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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 01 May 2017 11:28:29 +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/2017/May/01/t1493634578n0n0ktzqjf5i50t.htm/, Retrieved Wed, 15 May 2024 20:53:36 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Wed, 15 May 2024 20:53:36 +0200

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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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

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The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	79.92	NA	NA	-0.473222	NA
2	80.26	NA	NA	-0.497722	NA
3	80.69	NA	NA	-0.773806	NA
4	84.5	NA	NA	0.696611	NA
5	85.45	NA	NA	0.613611	NA
6	86.19	NA	NA	0.769528	NA
7	86.4	85.7747	84.7838	0.990944	0.625306
8	85.98	85.8316	85.3267	0.504944	0.148389
9	85.87	85.8614	85.8525	0.00894444	0.00855556
10	86.06	85.9463	86.3746	-0.428306	0.113722
11	86.43	86.2744	86.9433	-0.668972	0.155639
12	86.43	86.8174	87.56	-0.742556	-0.387444
13	86.37	87.7301	88.2033	-0.473222	-1.36011
14	86.84	88.3652	88.8629	-0.497722	-1.52519
15	86.73	88.7404	89.5142	-0.773806	-2.01036
16	90.99	90.8279	90.1313	0.696611	0.162139
17	92.61	91.3732	90.7596	0.613611	1.23681
18	93.83	92.1945	91.425	0.769528	1.63547
19	94.2	93.0959	92.105	0.990944	1.10406
20	94.01	93.2795	92.7746	0.504944	0.730472
21	93.47	93.4414	93.4325	0.00894444	0.0285556
22	93.27	93.5667	93.995	-0.428306	-0.296694
23	94.3	93.7464	94.4154	-0.668972	0.553556
24	94.53	94.007	94.7496	-0.742556	0.522972
25	94.59	94.5789	95.0521	-0.473222	0.0111389
26	94.69	94.8981	95.3958	-0.497722	-0.208111
27	94.67	95.0437	95.8175	-0.773806	-0.373694
28	96.55	96.9916	96.295	0.696611	-0.441611
29	97.14	97.3369	96.7233	0.613611	-0.196944
30	97.32	97.8733	97.1037	0.769528	-0.553278
31	97.97	98.4984	97.5075	0.990944	-0.528444
32	98.49	98.4237	97.9187	0.504944	0.0663056
33	99.11	98.3385	98.3296	0.00894444	0.771472
34	99.09	98.285	98.7133	-0.428306	0.804972
35	98.76	98.3544	99.0233	-0.668972	0.405639
36	99.2	98.5604	99.3029	-0.742556	0.639639
37	99.61	99.0751	99.5483	-0.473222	0.534889
38	99.54	99.2306	99.7283	-0.497722	0.309389
39	99.68	99.0758	99.8496	-0.773806	0.604222
40	100.75	100.626	99.9296	0.696611	0.123806
41	100.38	100.598	99.9846	0.613611	-0.218194
42	100.79	100.77	100	0.769528	0.0200556
43	100.39	100.989	99.9983	0.990944	-0.599278
44	100.39	100.52	100.015	0.504944	-0.129944
45	100.12	100.041	100.032	0.00894444	0.0785556
46	100	99.6159	100.044	-0.428306	0.384139
47	99.17	99.4123	100.081	-0.668972	-0.242278
48	99.17	99.3887	100.131	-0.742556	-0.218694
