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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 27 Nov 2014 08:52:44 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/27/t14170783752l6styr9fpcdx4o.htm/, Retrieved Fri, 17 May 2024 06:40:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=259529, Retrieved Fri, 17 May 2024 06:40:13 +0000

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105

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-       [Classical Decomposition] [] [2014-11-27 08:52:44] [3bbf952604bb7b6db5ab93a0a8bc191d] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259529&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259529&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259529&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.4718	NA	NA	-0.00562056	NA
2	1.4748	NA	NA	-0.00921139	NA
3	1.5527	NA	NA	-0.00537222	NA
4	1.5751	NA	NA	0.00407861	NA
5	1.5557	NA	NA	-0.0146364	NA
6	1.5553	NA	NA	-0.0156231	NA
7	1.577	1.47834	1.46444	0.0139061	0.0986564
8	1.4975	1.46035	1.4501	0.0102553	0.0371489
9	1.437	1.44004	1.4316	0.00844861	-0.00304444
10	1.3322	1.42528	1.4106	0.0146753	-0.0930794
11	1.2732	1.39058	1.39199	-0.00140806	-0.117379
12	1.3449	1.37815	1.37764	0.000507778	-0.0332453
13	1.3239	1.3586	1.36422	-0.00562056	-0.0347044
14	1.2785	1.34506	1.35427	-0.00921139	-0.0665594
15	1.305	1.34675	1.35212	-0.00537222	-0.0417528
16	1.319	1.36323	1.35915	0.00407861	-0.0442286
17	1.365	1.35983	1.37447	-0.0146364	0.00516972
18	1.4016	1.37279	1.38841	-0.0156231	0.0288106
19	1.4088	1.41148	1.39757	0.0139061	-0.00267694
20	1.4268	1.41588	1.40563	0.0102553	0.0109156
21	1.4562	1.41999	1.41155	0.00844861	0.0362056
22	1.4816	1.42928	1.41461	0.0146753	0.0523164
23	1.4914	1.40958	1.41099	-0.00140806	0.0818206
24	1.4614	1.39945	1.39894	0.000507778	0.0619547
25	1.4272	1.3803	1.38592	-0.00562056	0.0469039
26	1.3686	1.36549	1.3747	-0.00921139	0.00311139
27	1.3569	1.35737	1.36275	-0.00537222	-0.000473611
28	1.3406	1.35677	1.35269	0.00407861	-0.0161703
29	1.2565	1.32901	1.34365	-0.0146364	-0.0725094
30	1.2209	1.31699	1.33262	-0.0156231	-0.0960936
31	1.277	1.33691	1.32301	0.0139061	-0.0599144
32	1.2894	1.32931	1.31905	0.0102553	-0.0399094
33	1.3067	1.32914	1.32069	0.00844861	-0.0224403
34	1.3898	1.34148	1.3268	0.0146753	0.0483247
35	1.3661	1.33714	1.33855	-0.00140806	0.0289581
36	1.322	1.35557	1.35506	0.000507778	-0.0335703
37	1.336	1.36475	1.37037	-0.00562056	-0.0287461
38	1.3649	1.37342	1.38263	-0.00921139	-0.00851778
39	1.3999	1.38622	1.3916	-0.00537222	0.0136764
40	1.4442	1.3978	1.39372	0.00407861	0.0463964
41	1.4349	1.37785	1.39249	-0.0146364	0.0570489
42	1.4388	1.37626	1.39188	-0.0156231	0.0625439
43	1.4264	1.40372	1.38981	0.0139061	0.0226814
44	1.4343	1.3964	1.38615	0.0102553	0.0378989
