
[ROW][C]27[/C][C]94.44[/C][C]94.1691[/C][C]93.6354[/C][C]0.533694[/C][C]0.270889[/C][/ROW]
[ROW][C]28[/C][C]93.59[/C][C]94.0159[/C][C]93.9637[/C][C]0.0521944[/C][C]-0.425944[/C][/ROW]
[ROW][C]29[/C][C]93.39[/C][C]94.2253[/C][C]94.3146[/C][C]-0.0893056[/C][C]-0.835278[/C][/ROW]
[ROW][C]30[/C][C]93.33[/C][C]94.5622[/C][C]94.6742[/C][C]-0.111972[/C][C]-1.23219[/C][/ROW]
[ROW][C]31[/C][C]93.72[/C][C]94.8477[/C][C]95.0788[/C][C]-0.231056[/C][C]-1.12769[/C][/ROW]
[ROW][C]32[/C][C]95.43[/C][C]95.5338[/C][C]95.5771[/C][C]-0.0433056[/C][C]-0.103778[/C][/ROW]
[ROW][C]33[/C][C]97.06[/C][C]96.7349[/C][C]96.1112[/C][C]0.623611[/C][C]0.325139[/C][/ROW]
[ROW][C]34[/C][C]97.7[/C][C]97.0004[/C][C]96.6279[/C][C]0.372528[/C][C]0.699556[/C][/ROW]
[ROW][C]35[/C][C]97.59[/C][C]97.2493[/C][C]97.1412[/C][C]0.108028[/C][C]0.340722[/C][/ROW]
[ROW][C]36[/C][C]96.97[/C][C]96.974[/C][C]97.6621[/C][C]-0.688056[/C][C]-0.00402778[/C][/ROW]
[ROW][C]37[/C][C]97.75[/C][C]97.8184[/C][C]98.1804[/C][C]-0.361972[/C][C]-0.0684444[/C][/ROW]
[ROW][C]38[/C][C]99.27[/C][C]98.466[/C][C]98.6304[/C][C]-0.164389[/C][C]0.803972[/C][/ROW]
[ROW][C]39[/C][C]100.63[/C][C]99.5308[/C][C]98.9971[/C][C]0.533694[/C][C]1.09922[/C][/ROW]
[ROW][C]40[/C][C]99.8[/C][C]99.3418[/C][C]99.2896[/C][C]0.0521944[/C][C]0.458222[/C][/ROW]
[ROW][C]41[/C][C]99.5[/C][C]99.4715[/C][C]99.5608[/C][C]-0.0893056[/C][C]0.0284722[/C][/ROW]
[ROW][C]42[/C][C]99.72[/C][C]99.7418[/C][C]99.8537[/C][C]-0.111972[/C][C]-0.0217778[/C][/ROW]
[ROW][C]43[/C][C]99.77[/C][C]99.9285[/C][C]100.16[/C][C]-0.231056[/C][C]-0.158528[/C][/ROW]
[ROW][C]44[/C][C]100.18[/C][C]100.403[/C][C]100.446[/C][C]-0.0433056[/C][C]-0.222944[/C][/ROW]
[ROW][C]45[/C][C]101.11[/C][C]101.306[/C][C]100.682[/C][C]0.623611[/C][C]-0.195694[/C][/ROW]
[ROW][C]46[/C][C]100.67[/C][C]101.363[/C][C]100.99[/C][C]0.372528[/C][C]-0.692528[/C][/ROW]
[ROW][C]47[/C][C]101.13[/C][C]101.509[/C][C]101.401[/C][C]0.108028[/C][C]-0.379278[/C][/ROW]
[ROW][C]48[/C][C]100.46[/C][C]101.13[/C][C]101.818[/C][C]-0.688056[/C][C]-0.670278[/C][/ROW]
[ROW][C]49[/C][C]101.6[/C][C]101.88[/C][C]102.242[/C][C]-0.361972[/C][C]-0.279694[/C][/ROW]
[ROW][C]50[/C][C]102.3[/C][C]102.494[/C][C]102.659[/C][C]-0.164389[/C][C]-0.194361[/C][/ROW]
[ROW][C]51[/C][C]103.26[/C][C]103.541[/C][C]103.008[/C][C]0.533694[/C][C]-0.281194[/C][/ROW]
[ROW][C]52[/C][C]104.56[/C][C]103.363[/C][C]103.311[/C][C]0.0521944[/C][C]1.19697[/C][/ROW]
[ROW][C]53[/C][C]104.61[/C][C]103.519[/C][C]103.608[/C][C]-0.0893056[/C][C]1.09139[/C][/ROW]