49	99.59	99.743	100.216	-0.473222	-0.153028
50	99.96	99.826	100.324	-0.497722	0.133972
51	99.68	99.6491	100.423	-0.773806	0.0308889
52	101.03	101.222	100.526	0.696611	-0.192444
53	100.99	101.285	100.672	0.613611	-0.295278
54	101.38	101.654	100.884	0.769528	-0.273694
55	101.84	102.178	101.188	0.990944	-0.338444
56	101.52	102.072	101.567	0.504944	-0.552028
57	101.37	101.994	101.985	0.00894444	-0.623944
58	101.22	101.963	102.391	-0.428306	-0.742944
59	101.45	102.059	102.728	-0.668972	-0.609361
60	101.99	102.283	103.026	-0.742556	-0.293278
61	104.05	102.82	103.293	-0.473222	1.23031
62	104.61	103.057	103.555	-0.497722	1.55314
63	105.06	103.048	103.822	-0.773806	2.01214
64	105.4	104.789	104.092	0.696611	0.611306
65	104.71	104.973	104.36	0.613611	-0.263194
66	104.8	105.365	104.596	0.769528	-0.565361
67	104.83	NA	NA	0.990944	NA
68	104.81	NA	NA	0.504944	NA
69	104.49	NA	NA	0.00894444	NA
70	104.59	NA	NA	-0.428306	NA
71	104.5	NA	NA	-0.668972	NA
72	104.61	NA	NA	-0.742556	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 79.92 & NA & NA & -0.473222 & NA \tabularnewline
2 & 80.26 & NA & NA & -0.497722 & NA \tabularnewline
3 & 80.69 & NA & NA & -0.773806 & NA \tabularnewline
4 & 84.5 & NA & NA & 0.696611 & NA \tabularnewline
5 & 85.45 & NA & NA & 0.613611 & NA \tabularnewline
6 & 86.19 & NA & NA & 0.769528 & NA \tabularnewline
7 & 86.4 & 85.7747 & 84.7838 & 0.990944 & 0.625306 \tabularnewline
8 & 85.98 & 85.8316 & 85.3267 & 0.504944 & 0.148389 \tabularnewline
9 & 85.87 & 85.8614 & 85.8525 & 0.00894444 & 0.00855556 \tabularnewline
10 & 86.06 & 85.9463 & 86.3746 & -0.428306 & 0.113722 \tabularnewline
11 & 86.43 & 86.2744 & 86.9433 & -0.668972 & 0.155639 \tabularnewline
12 & 86.43 & 86.8174 & 87.56 & -0.742556 & -0.387444 \tabularnewline
13 & 86.37 & 87.7301 & 88.2033 & -0.473222 & -1.36011 \tabularnewline
14 & 86.84 & 88.3652 & 88.8629 & -0.497722 & -1.52519 \tabularnewline
15 & 86.73 & 88.7404 & 89.5142 & -0.773806 & -2.01036 \tabularnewline
16 & 90.99 & 90.8279 & 90.1313 & 0.696611 & 0.162139 \tabularnewline
17 & 92.61 & 91.3732 & 90.7596 & 0.613611 & 1.23681 \tabularnewline
18 & 93.83 & 92.1945 & 91.425 & 0.769528 & 1.63547 \tabularnewline
19 & 94.2 & 93.0959 & 92.105 & 0.990944 & 1.10406 \tabularnewline
20 & 94.01 & 93.2795 & 92.7746 & 0.504944 & 0.730472 \tabularnewline
21 & 93.47 & 93.4414 & 93.4325 & 0.00894444 & 0.0285556 \tabularnewline
22 & 93.27 & 93.5667 & 93.995 & -0.428306 & -0.296694 \tabularnewline
23 & 94.3 & 93.7464 & 94.4154 & -0.668972 & 0.553556 \tabularnewline
24 & 94.53 & 94.007 & 94.7496 & -0.742556 & 0.522972 \tabularnewline