45	1.377	1.3895	1.38105	0.00844861	-0.0124986
46	1.3706	1.38707	1.37239	0.0146753	-0.0164669
47	1.3556	1.35915	1.36056	-0.00140806	-0.00355028
48	1.3179	1.34681	1.3463	0.000507778	-0.0289078
49	1.2905	1.32469	1.33031	-0.00562056	-0.0341878
50	1.3224	1.30477	1.31398	-0.00921139	0.0176322
51	1.3201	1.2967	1.30207	-0.00537222	0.0233972
52	1.3162	1.2993	1.29522	0.00407861	0.0169047
53	1.2789	1.2745	1.28913	-0.0146364	0.00440306
54	1.2526	1.27023	1.28585	-0.0156231	-0.0176269
55	1.2288	1.3011	1.2872	0.0139061	-0.0723019
56	1.24	1.29961	1.28935	0.0102553	-0.0596094
57	1.2856	1.29738	1.28893	0.00844861	-0.0117778
58	1.2974	1.30205	1.28738	0.0146753	-0.00465028
59	1.2828	1.2862	1.28761	-0.00140806	-0.00340444
60	1.3119	1.29169	1.29118	0.000507778	0.0202131
61	1.3288	1.29162	1.29724	-0.00562056	0.0371789
62	1.3359	1.29512	1.30433	-0.00921139	0.0407781
63	1.2964	1.3048	1.31018	-0.00537222	-0.00840278
64	1.3026	1.31906	1.31498	0.00407861	-0.0164578
65	1.2982	1.30587	1.3205	-0.0146364	-0.00766778
66	1.3189	1.31009	1.32571	-0.0156231	0.00881056
67	1.308	NA	NA	0.0139061	NA
68	1.331	NA	NA	0.0102553	NA
69	1.3348	NA	NA	0.00844861	NA
70	1.3635	NA	NA	0.0146753	NA
71	1.3493	NA	NA	-0.00140806	NA
72	1.3704	NA	NA	0.000507778	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.4718 & NA & NA & -0.00562056 & NA \tabularnewline
2 & 1.4748 & NA & NA & -0.00921139 & NA \tabularnewline
3 & 1.5527 & NA & NA & -0.00537222 & NA \tabularnewline
4 & 1.5751 & NA & NA & 0.00407861 & NA \tabularnewline
5 & 1.5557 & NA & NA & -0.0146364 & NA \tabularnewline
6 & 1.5553 & NA & NA & -0.0156231 & NA \tabularnewline
7 & 1.577 & 1.47834 & 1.46444 & 0.0139061 & 0.0986564 \tabularnewline
8 & 1.4975 & 1.46035 & 1.4501 & 0.0102553 & 0.0371489 \tabularnewline
9 & 1.437 & 1.44004 & 1.4316 & 0.00844861 & -0.00304444 \tabularnewline
10 & 1.3322 & 1.42528 & 1.4106 & 0.0146753 & -0.0930794 \tabularnewline
11 & 1.2732 & 1.39058 & 1.39199 & -0.00140806 & -0.117379 \tabularnewline
12 & 1.3449 & 1.37815 & 1.37764 & 0.000507778 & -0.0332453 \tabularnewline
13 & 1.3239 & 1.3586 & 1.36422 & -0.00562056 & -0.0347044 \tabularnewline
14 & 1.2785 & 1.34506 & 1.35427 & -0.00921139 & -0.0665594 \tabularnewline
15 & 1.305 & 1.34675 & 1.35212 & -0.00537222 & -0.0417528 \tabularnewline
16 & 1.319 & 1.36323 & 1.35915 & 0.00407861 & -0.0442286 \tabularnewline
17 & 1.365 & 1.35983 & 1.37447 & -0.0146364 & 0.00516972 \tabularnewline
18 & 1.4016 & 1.37279 & 1.38841 & -0.0156231 & 0.0288106 \tabularnewline
19 & 1.4088 & 1.41148 & 1.39757 & 0.0139061 & -0.00267694 \tabularnewline
20 & 1.4268 & 1.41588 & 1.40563 & 0.0102553 & 0.0109156 \tabularnewline
21 & 1.4562 & 1.41999 & 1.41155 & 0.00844861 & 0.0362056 \tabularnewline
22 & 1.4816 & 1.42928 & 1.41461 & 0.0146753 & 0.0523164 \tabularnewline
