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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 09 Dec 2013 04:13:37 -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/2013/Dec/09/t1386580482s3utvm2ttv67m79.htm/, Retrieved Sat, 20 Apr 2024 04:18:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231593, Retrieved Sat, 20 Apr 2024 04:18:29 +0000

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Estimated Impact

108

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-       [Classical Decomposition] [decomposition of ...] [2013-12-09 09:13:37] [45baafc513cf820e9f0a314ccf5f72d1] [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	5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231593&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]5 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=231593&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231593&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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	31.5	NA	NA	0.0109664	NA
2	31.29	NA	NA	-0.00771412	NA
3	31.3	NA	NA	-0.0544502	NA
4	31.06	NA	NA	0.00492477	NA
5	31.09	NA	NA	-0.0288947	NA
6	31.11	NA	NA	0.00284144	NA
7	31.13	31.0751	31.0542	0.020897	0.0549363
8	31.1	31.0821	31.0021	0.0799942	0.0179225
9	31.03	30.9994	30.9546	0.0447859	0.0306308
10	30.74	30.8546	30.91	-0.0554225	-0.114578
11	30.83	30.863	30.8742	-0.0111169	-0.0330498
12	30.82	30.8344	30.8412	-0.00681134	-0.0144387
13	30.8	30.8172	30.8062	0.0109664	-0.0172164
14	30.74	30.7648	30.7725	-0.00771412	-0.0247859
15	30.71	30.6876	30.7421	-0.0544502	0.0223669
16	30.58	30.7341	30.7292	0.00492477	-0.154091
17	30.71	30.7024	30.7312	-0.0288947	0.00764468
18	30.7	30.7337	30.7308	0.00284144	-0.0336748
19	30.7	30.7509	30.73	0.020897	-0.050897
20	30.72	30.8158	30.7358	0.0799942	-0.0958275
21	30.68	30.7931	30.7483	0.0447859	-0.113119
22	30.78	30.7137	30.7692	-0.0554225	0.0662558
23	30.84	30.7768	30.7879	-0.0111169	0.0632002
24	30.8	30.7878	30.7946	-0.00681134	0.012228
25	30.8	30.8097	30.7987	0.0109664	-0.00971644
26	30.88	30.7944	30.8021	-0.00771412	0.0856308
27	30.87	30.7468	30.8012	-0.0544502	0.1232
28	30.92	30.7933	30.7883	0.00492477	0.126742
29	30.82	30.7378	30.7667	-0.0288947	0.082228
30	30.75	30.7503	30.7475	0.00284144	-0.000341435
31	30.75	30.7517	30.7308	0.020897	-0.00173032
32	30.75	30.7921	30.7121	0.0799942	-0.0420775
33	30.63	30.7335	30.6888	0.0447859	-0.103536
34	30.52	30.6075	30.6629	-0.0554225	-0.0874942