25 & 94.59 & 94.5789 & 95.0521 & -0.473222 & 0.0111389 \tabularnewline
26 & 94.69 & 94.8981 & 95.3958 & -0.497722 & -0.208111 \tabularnewline
27 & 94.67 & 95.0437 & 95.8175 & -0.773806 & -0.373694 \tabularnewline
28 & 96.55 & 96.9916 & 96.295 & 0.696611 & -0.441611 \tabularnewline
29 & 97.14 & 97.3369 & 96.7233 & 0.613611 & -0.196944 \tabularnewline
30 & 97.32 & 97.8733 & 97.1037 & 0.769528 & -0.553278 \tabularnewline
31 & 97.97 & 98.4984 & 97.5075 & 0.990944 & -0.528444 \tabularnewline
32 & 98.49 & 98.4237 & 97.9187 & 0.504944 & 0.0663056 \tabularnewline
33 & 99.11 & 98.3385 & 98.3296 & 0.00894444 & 0.771472 \tabularnewline
34 & 99.09 & 98.285 & 98.7133 & -0.428306 & 0.804972 \tabularnewline
35 & 98.76 & 98.3544 & 99.0233 & -0.668972 & 0.405639 \tabularnewline
36 & 99.2 & 98.5604 & 99.3029 & -0.742556 & 0.639639 \tabularnewline
37 & 99.61 & 99.0751 & 99.5483 & -0.473222 & 0.534889 \tabularnewline
38 & 99.54 & 99.2306 & 99.7283 & -0.497722 & 0.309389 \tabularnewline
39 & 99.68 & 99.0758 & 99.8496 & -0.773806 & 0.604222 \tabularnewline
40 & 100.75 & 100.626 & 99.9296 & 0.696611 & 0.123806 \tabularnewline
41 & 100.38 & 100.598 & 99.9846 & 0.613611 & -0.218194 \tabularnewline
42 & 100.79 & 100.77 & 100 & 0.769528 & 0.0200556 \tabularnewline
43 & 100.39 & 100.989 & 99.9983 & 0.990944 & -0.599278 \tabularnewline
44 & 100.39 & 100.52 & 100.015 & 0.504944 & -0.129944 \tabularnewline
45 & 100.12 & 100.041 & 100.032 & 0.00894444 & 0.0785556 \tabularnewline
46 & 100 & 99.6159 & 100.044 & -0.428306 & 0.384139 \tabularnewline
47 & 99.17 & 99.4123 & 100.081 & -0.668972 & -0.242278 \tabularnewline
48 & 99.17 & 99.3887 & 100.131 & -0.742556 & -0.218694 \tabularnewline
49 & 99.59 & 99.743 & 100.216 & -0.473222 & -0.153028 \tabularnewline
50 & 99.96 & 99.826 & 100.324 & -0.497722 & 0.133972 \tabularnewline
51 & 99.68 & 99.6491 & 100.423 & -0.773806 & 0.0308889 \tabularnewline
52 & 101.03 & 101.222 & 100.526 & 0.696611 & -0.192444 \tabularnewline
53 & 100.99 & 101.285 & 100.672 & 0.613611 & -0.295278 \tabularnewline
54 & 101.38 & 101.654 & 100.884 & 0.769528 & -0.273694 \tabularnewline
55 & 101.84 & 102.178 & 101.188 & 0.990944 & -0.338444 \tabularnewline
56 & 101.52 & 102.072 & 101.567 & 0.504944 & -0.552028 \tabularnewline
57 & 101.37 & 101.994 & 101.985 & 0.00894444 & -0.623944 \tabularnewline
58 & 101.22 & 101.963 & 102.391 & -0.428306 & -0.742944 \tabularnewline
59 & 101.45 & 102.059 & 102.728 & -0.668972 & -0.609361 \tabularnewline
60 & 101.99 & 102.283 & 103.026 & -0.742556 & -0.293278 \tabularnewline
61 & 104.05 & 102.82 & 103.293 & -0.473222 & 1.23031 \tabularnewline