23 & 1.4914 & 1.40958 & 1.41099 & -0.00140806 & 0.0818206 \tabularnewline
24 & 1.4614 & 1.39945 & 1.39894 & 0.000507778 & 0.0619547 \tabularnewline
25 & 1.4272 & 1.3803 & 1.38592 & -0.00562056 & 0.0469039 \tabularnewline
26 & 1.3686 & 1.36549 & 1.3747 & -0.00921139 & 0.00311139 \tabularnewline
27 & 1.3569 & 1.35737 & 1.36275 & -0.00537222 & -0.000473611 \tabularnewline
28 & 1.3406 & 1.35677 & 1.35269 & 0.00407861 & -0.0161703 \tabularnewline
29 & 1.2565 & 1.32901 & 1.34365 & -0.0146364 & -0.0725094 \tabularnewline
30 & 1.2209 & 1.31699 & 1.33262 & -0.0156231 & -0.0960936 \tabularnewline
31 & 1.277 & 1.33691 & 1.32301 & 0.0139061 & -0.0599144 \tabularnewline
32 & 1.2894 & 1.32931 & 1.31905 & 0.0102553 & -0.0399094 \tabularnewline
33 & 1.3067 & 1.32914 & 1.32069 & 0.00844861 & -0.0224403 \tabularnewline
34 & 1.3898 & 1.34148 & 1.3268 & 0.0146753 & 0.0483247 \tabularnewline
35 & 1.3661 & 1.33714 & 1.33855 & -0.00140806 & 0.0289581 \tabularnewline
36 & 1.322 & 1.35557 & 1.35506 & 0.000507778 & -0.0335703 \tabularnewline
37 & 1.336 & 1.36475 & 1.37037 & -0.00562056 & -0.0287461 \tabularnewline
38 & 1.3649 & 1.37342 & 1.38263 & -0.00921139 & -0.00851778 \tabularnewline
39 & 1.3999 & 1.38622 & 1.3916 & -0.00537222 & 0.0136764 \tabularnewline
40 & 1.4442 & 1.3978 & 1.39372 & 0.00407861 & 0.0463964 \tabularnewline
41 & 1.4349 & 1.37785 & 1.39249 & -0.0146364 & 0.0570489 \tabularnewline
42 & 1.4388 & 1.37626 & 1.39188 & -0.0156231 & 0.0625439 \tabularnewline
43 & 1.4264 & 1.40372 & 1.38981 & 0.0139061 & 0.0226814 \tabularnewline
44 & 1.4343 & 1.3964 & 1.38615 & 0.0102553 & 0.0378989 \tabularnewline
45 & 1.377 & 1.3895 & 1.38105 & 0.00844861 & -0.0124986 \tabularnewline
46 & 1.3706 & 1.38707 & 1.37239 & 0.0146753 & -0.0164669 \tabularnewline
47 & 1.3556 & 1.35915 & 1.36056 & -0.00140806 & -0.00355028 \tabularnewline
48 & 1.3179 & 1.34681 & 1.3463 & 0.000507778 & -0.0289078 \tabularnewline
49 & 1.2905 & 1.32469 & 1.33031 & -0.00562056 & -0.0341878 \tabularnewline
50 & 1.3224 & 1.30477 & 1.31398 & -0.00921139 & 0.0176322 \tabularnewline
51 & 1.3201 & 1.2967 & 1.30207 & -0.00537222 & 0.0233972 \tabularnewline
52 & 1.3162 & 1.2993 & 1.29522 & 0.00407861 & 0.0169047 \tabularnewline
53 & 1.2789 & 1.2745 & 1.28913 & -0.0146364 & 0.00440306 \tabularnewline
54 & 1.2526 & 1.27023 & 1.28585 & -0.0156231 & -0.0176269 \tabularnewline
55 & 1.2288 & 1.3011 & 1.2872 & 0.0139061 & -0.0723019 \tabularnewline
56 & 1.24 & 1.29961 & 1.28935 & 0.0102553 & -0.0596094 \tabularnewline
57 & 1.2856 & 1.29738 & 1.28893 & 0.00844861 & -0.0117778 \tabularnewline
58 & 1.2974 & 1.30205 & 1.28738 & 0.0146753 & -0.00465028 \tabularnewline
59 & 1.2828 & 1.2862 & 1.28761 & -0.00140806 & -0.00340444 \tabularnewline
60 & 1.3119 & 1.29169 & 1.29118 & 0.000507778 & 0.0202131 \tabularnewline