35	30.58	30.6268	30.6379	-0.0111169	-0.0467998
36	30.6	30.6128	30.6196	-0.00681134	-0.012772
37	30.6	30.618	30.6071	0.0109664	-0.0180498
38	30.63	30.5881	30.5958	-0.00771412	0.0418808
39	30.56	30.5376	30.5921	-0.0544502	0.0223669
40	30.61	30.5908	30.5858	0.00492477	0.0192419
41	30.53	30.5386	30.5675	-0.0288947	-0.00860532
42	30.6	30.547	30.5442	0.00284144	0.0529919
43	30.6	30.5401	30.5192	0.020897	0.0599363
44	30.63	30.5637	30.4838	0.0799942	0.0662558
45	30.66	30.4806	30.4358	0.0447859	0.179381
46	30.34	30.3262	30.3817	-0.0554225	0.0137558
47	30.32	30.3122	30.3233	-0.0111169	0.00778356
48	30.3	30.2578	30.2646	-0.00681134	0.042228
49	30.3	30.2147	30.2037	0.0109664	0.0852836
50	30.08	30.141	30.1487	-0.00771412	-0.0610359
51	29.96	30.036	30.0904	-0.0544502	-0.0759664
52	29.91	30.0445	30.0396	0.00492477	-0.134508
53	29.83	29.9819	30.0108	-0.0288947	-0.151939
54	29.89	29.9899	29.9871	0.00284144	-0.0999248
55	29.85	29.9855	29.9646	0.020897	-0.13548
56	30.06	30.0283	29.9483	0.0799942	0.0316725
57	29.83	29.9835	29.9388	0.0447859	-0.153536
58	29.95	29.8875	29.9429	-0.0554225	0.0625058
59	30.02	29.9439	29.955	-0.0111169	0.0761169
60	30.03	29.9519	29.9588	-0.00681134	0.0780613
61	30.03	29.973	29.9621	0.0109664	0.0569502
62	29.96	29.9502	29.9579	-0.00771412	0.00979745
63	29.85	29.9018	29.9562	-0.0544502	-0.0517998
64	30.12	29.957	29.9521	0.00492477	0.162992
65	29.91	29.8961	29.925	-0.0288947	0.0138947
66	29.9	29.8899	29.8871	0.00284144	0.0100752
67	29.92	29.8671	29.8462	0.020897	0.052853
68	29.89	29.8883	29.8083	0.0799942	0.00167245
69	29.96	29.8202	29.7754	0.0447859	0.139797
70	29.72	29.6808	29.7362	-0.0554225	0.0391725
71	29.6	29.6876	29.6987	-0.0111169	-0.0876331
72	29.54	29.6657	29.6725	-0.00681134	-0.125689
73	29.54	29.6576	29.6467	0.0109664	-0.117633
74	29.54	29.6119	29.6196	-0.00771412	-0.0718692
75	29.48	29.5405	29.595	-0.0544502	-0.0605498
76	29.55	29.5908	29.5858	0.00492477	-0.0407581
77	29.58	29.5436	29.5725	-0.0288947	0.0363947
78	29.6	29.5495	29.5467	0.00284144	0.0504919
79	29.6	NA	NA	0.020897	NA
80	29.56	NA	NA	0.0799942	NA
81	29.7	NA	NA	0.0447859	NA
82	29.76	NA	NA	-0.0554225	NA
83	29.24	NA	NA	-0.0111169	NA
84	29.28	NA	NA	-0.00681134	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 31.5 & NA & NA & 0.0109664 & NA \tabularnewline
2 & 31.29 & NA & NA & -0.00771412 & NA \tabularnewline
3 & 31.3 & NA & NA & -0.0544502 & NA \tabularnewline
4 & 31.06 & NA & NA & 0.00492477 & NA \tabularnewline