62 & 104.61 & 103.057 & 103.555 & -0.497722 & 1.55314 \tabularnewline
63 & 105.06 & 103.048 & 103.822 & -0.773806 & 2.01214 \tabularnewline
64 & 105.4 & 104.789 & 104.092 & 0.696611 & 0.611306 \tabularnewline
65 & 104.71 & 104.973 & 104.36 & 0.613611 & -0.263194 \tabularnewline
66 & 104.8 & 105.365 & 104.596 & 0.769528 & -0.565361 \tabularnewline
67 & 104.83 & NA & NA & 0.990944 & NA \tabularnewline
68 & 104.81 & NA & NA & 0.504944 & NA \tabularnewline
69 & 104.49 & NA & NA & 0.00894444 & NA \tabularnewline
70 & 104.59 & NA & NA & -0.428306 & NA \tabularnewline
71 & 104.5 & NA & NA & -0.668972 & NA \tabularnewline
72 & 104.61 & NA & NA & -0.742556 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]79.92[/C][C]NA[/C][C]NA[/C][C]-0.473222[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]80.26[/C][C]NA[/C][C]NA[/C][C]-0.497722[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]80.69[/C][C]NA[/C][C]NA[/C][C]-0.773806[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]84.5[/C][C]NA[/C][C]NA[/C][C]0.696611[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]85.45[/C][C]NA[/C][C]NA[/C][C]0.613611[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]86.19[/C][C]NA[/C][C]NA[/C][C]0.769528[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]86.4[/C][C]85.7747[/C][C]84.7838[/C][C]0.990944[/C][C]0.625306[/C][/ROW]
[ROW][C]8[/C][C]85.98[/C][C]85.8316[/C][C]85.3267[/C][C]0.504944[/C][C]0.148389[/C][/ROW]
[ROW][C]9[/C][C]85.87[/C][C]85.8614[/C][C]85.8525[/C][C]0.00894444[/C][C]0.00855556[/C][/ROW]
[ROW][C]10[/C][C]86.06[/C][C]85.9463[/C][C]86.3746[/C][C]-0.428306[/C][C]0.113722[/C][/ROW]
[ROW][C]11[/C][C]86.43[/C][C]86.2744[/C][C]86.9433[/C][C]-0.668972[/C][C]0.155639[/C][/ROW]
[ROW][C]12[/C][C]86.43[/C][C]86.8174[/C][C]87.56[/C][C]-0.742556[/C][C]-0.387444[/C][/ROW]
[ROW][C]13[/C][C]86.37[/C][C]87.7301[/C][C]88.2033[/C][C]-0.473222[/C][C]-1.36011[/C][/ROW]
[ROW][C]14[/C][C]86.84[/C][C]88.3652[/C][C]88.8629[/C][C]-0.497722[/C][C]-1.52519[/C][/ROW]
[ROW][C]15[/C][C]86.73[/C][C]88.7404[/C][C]89.5142[/C][C]-0.773806[/C][C]-2.01036[/C][/ROW]
[ROW][C]16[/C][C]90.99[/C][C]90.8279[/C][C]90.1313[/C][C]0.696611[/C][C]0.162139[/C][/ROW]
[ROW][C]17[/C][C]92.61[/C][C]91.3732[/C][C]90.7596[/C][C]0.613611[/C][C]1.23681[/C][/ROW]
[ROW][C]18[/C][C]93.83[/C][C]92.1945[/C][C]91.425[/C][C]0.769528[/C][C]1.63547[/C][/ROW]
[ROW][C]19[/C][C]94.2[/C][C]93.0959[/C][C]92.105[/C][C]0.990944[/C][C]1.10406[/C][/ROW]
[ROW][C]20[/C][C]94.01[/C][C]93.2795[/C][C]92.7746[/C][C]0.504944[/C][C]0.730472[/C][/ROW]
[ROW][C]21[/C][C]93.47[/C][C]93.4414[/C][C]93.4325[/C][C]0.00894444[/C][C]0.0285556[/C][/ROW]