61 & 1.3288 & 1.29162 & 1.29724 & -0.00562056 & 0.0371789 \tabularnewline
62 & 1.3359 & 1.29512 & 1.30433 & -0.00921139 & 0.0407781 \tabularnewline
63 & 1.2964 & 1.3048 & 1.31018 & -0.00537222 & -0.00840278 \tabularnewline
64 & 1.3026 & 1.31906 & 1.31498 & 0.00407861 & -0.0164578 \tabularnewline
65 & 1.2982 & 1.30587 & 1.3205 & -0.0146364 & -0.00766778 \tabularnewline
66 & 1.3189 & 1.31009 & 1.32571 & -0.0156231 & 0.00881056 \tabularnewline
67 & 1.308 & NA & NA & 0.0139061 & NA \tabularnewline
68 & 1.331 & NA & NA & 0.0102553 & NA \tabularnewline
69 & 1.3348 & NA & NA & 0.00844861 & NA \tabularnewline
70 & 1.3635 & NA & NA & 0.0146753 & NA \tabularnewline
71 & 1.3493 & NA & NA & -0.00140806 & NA \tabularnewline
72 & 1.3704 & NA & NA & 0.000507778 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259529&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]1.4718[/C][C]NA[/C][C]NA[/C][C]-0.00562056[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.4748[/C][C]NA[/C][C]NA[/C][C]-0.00921139[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.5527[/C][C]NA[/C][C]NA[/C][C]-0.00537222[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.5751[/C][C]NA[/C][C]NA[/C][C]0.00407861[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.5557[/C][C]NA[/C][C]NA[/C][C]-0.0146364[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.5553[/C][C]NA[/C][C]NA[/C][C]-0.0156231[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.577[/C][C]1.47834[/C][C]1.46444[/C][C]0.0139061[/C][C]0.0986564[/C][/ROW]
[ROW][C]8[/C][C]1.4975[/C][C]1.46035[/C][C]1.4501[/C][C]0.0102553[/C][C]0.0371489[/C][/ROW]
[ROW][C]9[/C][C]1.437[/C][C]1.44004[/C][C]1.4316[/C][C]0.00844861[/C][C]-0.00304444[/C][/ROW]
[ROW][C]10[/C][C]1.3322[/C][C]1.42528[/C][C]1.4106[/C][C]0.0146753[/C][C]-0.0930794[/C][/ROW]
[ROW][C]11[/C][C]1.2732[/C][C]1.39058[/C][C]1.39199[/C][C]-0.00140806[/C][C]-0.117379[/C][/ROW]
[ROW][C]12[/C][C]1.3449[/C][C]1.37815[/C][C]1.37764[/C][C]0.000507778[/C][C]-0.0332453[/C][/ROW]
[ROW][C]13[/C][C]1.3239[/C][C]1.3586[/C][C]1.36422[/C][C]-0.00562056[/C][C]-0.0347044[/C][/ROW]
[ROW][C]14[/C][C]1.2785[/C][C]1.34506[/C][C]1.35427[/C][C]-0.00921139[/C][C]-0.0665594[/C][/ROW]
[ROW][C]15[/C][C]1.305[/C][C]1.34675[/C][C]1.35212[/C][C]-0.00537222[/C][C]-0.0417528[/C][/ROW]
[ROW][C]16[/C][C]1.319[/C][C]1.36323[/C][C]1.35915[/C][C]0.00407861[/C][C]-0.0442286[/C][/ROW]
[ROW][C]17[/C][C]1.365[/C][C]1.35983[/C][C]1.37447[/C][C]-0.0146364[/C][C]0.00516972[/C][/ROW]
[ROW][C]18[/C][C]1.4016[/C][C]1.37279[/C][C]1.38841[/C][C]-0.0156231[/C][C]0.0288106[/C][/ROW]
[ROW][C]19[/C][C]1.4088[/C][C]1.41148[/C][C]1.39757[/C][C]0.0139061[/C][C]-0.00267694[/C][/ROW]
[ROW][C]20[/C][C]1.4268[/C][C]1.41588[/C][C]1.40563[/C][C]0.0102553[/C][C]0.0109156[/C][/ROW]