5 & 31.09 & NA & NA & -0.0288947 & NA \tabularnewline
6 & 31.11 & NA & NA & 0.00284144 & NA \tabularnewline
7 & 31.13 & 31.0751 & 31.0542 & 0.020897 & 0.0549363 \tabularnewline
8 & 31.1 & 31.0821 & 31.0021 & 0.0799942 & 0.0179225 \tabularnewline
9 & 31.03 & 30.9994 & 30.9546 & 0.0447859 & 0.0306308 \tabularnewline
10 & 30.74 & 30.8546 & 30.91 & -0.0554225 & -0.114578 \tabularnewline
11 & 30.83 & 30.863 & 30.8742 & -0.0111169 & -0.0330498 \tabularnewline
12 & 30.82 & 30.8344 & 30.8412 & -0.00681134 & -0.0144387 \tabularnewline
13 & 30.8 & 30.8172 & 30.8062 & 0.0109664 & -0.0172164 \tabularnewline
14 & 30.74 & 30.7648 & 30.7725 & -0.00771412 & -0.0247859 \tabularnewline
15 & 30.71 & 30.6876 & 30.7421 & -0.0544502 & 0.0223669 \tabularnewline
16 & 30.58 & 30.7341 & 30.7292 & 0.00492477 & -0.154091 \tabularnewline
17 & 30.71 & 30.7024 & 30.7312 & -0.0288947 & 0.00764468 \tabularnewline
18 & 30.7 & 30.7337 & 30.7308 & 0.00284144 & -0.0336748 \tabularnewline
19 & 30.7 & 30.7509 & 30.73 & 0.020897 & -0.050897 \tabularnewline
20 & 30.72 & 30.8158 & 30.7358 & 0.0799942 & -0.0958275 \tabularnewline
21 & 30.68 & 30.7931 & 30.7483 & 0.0447859 & -0.113119 \tabularnewline
22 & 30.78 & 30.7137 & 30.7692 & -0.0554225 & 0.0662558 \tabularnewline
23 & 30.84 & 30.7768 & 30.7879 & -0.0111169 & 0.0632002 \tabularnewline
24 & 30.8 & 30.7878 & 30.7946 & -0.00681134 & 0.012228 \tabularnewline
25 & 30.8 & 30.8097 & 30.7987 & 0.0109664 & -0.00971644 \tabularnewline
26 & 30.88 & 30.7944 & 30.8021 & -0.00771412 & 0.0856308 \tabularnewline
27 & 30.87 & 30.7468 & 30.8012 & -0.0544502 & 0.1232 \tabularnewline
28 & 30.92 & 30.7933 & 30.7883 & 0.00492477 & 0.126742 \tabularnewline
29 & 30.82 & 30.7378 & 30.7667 & -0.0288947 & 0.082228 \tabularnewline
30 & 30.75 & 30.7503 & 30.7475 & 0.00284144 & -0.000341435 \tabularnewline
31 & 30.75 & 30.7517 & 30.7308 & 0.020897 & -0.00173032 \tabularnewline
32 & 30.75 & 30.7921 & 30.7121 & 0.0799942 & -0.0420775 \tabularnewline
33 & 30.63 & 30.7335 & 30.6888 & 0.0447859 & -0.103536 \tabularnewline
34 & 30.52 & 30.6075 & 30.6629 & -0.0554225 & -0.0874942 \tabularnewline
35 & 30.58 & 30.6268 & 30.6379 & -0.0111169 & -0.0467998 \tabularnewline
36 & 30.6 & 30.6128 & 30.6196 & -0.00681134 & -0.012772 \tabularnewline
37 & 30.6 & 30.618 & 30.6071 & 0.0109664 & -0.0180498 \tabularnewline
38 & 30.63 & 30.5881 & 30.5958 & -0.00771412 & 0.0418808 \tabularnewline
39 & 30.56 & 30.5376 & 30.5921 & -0.0544502 & 0.0223669 \tabularnewline