[ROW][C]22[/C][C]93.27[/C][C]93.5667[/C][C]93.995[/C][C]-0.428306[/C][C]-0.296694[/C][/ROW]
[ROW][C]23[/C][C]94.3[/C][C]93.7464[/C][C]94.4154[/C][C]-0.668972[/C][C]0.553556[/C][/ROW]
[ROW][C]24[/C][C]94.53[/C][C]94.007[/C][C]94.7496[/C][C]-0.742556[/C][C]0.522972[/C][/ROW]
[ROW][C]25[/C][C]94.59[/C][C]94.5789[/C][C]95.0521[/C][C]-0.473222[/C][C]0.0111389[/C][/ROW]
[ROW][C]26[/C][C]94.69[/C][C]94.8981[/C][C]95.3958[/C][C]-0.497722[/C][C]-0.208111[/C][/ROW]
[ROW][C]27[/C][C]94.67[/C][C]95.0437[/C][C]95.8175[/C][C]-0.773806[/C][C]-0.373694[/C][/ROW]
[ROW][C]28[/C][C]96.55[/C][C]96.9916[/C][C]96.295[/C][C]0.696611[/C][C]-0.441611[/C][/ROW]
[ROW][C]29[/C][C]97.14[/C][C]97.3369[/C][C]96.7233[/C][C]0.613611[/C][C]-0.196944[/C][/ROW]
[ROW][C]30[/C][C]97.32[/C][C]97.8733[/C][C]97.1037[/C][C]0.769528[/C][C]-0.553278[/C][/ROW]
[ROW][C]31[/C][C]97.97[/C][C]98.4984[/C][C]97.5075[/C][C]0.990944[/C][C]-0.528444[/C][/ROW]
[ROW][C]32[/C][C]98.49[/C][C]98.4237[/C][C]97.9187[/C][C]0.504944[/C][C]0.0663056[/C][/ROW]
[ROW][C]33[/C][C]99.11[/C][C]98.3385[/C][C]98.3296[/C][C]0.00894444[/C][C]0.771472[/C][/ROW]
[ROW][C]34[/C][C]99.09[/C][C]98.285[/C][C]98.7133[/C][C]-0.428306[/C][C]0.804972[/C][/ROW]
[ROW][C]35[/C][C]98.76[/C][C]98.3544[/C][C]99.0233[/C][C]-0.668972[/C][C]0.405639[/C][/ROW]
[ROW][C]36[/C][C]99.2[/C][C]98.5604[/C][C]99.3029[/C][C]-0.742556[/C][C]0.639639[/C][/ROW]
[ROW][C]37[/C][C]99.61[/C][C]99.0751[/C][C]99.5483[/C][C]-0.473222[/C][C]0.534889[/C][/ROW]
[ROW][C]38[/C][C]99.54[/C][C]99.2306[/C][C]99.7283[/C][C]-0.497722[/C][C]0.309389[/C][/ROW]
[ROW][C]39[/C][C]99.68[/C][C]99.0758[/C][C]99.8496[/C][C]-0.773806[/C][C]0.604222[/C][/ROW]
[ROW][C]40[/C][C]100.75[/C][C]100.626[/C][C]99.9296[/C][C]0.696611[/C][C]0.123806[/C][/ROW]
[ROW][C]41[/C][C]100.38[/C][C]100.598[/C][C]99.9846[/C][C]0.613611[/C][C]-0.218194[/C][/ROW]
[ROW][C]42[/C][C]100.79[/C][C]100.77[/C][C]100[/C][C]0.769528[/C][C]0.0200556[/C][/ROW]
[ROW][C]43[/C][C]100.39[/C][C]100.989[/C][C]99.9983[/C][C]0.990944[/C][C]-0.599278[/C][/ROW]
[ROW][C]44[/C][C]100.39[/C][C]100.52[/C][C]100.015[/C][C]0.504944[/C][C]-0.129944[/C][/ROW]
[ROW][C]45[/C][C]100.12[/C][C]100.041[/C][C]100.032[/C][C]0.00894444[/C][C]0.0785556[/C][/ROW]
[ROW][C]46[/C][C]100[/C][C]99.6159[/C][C]100.044[/C][C]-0.428306[/C][C]0.384139[/C][/ROW]
[ROW][C]47[/C][C]99.17[/C][C]99.4123[/C][C]100.081[/C][C]-0.668972[/C][C]-0.242278[/C][/ROW]
[ROW][C]48[/C][C]99.17[/C][C]99.3887[/C][C]100.131[/C][C]-0.742556[/C][C]-0.218694[/C][/ROW]
[ROW][C]49[/C][C]99.59[/C][C]99.743[/C][C]100.216[/C][C]-0.473222[/C][C]-0.153028[/C][/ROW]