[ROW][C]21[/C][C]1.4562[/C][C]1.41999[/C][C]1.41155[/C][C]0.00844861[/C][C]0.0362056[/C][/ROW]
[ROW][C]22[/C][C]1.4816[/C][C]1.42928[/C][C]1.41461[/C][C]0.0146753[/C][C]0.0523164[/C][/ROW]
[ROW][C]23[/C][C]1.4914[/C][C]1.40958[/C][C]1.41099[/C][C]-0.00140806[/C][C]0.0818206[/C][/ROW]
[ROW][C]24[/C][C]1.4614[/C][C]1.39945[/C][C]1.39894[/C][C]0.000507778[/C][C]0.0619547[/C][/ROW]
[ROW][C]25[/C][C]1.4272[/C][C]1.3803[/C][C]1.38592[/C][C]-0.00562056[/C][C]0.0469039[/C][/ROW]
[ROW][C]26[/C][C]1.3686[/C][C]1.36549[/C][C]1.3747[/C][C]-0.00921139[/C][C]0.00311139[/C][/ROW]
[ROW][C]27[/C][C]1.3569[/C][C]1.35737[/C][C]1.36275[/C][C]-0.00537222[/C][C]-0.000473611[/C][/ROW]
[ROW][C]28[/C][C]1.3406[/C][C]1.35677[/C][C]1.35269[/C][C]0.00407861[/C][C]-0.0161703[/C][/ROW]
[ROW][C]29[/C][C]1.2565[/C][C]1.32901[/C][C]1.34365[/C][C]-0.0146364[/C][C]-0.0725094[/C][/ROW]
[ROW][C]30[/C][C]1.2209[/C][C]1.31699[/C][C]1.33262[/C][C]-0.0156231[/C][C]-0.0960936[/C][/ROW]
[ROW][C]31[/C][C]1.277[/C][C]1.33691[/C][C]1.32301[/C][C]0.0139061[/C][C]-0.0599144[/C][/ROW]
[ROW][C]32[/C][C]1.2894[/C][C]1.32931[/C][C]1.31905[/C][C]0.0102553[/C][C]-0.0399094[/C][/ROW]
[ROW][C]33[/C][C]1.3067[/C][C]1.32914[/C][C]1.32069[/C][C]0.00844861[/C][C]-0.0224403[/C][/ROW]
[ROW][C]34[/C][C]1.3898[/C][C]1.34148[/C][C]1.3268[/C][C]0.0146753[/C][C]0.0483247[/C][/ROW]
[ROW][C]35[/C][C]1.3661[/C][C]1.33714[/C][C]1.33855[/C][C]-0.00140806[/C][C]0.0289581[/C][/ROW]
[ROW][C]36[/C][C]1.322[/C][C]1.35557[/C][C]1.35506[/C][C]0.000507778[/C][C]-0.0335703[/C][/ROW]
[ROW][C]37[/C][C]1.336[/C][C]1.36475[/C][C]1.37037[/C][C]-0.00562056[/C][C]-0.0287461[/C][/ROW]
[ROW][C]38[/C][C]1.3649[/C][C]1.37342[/C][C]1.38263[/C][C]-0.00921139[/C][C]-0.00851778[/C][/ROW]
[ROW][C]39[/C][C]1.3999[/C][C]1.38622[/C][C]1.3916[/C][C]-0.00537222[/C][C]0.0136764[/C][/ROW]
[ROW][C]40[/C][C]1.4442[/C][C]1.3978[/C][C]1.39372[/C][C]0.00407861[/C][C]0.0463964[/C][/ROW]
[ROW][C]41[/C][C]1.4349[/C][C]1.37785[/C][C]1.39249[/C][C]-0.0146364[/C][C]0.0570489[/C][/ROW]
[ROW][C]42[/C][C]1.4388[/C][C]1.37626[/C][C]1.39188[/C][C]-0.0156231[/C][C]0.0625439[/C][/ROW]
[ROW][C]43[/C][C]1.4264[/C][C]1.40372[/C][C]1.38981[/C][C]0.0139061[/C][C]0.0226814[/C][/ROW]
[ROW][C]44[/C][C]1.4343[/C][C]1.3964[/C][C]1.38615[/C][C]0.0102553[/C][C]0.0378989[/C][/ROW]
[ROW][C]45[/C][C]1.377[/C][C]1.3895[/C][C]1.38105[/C][C]0.00844861[/C][C]-0.0124986[/C][/ROW]
[ROW][C]46[/C][C]1.3706[/C][C]1.38707[/C][C]1.37239[/C][C]0.0146753[/C][C]-0.0164669[/C][/ROW]
[ROW][C]47[/C][C]1.3556[/C][C]1.35915[/C][C]1.36056[/C][C]-0.00140806[/C][C]-0.00355028[/C][/ROW]
[ROW][C]48[/C][C]1.3179[/C][C]1.34681[/C][C]1.3463[/C][C]0.000507778[/C][C]-0.0289078[/C][/ROW]
[ROW][C]49[/C][C]1.2905[/C][C]1.32469[/C][C]1.33031[/C][C]-0.00562056[/C][C]-0.0341878[/C][/ROW]