40 & 30.61 & 30.5908 & 30.5858 & 0.00492477 & 0.0192419 \tabularnewline
41 & 30.53 & 30.5386 & 30.5675 & -0.0288947 & -0.00860532 \tabularnewline
42 & 30.6 & 30.547 & 30.5442 & 0.00284144 & 0.0529919 \tabularnewline
43 & 30.6 & 30.5401 & 30.5192 & 0.020897 & 0.0599363 \tabularnewline
44 & 30.63 & 30.5637 & 30.4838 & 0.0799942 & 0.0662558 \tabularnewline
45 & 30.66 & 30.4806 & 30.4358 & 0.0447859 & 0.179381 \tabularnewline
46 & 30.34 & 30.3262 & 30.3817 & -0.0554225 & 0.0137558 \tabularnewline
47 & 30.32 & 30.3122 & 30.3233 & -0.0111169 & 0.00778356 \tabularnewline
48 & 30.3 & 30.2578 & 30.2646 & -0.00681134 & 0.042228 \tabularnewline
49 & 30.3 & 30.2147 & 30.2037 & 0.0109664 & 0.0852836 \tabularnewline
50 & 30.08 & 30.141 & 30.1487 & -0.00771412 & -0.0610359 \tabularnewline
51 & 29.96 & 30.036 & 30.0904 & -0.0544502 & -0.0759664 \tabularnewline
52 & 29.91 & 30.0445 & 30.0396 & 0.00492477 & -0.134508 \tabularnewline
53 & 29.83 & 29.9819 & 30.0108 & -0.0288947 & -0.151939 \tabularnewline
54 & 29.89 & 29.9899 & 29.9871 & 0.00284144 & -0.0999248 \tabularnewline
55 & 29.85 & 29.9855 & 29.9646 & 0.020897 & -0.13548 \tabularnewline
56 & 30.06 & 30.0283 & 29.9483 & 0.0799942 & 0.0316725 \tabularnewline
57 & 29.83 & 29.9835 & 29.9388 & 0.0447859 & -0.153536 \tabularnewline
58 & 29.95 & 29.8875 & 29.9429 & -0.0554225 & 0.0625058 \tabularnewline
59 & 30.02 & 29.9439 & 29.955 & -0.0111169 & 0.0761169 \tabularnewline
60 & 30.03 & 29.9519 & 29.9588 & -0.00681134 & 0.0780613 \tabularnewline
61 & 30.03 & 29.973 & 29.9621 & 0.0109664 & 0.0569502 \tabularnewline
62 & 29.96 & 29.9502 & 29.9579 & -0.00771412 & 0.00979745 \tabularnewline
63 & 29.85 & 29.9018 & 29.9562 & -0.0544502 & -0.0517998 \tabularnewline
64 & 30.12 & 29.957 & 29.9521 & 0.00492477 & 0.162992 \tabularnewline
65 & 29.91 & 29.8961 & 29.925 & -0.0288947 & 0.0138947 \tabularnewline
66 & 29.9 & 29.8899 & 29.8871 & 0.00284144 & 0.0100752 \tabularnewline
67 & 29.92 & 29.8671 & 29.8462 & 0.020897 & 0.052853 \tabularnewline
68 & 29.89 & 29.8883 & 29.8083 & 0.0799942 & 0.00167245 \tabularnewline
69 & 29.96 & 29.8202 & 29.7754 & 0.0447859 & 0.139797 \tabularnewline
70 & 29.72 & 29.6808 & 29.7362 & -0.0554225 & 0.0391725 \tabularnewline
71 & 29.6 & 29.6876 & 29.6987 & -0.0111169 & -0.0876331 \tabularnewline
72 & 29.54 & 29.6657 & 29.6725 & -0.00681134 & -0.125689 \tabularnewline
73 & 29.54 & 29.6576 & 29.6467 & 0.0109664 & -0.117633 \tabularnewline