[ROW][C]50[/C][C]99.96[/C][C]99.826[/C][C]100.324[/C][C]-0.497722[/C][C]0.133972[/C][/ROW]
[ROW][C]51[/C][C]99.68[/C][C]99.6491[/C][C]100.423[/C][C]-0.773806[/C][C]0.0308889[/C][/ROW]
[ROW][C]52[/C][C]101.03[/C][C]101.222[/C][C]100.526[/C][C]0.696611[/C][C]-0.192444[/C][/ROW]
[ROW][C]53[/C][C]100.99[/C][C]101.285[/C][C]100.672[/C][C]0.613611[/C][C]-0.295278[/C][/ROW]
[ROW][C]54[/C][C]101.38[/C][C]101.654[/C][C]100.884[/C][C]0.769528[/C][C]-0.273694[/C][/ROW]
[ROW][C]55[/C][C]101.84[/C][C]102.178[/C][C]101.188[/C][C]0.990944[/C][C]-0.338444[/C][/ROW]
[ROW][C]56[/C][C]101.52[/C][C]102.072[/C][C]101.567[/C][C]0.504944[/C][C]-0.552028[/C][/ROW]
[ROW][C]57[/C][C]101.37[/C][C]101.994[/C][C]101.985[/C][C]0.00894444[/C][C]-0.623944[/C][/ROW]
[ROW][C]58[/C][C]101.22[/C][C]101.963[/C][C]102.391[/C][C]-0.428306[/C][C]-0.742944[/C][/ROW]
[ROW][C]59[/C][C]101.45[/C][C]102.059[/C][C]102.728[/C][C]-0.668972[/C][C]-0.609361[/C][/ROW]
[ROW][C]60[/C][C]101.99[/C][C]102.283[/C][C]103.026[/C][C]-0.742556[/C][C]-0.293278[/C][/ROW]
[ROW][C]61[/C][C]104.05[/C][C]102.82[/C][C]103.293[/C][C]-0.473222[/C][C]1.23031[/C][/ROW]
[ROW][C]62[/C][C]104.61[/C][C]103.057[/C][C]103.555[/C][C]-0.497722[/C][C]1.55314[/C][/ROW]
[ROW][C]63[/C][C]105.06[/C][C]103.048[/C][C]103.822[/C][C]-0.773806[/C][C]2.01214[/C][/ROW]
[ROW][C]64[/C][C]105.4[/C][C]104.789[/C][C]104.092[/C][C]0.696611[/C][C]0.611306[/C][/ROW]
[ROW][C]65[/C][C]104.71[/C][C]104.973[/C][C]104.36[/C][C]0.613611[/C][C]-0.263194[/C][/ROW]
[ROW][C]66[/C][C]104.8[/C][C]105.365[/C][C]104.596[/C][C]0.769528[/C][C]-0.565361[/C][/ROW]
[ROW][C]67[/C][C]104.83[/C][C]NA[/C][C]NA[/C][C]0.990944[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]104.81[/C][C]NA[/C][C]NA[/C][C]0.504944[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]104.49[/C][C]NA[/C][C]NA[/C][C]0.00894444[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]104.59[/C][C]NA[/C][C]NA[/C][C]-0.428306[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]104.5[/C][C]NA[/C][C]NA[/C][C]-0.668972[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]104.61[/C][C]NA[/C][C]NA[/C][C]-0.742556[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	79.92	NA	NA	-0.473222	NA
2	80.26	NA	NA	-0.497722	NA
3	80.69	NA	NA	-0.773806	NA
4	84.5	NA	NA	0.696611	NA
5	85.45	NA	NA	0.613611	NA
6	86.19	NA	NA	0.769528	NA
7	86.4	85.7747	84.7838	0.990944	0.625306
8	85.98	85.8316	85.3267	0.504944	0.148389
9	85.87	85.8614	85.8525	0.00894444	0.00855556
10	86.06	85.9463	86.3746	-0.428306	0.113722
11	86.43	86.2744	86.9433	-0.668972	0.155639
12	86.43	86.8174	87.56	-0.742556	-0.387444