[ROW][C]50[/C][C]1.3224[/C][C]1.30477[/C][C]1.31398[/C][C]-0.00921139[/C][C]0.0176322[/C][/ROW]
[ROW][C]51[/C][C]1.3201[/C][C]1.2967[/C][C]1.30207[/C][C]-0.00537222[/C][C]0.0233972[/C][/ROW]
[ROW][C]52[/C][C]1.3162[/C][C]1.2993[/C][C]1.29522[/C][C]0.00407861[/C][C]0.0169047[/C][/ROW]
[ROW][C]53[/C][C]1.2789[/C][C]1.2745[/C][C]1.28913[/C][C]-0.0146364[/C][C]0.00440306[/C][/ROW]
[ROW][C]54[/C][C]1.2526[/C][C]1.27023[/C][C]1.28585[/C][C]-0.0156231[/C][C]-0.0176269[/C][/ROW]
[ROW][C]55[/C][C]1.2288[/C][C]1.3011[/C][C]1.2872[/C][C]0.0139061[/C][C]-0.0723019[/C][/ROW]
[ROW][C]56[/C][C]1.24[/C][C]1.29961[/C][C]1.28935[/C][C]0.0102553[/C][C]-0.0596094[/C][/ROW]
[ROW][C]57[/C][C]1.2856[/C][C]1.29738[/C][C]1.28893[/C][C]0.00844861[/C][C]-0.0117778[/C][/ROW]
[ROW][C]58[/C][C]1.2974[/C][C]1.30205[/C][C]1.28738[/C][C]0.0146753[/C][C]-0.00465028[/C][/ROW]
[ROW][C]59[/C][C]1.2828[/C][C]1.2862[/C][C]1.28761[/C][C]-0.00140806[/C][C]-0.00340444[/C][/ROW]
[ROW][C]60[/C][C]1.3119[/C][C]1.29169[/C][C]1.29118[/C][C]0.000507778[/C][C]0.0202131[/C][/ROW]
[ROW][C]61[/C][C]1.3288[/C][C]1.29162[/C][C]1.29724[/C][C]-0.00562056[/C][C]0.0371789[/C][/ROW]
[ROW][C]62[/C][C]1.3359[/C][C]1.29512[/C][C]1.30433[/C][C]-0.00921139[/C][C]0.0407781[/C][/ROW]
[ROW][C]63[/C][C]1.2964[/C][C]1.3048[/C][C]1.31018[/C][C]-0.00537222[/C][C]-0.00840278[/C][/ROW]
[ROW][C]64[/C][C]1.3026[/C][C]1.31906[/C][C]1.31498[/C][C]0.00407861[/C][C]-0.0164578[/C][/ROW]
[ROW][C]65[/C][C]1.2982[/C][C]1.30587[/C][C]1.3205[/C][C]-0.0146364[/C][C]-0.00766778[/C][/ROW]
[ROW][C]66[/C][C]1.3189[/C][C]1.31009[/C][C]1.32571[/C][C]-0.0156231[/C][C]0.00881056[/C][/ROW]
[ROW][C]67[/C][C]1.308[/C][C]NA[/C][C]NA[/C][C]0.0139061[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.331[/C][C]NA[/C][C]NA[/C][C]0.0102553[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.3348[/C][C]NA[/C][C]NA[/C][C]0.00844861[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.3635[/C][C]NA[/C][C]NA[/C][C]0.0146753[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.3493[/C][C]NA[/C][C]NA[/C][C]-0.00140806[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.3704[/C][C]NA[/C][C]NA[/C][C]0.000507778[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259529&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259529&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	1.4718	NA	NA	-0.00562056	NA
2	1.4748	NA	NA	-0.00921139	NA
3	1.5527	NA	NA	-0.00537222	NA
4	1.5751	NA	NA	0.00407861	NA
5	1.5557	NA	NA	-0.0146364	NA
6	1.5553	NA	NA	-0.0156231	NA
7	1.577	1.47834	1.46444	0.0139061	0.0986564
8	1.4975	1.46035	1.4501	0.0102553	0.0371489
9	1.437	1.44004	1.4316	0.00844861	-0.00304444
10	1.3322	1.42528	1.4106	0.0146753	-0.0930794
11	1.2732	1.39058	1.39199	-0.00140806	-0.117379
12	1.3449	1.37815	1.37764	0.000507778	-0.0332453