74 & 29.54 & 29.6119 & 29.6196 & -0.00771412 & -0.0718692 \tabularnewline
75 & 29.48 & 29.5405 & 29.595 & -0.0544502 & -0.0605498 \tabularnewline
76 & 29.55 & 29.5908 & 29.5858 & 0.00492477 & -0.0407581 \tabularnewline
77 & 29.58 & 29.5436 & 29.5725 & -0.0288947 & 0.0363947 \tabularnewline
78 & 29.6 & 29.5495 & 29.5467 & 0.00284144 & 0.0504919 \tabularnewline
79 & 29.6 & NA & NA & 0.020897 & NA \tabularnewline
80 & 29.56 & NA & NA & 0.0799942 & NA \tabularnewline
81 & 29.7 & NA & NA & 0.0447859 & NA \tabularnewline
82 & 29.76 & NA & NA & -0.0554225 & NA \tabularnewline
83 & 29.24 & NA & NA & -0.0111169 & NA \tabularnewline
84 & 29.28 & NA & NA & -0.00681134 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231593&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]31.5[/C][C]NA[/C][C]NA[/C][C]0.0109664[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]31.29[/C][C]NA[/C][C]NA[/C][C]-0.00771412[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]31.3[/C][C]NA[/C][C]NA[/C][C]-0.0544502[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]31.06[/C][C]NA[/C][C]NA[/C][C]0.00492477[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]31.09[/C][C]NA[/C][C]NA[/C][C]-0.0288947[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]31.11[/C][C]NA[/C][C]NA[/C][C]0.00284144[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]31.13[/C][C]31.0751[/C][C]31.0542[/C][C]0.020897[/C][C]0.0549363[/C][/ROW]
[ROW][C]8[/C][C]31.1[/C][C]31.0821[/C][C]31.0021[/C][C]0.0799942[/C][C]0.0179225[/C][/ROW]
[ROW][C]9[/C][C]31.03[/C][C]30.9994[/C][C]30.9546[/C][C]0.0447859[/C][C]0.0306308[/C][/ROW]
[ROW][C]10[/C][C]30.74[/C][C]30.8546[/C][C]30.91[/C][C]-0.0554225[/C][C]-0.114578[/C][/ROW]
[ROW][C]11[/C][C]30.83[/C][C]30.863[/C][C]30.8742[/C][C]-0.0111169[/C][C]-0.0330498[/C][/ROW]
[ROW][C]12[/C][C]30.82[/C][C]30.8344[/C][C]30.8412[/C][C]-0.00681134[/C][C]-0.0144387[/C][/ROW]
[ROW][C]13[/C][C]30.8[/C][C]30.8172[/C][C]30.8062[/C][C]0.0109664[/C][C]-0.0172164[/C][/ROW]
[ROW][C]14[/C][C]30.74[/C][C]30.7648[/C][C]30.7725[/C][C]-0.00771412[/C][C]-0.0247859[/C][/ROW]
[ROW][C]15[/C][C]30.71[/C][C]30.6876[/C][C]30.7421[/C][C]-0.0544502[/C][C]0.0223669[/C][/ROW]
[ROW][C]16[/C][C]30.58[/C][C]30.7341[/C][C]30.7292[/C][C]0.00492477[/C][C]-0.154091[/C][/ROW]
[ROW][C]17[/C][C]30.71[/C][C]30.7024[/C][C]30.7312[/C][C]-0.0288947[/C][C]0.00764468[/C][/ROW]
[ROW][C]18[/C][C]30.7[/C][C]30.7337[/C][C]30.7308[/C][C]0.00284144[/C][C]-0.0336748[/C][/ROW]