[ROW][C]54[/C][C]104.62[/C][C]103.805[/C][C]103.917[/C][C]-0.111972[/C][C]0.814889[/C][/ROW]
[ROW][C]55[/C][C]105.03[/C][C]103.977[/C][C]104.208[/C][C]-0.231056[/C][C]1.05314[/C][/ROW]
[ROW][C]56[/C][C]104.93[/C][C]104.426[/C][C]104.47[/C][C]-0.0433056[/C][C]0.503722[/C][/ROW]
[ROW][C]57[/C][C]104.73[/C][C]105.348[/C][C]104.724[/C][C]0.623611[/C][C]-0.617778[/C][/ROW]
[ROW][C]58[/C][C]104.33[/C][C]105.302[/C][C]104.929[/C][C]0.372528[/C][C]-0.971694[/C][/ROW]
[ROW][C]59[/C][C]104.6[/C][C]105.211[/C][C]105.103[/C][C]0.108028[/C][C]-0.610944[/C][/ROW]
[ROW][C]60[/C][C]104.41[/C][C]104.582[/C][C]105.27[/C][C]-0.688056[/C][C]-0.171944[/C][/ROW]
[ROW][C]61[/C][C]104.63[/C][C]105.061[/C][C]105.422[/C][C]-0.361972[/C][C]-0.430528[/C][/ROW]
[ROW][C]62[/C][C]105.55[/C][C]105.416[/C][C]105.58[/C][C]-0.164389[/C][C]0.134389[/C][/ROW]
[ROW][C]63[/C][C]106.12[/C][C]106.289[/C][C]105.755[/C][C]0.533694[/C][C]-0.169111[/C][/ROW]
[ROW][C]64[/C][C]106.62[/C][C]105.999[/C][C]105.947[/C][C]0.0521944[/C][C]0.620722[/C][/ROW]
[ROW][C]65[/C][C]106.72[/C][C]106.105[/C][C]106.195[/C][C]-0.0893056[/C][C]0.614722[/C][/ROW]
[ROW][C]66[/C][C]106.52[/C][C]106.373[/C][C]106.485[/C][C]-0.111972[/C][C]0.146556[/C][/ROW]
[ROW][C]67[/C][C]106.79[/C][C]NA[/C][C]NA[/C][C]-0.231056[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]106.95[/C][C]NA[/C][C]NA[/C][C]-0.0433056[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]106.92[/C][C]NA[/C][C]NA[/C][C]0.623611[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]106.74[/C][C]NA[/C][C]NA[/C][C]0.372528[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]108.13[/C][C]NA[/C][C]NA[/C][C]0.108028[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]107.86[/C][C]NA[/C][C]NA[/C][C]-0.688056[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294750&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294750&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	92.94	NA	NA	-0.361972	NA
2	92.97	NA	NA	-0.164389	NA
3	93.37	NA	NA	0.533694	NA
4	92.6	NA	NA	0.0521944	NA
5	92.84	NA	NA	-0.0893056	NA
6	92.55	NA	NA	-0.111972	NA
7	92.93	92.5956	92.8267	-0.231056	0.334389
8	92.44	92.7275	92.7708	-0.0433056	-0.287528
9	93.36	93.2699	92.6463	0.623611	0.0901389
10	93.24	92.85	92.4775	0.372528	0.389972
11	92.65	92.4159	92.3079	0.108028	0.234056
12	92.06	91.5386	92.2267	-0.688056	0.521389
13	92.88	91.8093	92.1712	-0.361972	1.07072
14	91.69	91.9523	92.1167	-0.164389	-0.262278
15	91.66	92.6416	92.1079	0.533694	-0.981611