13	1.3239	1.3586	1.36422	-0.00562056	-0.0347044
14	1.2785	1.34506	1.35427	-0.00921139	-0.0665594
15	1.305	1.34675	1.35212	-0.00537222	-0.0417528
16	1.319	1.36323	1.35915	0.00407861	-0.0442286
17	1.365	1.35983	1.37447	-0.0146364	0.00516972
18	1.4016	1.37279	1.38841	-0.0156231	0.0288106
19	1.4088	1.41148	1.39757	0.0139061	-0.00267694
20	1.4268	1.41588	1.40563	0.0102553	0.0109156
21	1.4562	1.41999	1.41155	0.00844861	0.0362056
22	1.4816	1.42928	1.41461	0.0146753	0.0523164
23	1.4914	1.40958	1.41099	-0.00140806	0.0818206
24	1.4614	1.39945	1.39894	0.000507778	0.0619547
25	1.4272	1.3803	1.38592	-0.00562056	0.0469039
26	1.3686	1.36549	1.3747	-0.00921139	0.00311139
27	1.3569	1.35737	1.36275	-0.00537222	-0.000473611
28	1.3406	1.35677	1.35269	0.00407861	-0.0161703
29	1.2565	1.32901	1.34365	-0.0146364	-0.0725094
30	1.2209	1.31699	1.33262	-0.0156231	-0.0960936
31	1.277	1.33691	1.32301	0.0139061	-0.0599144
32	1.2894	1.32931	1.31905	0.0102553	-0.0399094
33	1.3067	1.32914	1.32069	0.00844861	-0.0224403
34	1.3898	1.34148	1.3268	0.0146753	0.0483247
35	1.3661	1.33714	1.33855	-0.00140806	0.0289581
36	1.322	1.35557	1.35506	0.000507778	-0.0335703
37	1.336	1.36475	1.37037	-0.00562056	-0.0287461
38	1.3649	1.37342	1.38263	-0.00921139	-0.00851778
39	1.3999	1.38622	1.3916	-0.00537222	0.0136764
40	1.4442	1.3978	1.39372	0.00407861	0.0463964
41	1.4349	1.37785	1.39249	-0.0146364	0.0570489
42	1.4388	1.37626	1.39188	-0.0156231	0.0625439
43	1.4264	1.40372	1.38981	0.0139061	0.0226814
44	1.4343	1.3964	1.38615	0.0102553	0.0378989
45	1.377	1.3895	1.38105	0.00844861	-0.0124986
46	1.3706	1.38707	1.37239	0.0146753	-0.0164669
47	1.3556	1.35915	1.36056	-0.00140806	-0.00355028
48	1.3179	1.34681	1.3463	0.000507778	-0.0289078
49	1.2905	1.32469	1.33031	-0.00562056	-0.0341878
50	1.3224	1.30477	1.31398	-0.00921139	0.0176322
51	1.3201	1.2967	1.30207	-0.00537222	0.0233972
52	1.3162	1.2993	1.29522	0.00407861	0.0169047
53	1.2789	1.2745	1.28913	-0.0146364	0.00440306
54	1.2526	1.27023	1.28585	-0.0156231	-0.0176269
55	1.2288	1.3011	1.2872	0.0139061	-0.0723019
56	1.24	1.29961	1.28935	0.0102553	-0.0596094
57	1.2856	1.29738	1.28893	0.00844861	-0.0117778
58	1.2974	1.30205	1.28738	0.0146753	-0.00465028
59	1.2828	1.2862	1.28761	-0.00140806	-0.00340444
60	1.3119	1.29169	1.29118	0.000507778	0.0202131
61	1.3288	1.29162	1.29724	-0.00562056	0.0371789
62	1.3359	1.29512	1.30433	-0.00921139	0.0407781
63	1.2964	1.3048	1.31018	-0.00537222	-0.00840278
64	1.3026	1.31906	1.31498	0.00407861	-0.0164578
65	1.2982	1.30587	1.3205	-0.0146364	-0.00766778
66	1.3189	1.31009	1.32571	-0.0156231	0.00881056
67	1.308	NA	NA	0.0139061	NA
68	1.331	NA	NA	0.0102553	NA
69	1.3348	NA	NA	0.00844861	NA
70	1.3635	NA	NA	0.0146753	NA
71	1.3493	NA	NA	-0.00140806	NA
72	1.3704	NA	NA	0.000507778	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