[ROW][C]19[/C][C]30.7[/C][C]30.7509[/C][C]30.73[/C][C]0.020897[/C][C]-0.050897[/C][/ROW]
[ROW][C]20[/C][C]30.72[/C][C]30.8158[/C][C]30.7358[/C][C]0.0799942[/C][C]-0.0958275[/C][/ROW]
[ROW][C]21[/C][C]30.68[/C][C]30.7931[/C][C]30.7483[/C][C]0.0447859[/C][C]-0.113119[/C][/ROW]
[ROW][C]22[/C][C]30.78[/C][C]30.7137[/C][C]30.7692[/C][C]-0.0554225[/C][C]0.0662558[/C][/ROW]
[ROW][C]23[/C][C]30.84[/C][C]30.7768[/C][C]30.7879[/C][C]-0.0111169[/C][C]0.0632002[/C][/ROW]
[ROW][C]24[/C][C]30.8[/C][C]30.7878[/C][C]30.7946[/C][C]-0.00681134[/C][C]0.012228[/C][/ROW]
[ROW][C]25[/C][C]30.8[/C][C]30.8097[/C][C]30.7987[/C][C]0.0109664[/C][C]-0.00971644[/C][/ROW]
[ROW][C]26[/C][C]30.88[/C][C]30.7944[/C][C]30.8021[/C][C]-0.00771412[/C][C]0.0856308[/C][/ROW]
[ROW][C]27[/C][C]30.87[/C][C]30.7468[/C][C]30.8012[/C][C]-0.0544502[/C][C]0.1232[/C][/ROW]
[ROW][C]28[/C][C]30.92[/C][C]30.7933[/C][C]30.7883[/C][C]0.00492477[/C][C]0.126742[/C][/ROW]
[ROW][C]29[/C][C]30.82[/C][C]30.7378[/C][C]30.7667[/C][C]-0.0288947[/C][C]0.082228[/C][/ROW]
[ROW][C]30[/C][C]30.75[/C][C]30.7503[/C][C]30.7475[/C][C]0.00284144[/C][C]-0.000341435[/C][/ROW]
[ROW][C]31[/C][C]30.75[/C][C]30.7517[/C][C]30.7308[/C][C]0.020897[/C][C]-0.00173032[/C][/ROW]
[ROW][C]32[/C][C]30.75[/C][C]30.7921[/C][C]30.7121[/C][C]0.0799942[/C][C]-0.0420775[/C][/ROW]
[ROW][C]33[/C][C]30.63[/C][C]30.7335[/C][C]30.6888[/C][C]0.0447859[/C][C]-0.103536[/C][/ROW]
[ROW][C]34[/C][C]30.52[/C][C]30.6075[/C][C]30.6629[/C][C]-0.0554225[/C][C]-0.0874942[/C][/ROW]
[ROW][C]35[/C][C]30.58[/C][C]30.6268[/C][C]30.6379[/C][C]-0.0111169[/C][C]-0.0467998[/C][/ROW]
[ROW][C]36[/C][C]30.6[/C][C]30.6128[/C][C]30.6196[/C][C]-0.00681134[/C][C]-0.012772[/C][/ROW]
[ROW][C]37[/C][C]30.6[/C][C]30.618[/C][C]30.6071[/C][C]0.0109664[/C][C]-0.0180498[/C][/ROW]
[ROW][C]38[/C][C]30.63[/C][C]30.5881[/C][C]30.5958[/C][C]-0.00771412[/C][C]0.0418808[/C][/ROW]
[ROW][C]39[/C][C]30.56[/C][C]30.5376[/C][C]30.5921[/C][C]-0.0544502[/C][C]0.0223669[/C][/ROW]
[ROW][C]40[/C][C]30.61[/C][C]30.5908[/C][C]30.5858[/C][C]0.00492477[/C][C]0.0192419[/C][/ROW]
[ROW][C]41[/C][C]30.53[/C][C]30.5386[/C][C]30.5675[/C][C]-0.0288947[/C][C]-0.00860532[/C][/ROW]
[ROW][C]42[/C][C]30.6[/C][C]30.547[/C][C]30.5442[/C][C]0.00284144[/C][C]0.0529919[/C][/ROW]
[ROW][C]43[/C][C]30.6[/C][C]30.5401[/C][C]30.5192[/C][C]0.020897[/C][C]0.0599363[/C][/ROW]
[ROW][C]44[/C][C]30.63[/C][C]30.5637[/C][C]30.4838[/C][C]0.0799942[/C][C]0.0662558[/C][/ROW]