16	90.26	92.1718	92.1196	0.0521944	-1.91178
17	91.11	92.0711	92.1604	-0.0893056	-0.961111
18	92.33	92.0993	92.2112	-0.111972	0.230722
19	91.82	91.9831	92.2142	-0.231056	-0.163111
20	92.24	92.1913	92.2346	-0.0433056	0.0487222
21	93.35	93.0136	92.39	0.623611	0.336389
22	93.53	93.0171	92.6446	0.372528	0.512889
23	93.34	92.9864	92.8783	0.108028	0.353639
24	92.59	92.3269	93.015	-0.688056	0.263056
25	92.42	92.7739	93.1358	-0.361972	-0.353861
26	92.64	93.1835	93.3479	-0.164389	-0.543528
27	94.44	94.1691	93.6354	0.533694	0.270889
28	93.59	94.0159	93.9637	0.0521944	-0.425944
29	93.39	94.2253	94.3146	-0.0893056	-0.835278
30	93.33	94.5622	94.6742	-0.111972	-1.23219
31	93.72	94.8477	95.0788	-0.231056	-1.12769
32	95.43	95.5338	95.5771	-0.0433056	-0.103778
33	97.06	96.7349	96.1112	0.623611	0.325139
34	97.7	97.0004	96.6279	0.372528	0.699556
35	97.59	97.2493	97.1412	0.108028	0.340722
36	96.97	96.974	97.6621	-0.688056	-0.00402778
37	97.75	97.8184	98.1804	-0.361972	-0.0684444
38	99.27	98.466	98.6304	-0.164389	0.803972
39	100.63	99.5308	98.9971	0.533694	1.09922
40	99.8	99.3418	99.2896	0.0521944	0.458222
41	99.5	99.4715	99.5608	-0.0893056	0.0284722
42	99.72	99.7418	99.8537	-0.111972	-0.0217778
43	99.77	99.9285	100.16	-0.231056	-0.158528
44	100.18	100.403	100.446	-0.0433056	-0.222944
45	101.11	101.306	100.682	0.623611	-0.195694
46	100.67	101.363	100.99	0.372528	-0.692528
47	101.13	101.509	101.401	0.108028	-0.379278
48	100.46	101.13	101.818	-0.688056	-0.670278
49	101.6	101.88	102.242	-0.361972	-0.279694
50	102.3	102.494	102.659	-0.164389	-0.194361
51	103.26	103.541	103.008	0.533694	-0.281194
52	104.56	103.363	103.311	0.0521944	1.19697
53	104.61	103.519	103.608	-0.0893056	1.09139
54	104.62	103.805	103.917	-0.111972	0.814889
55	105.03	103.977	104.208	-0.231056	1.05314
56	104.93	104.426	104.47	-0.0433056	0.503722
57	104.73	105.348	104.724	0.623611	-0.617778
58	104.33	105.302	104.929	0.372528	-0.971694
59	104.6	105.211	105.103	0.108028	-0.610944
60	104.41	104.582	105.27	-0.688056	-0.171944
61	104.63	105.061	105.422	-0.361972	-0.430528
62	105.55	105.416	105.58	-0.164389	0.134389
63	106.12	106.289	105.755	0.533694	-0.169111
64	106.62	105.999	105.947	0.0521944	0.620722
65	106.72	106.105	106.195	-0.0893056	0.614722
66	106.52	106.373	106.485	-0.111972	0.146556
67	106.79	NA	NA	-0.231056	NA
68	106.95	NA	NA	-0.0433056	NA
69	106.92	NA	NA	0.623611	NA
70	106.74	NA	NA	0.372528	NA
71	108.13	NA	NA	0.108028	NA
72	107.86	NA	NA	-0.688056	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