13	86.37	87.7301	88.2033	-0.473222	-1.36011
14	86.84	88.3652	88.8629	-0.497722	-1.52519
15	86.73	88.7404	89.5142	-0.773806	-2.01036
16	90.99	90.8279	90.1313	0.696611	0.162139
17	92.61	91.3732	90.7596	0.613611	1.23681
18	93.83	92.1945	91.425	0.769528	1.63547
19	94.2	93.0959	92.105	0.990944	1.10406
20	94.01	93.2795	92.7746	0.504944	0.730472
21	93.47	93.4414	93.4325	0.00894444	0.0285556
22	93.27	93.5667	93.995	-0.428306	-0.296694
23	94.3	93.7464	94.4154	-0.668972	0.553556
24	94.53	94.007	94.7496	-0.742556	0.522972
25	94.59	94.5789	95.0521	-0.473222	0.0111389
26	94.69	94.8981	95.3958	-0.497722	-0.208111
27	94.67	95.0437	95.8175	-0.773806	-0.373694
28	96.55	96.9916	96.295	0.696611	-0.441611
29	97.14	97.3369	96.7233	0.613611	-0.196944
30	97.32	97.8733	97.1037	0.769528	-0.553278
31	97.97	98.4984	97.5075	0.990944	-0.528444
32	98.49	98.4237	97.9187	0.504944	0.0663056
33	99.11	98.3385	98.3296	0.00894444	0.771472
34	99.09	98.285	98.7133	-0.428306	0.804972
35	98.76	98.3544	99.0233	-0.668972	0.405639
36	99.2	98.5604	99.3029	-0.742556	0.639639
37	99.61	99.0751	99.5483	-0.473222	0.534889
38	99.54	99.2306	99.7283	-0.497722	0.309389
39	99.68	99.0758	99.8496	-0.773806	0.604222
40	100.75	100.626	99.9296	0.696611	0.123806
41	100.38	100.598	99.9846	0.613611	-0.218194
42	100.79	100.77	100	0.769528	0.0200556
43	100.39	100.989	99.9983	0.990944	-0.599278
44	100.39	100.52	100.015	0.504944	-0.129944
45	100.12	100.041	100.032	0.00894444	0.0785556
46	100	99.6159	100.044	-0.428306	0.384139
47	99.17	99.4123	100.081	-0.668972	-0.242278
48	99.17	99.3887	100.131	-0.742556	-0.218694
49	99.59	99.743	100.216	-0.473222	-0.153028
50	99.96	99.826	100.324	-0.497722	0.133972
51	99.68	99.6491	100.423	-0.773806	0.0308889
52	101.03	101.222	100.526	0.696611	-0.192444
53	100.99	101.285	100.672	0.613611	-0.295278
54	101.38	101.654	100.884	0.769528	-0.273694
55	101.84	102.178	101.188	0.990944	-0.338444
56	101.52	102.072	101.567	0.504944	-0.552028
57	101.37	101.994	101.985	0.00894444	-0.623944
58	101.22	101.963	102.391	-0.428306	-0.742944
59	101.45	102.059	102.728	-0.668972	-0.609361
60	101.99	102.283	103.026	-0.742556	-0.293278
61	104.05	102.82	103.293	-0.473222	1.23031
62	104.61	103.057	103.555	-0.497722	1.55314
63	105.06	103.048	103.822	-0.773806	2.01214
64	105.4	104.789	104.092	0.696611	0.611306
65	104.71	104.973	104.36	0.613611	-0.263194
66	104.8	105.365	104.596	0.769528	-0.565361
67	104.83	NA	NA	0.990944	NA
68	104.81	NA	NA	0.504944	NA
69	104.49	NA	NA	0.00894444	NA
70	104.59	NA	NA	-0.428306	NA
71	104.5	NA	NA	-0.668972	NA
72	104.61	NA	NA	-0.742556	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