[ROW][C]45[/C][C]30.66[/C][C]30.4806[/C][C]30.4358[/C][C]0.0447859[/C][C]0.179381[/C][/ROW]
[ROW][C]46[/C][C]30.34[/C][C]30.3262[/C][C]30.3817[/C][C]-0.0554225[/C][C]0.0137558[/C][/ROW]
[ROW][C]47[/C][C]30.32[/C][C]30.3122[/C][C]30.3233[/C][C]-0.0111169[/C][C]0.00778356[/C][/ROW]
[ROW][C]48[/C][C]30.3[/C][C]30.2578[/C][C]30.2646[/C][C]-0.00681134[/C][C]0.042228[/C][/ROW]
[ROW][C]49[/C][C]30.3[/C][C]30.2147[/C][C]30.2037[/C][C]0.0109664[/C][C]0.0852836[/C][/ROW]
[ROW][C]50[/C][C]30.08[/C][C]30.141[/C][C]30.1487[/C][C]-0.00771412[/C][C]-0.0610359[/C][/ROW]
[ROW][C]51[/C][C]29.96[/C][C]30.036[/C][C]30.0904[/C][C]-0.0544502[/C][C]-0.0759664[/C][/ROW]
[ROW][C]52[/C][C]29.91[/C][C]30.0445[/C][C]30.0396[/C][C]0.00492477[/C][C]-0.134508[/C][/ROW]
[ROW][C]53[/C][C]29.83[/C][C]29.9819[/C][C]30.0108[/C][C]-0.0288947[/C][C]-0.151939[/C][/ROW]
[ROW][C]54[/C][C]29.89[/C][C]29.9899[/C][C]29.9871[/C][C]0.00284144[/C][C]-0.0999248[/C][/ROW]
[ROW][C]55[/C][C]29.85[/C][C]29.9855[/C][C]29.9646[/C][C]0.020897[/C][C]-0.13548[/C][/ROW]
[ROW][C]56[/C][C]30.06[/C][C]30.0283[/C][C]29.9483[/C][C]0.0799942[/C][C]0.0316725[/C][/ROW]
[ROW][C]57[/C][C]29.83[/C][C]29.9835[/C][C]29.9388[/C][C]0.0447859[/C][C]-0.153536[/C][/ROW]
[ROW][C]58[/C][C]29.95[/C][C]29.8875[/C][C]29.9429[/C][C]-0.0554225[/C][C]0.0625058[/C][/ROW]
[ROW][C]59[/C][C]30.02[/C][C]29.9439[/C][C]29.955[/C][C]-0.0111169[/C][C]0.0761169[/C][/ROW]
[ROW][C]60[/C][C]30.03[/C][C]29.9519[/C][C]29.9588[/C][C]-0.00681134[/C][C]0.0780613[/C][/ROW]
[ROW][C]61[/C][C]30.03[/C][C]29.973[/C][C]29.9621[/C][C]0.0109664[/C][C]0.0569502[/C][/ROW]
[ROW][C]62[/C][C]29.96[/C][C]29.9502[/C][C]29.9579[/C][C]-0.00771412[/C][C]0.00979745[/C][/ROW]
[ROW][C]63[/C][C]29.85[/C][C]29.9018[/C][C]29.9562[/C][C]-0.0544502[/C][C]-0.0517998[/C][/ROW]
[ROW][C]64[/C][C]30.12[/C][C]29.957[/C][C]29.9521[/C][C]0.00492477[/C][C]0.162992[/C][/ROW]
[ROW][C]65[/C][C]29.91[/C][C]29.8961[/C][C]29.925[/C][C]-0.0288947[/C][C]0.0138947[/C][/ROW]
[ROW][C]66[/C][C]29.9[/C][C]29.8899[/C][C]29.8871[/C][C]0.00284144[/C][C]0.0100752[/C][/ROW]
[ROW][C]67[/C][C]29.92[/C][C]29.8671[/C][C]29.8462[/C][C]0.020897[/C][C]0.052853[/C][/ROW]
[ROW][C]68[/C][C]29.89[/C][C]29.8883[/C][C]29.8083[/C][C]0.0799942[/C][C]0.00167245[/C][/ROW]
[ROW][C]69[/C][C]29.96[/C][C]29.8202[/C][C]29.7754[/C][C]0.0447859[/C][C]0.139797[/C][/ROW]
[ROW][C]70[/C][C]29.72[/C][C]29.6808[/C][C]29.7362[/C][C]-0.0554225[/C][C]0.0391725[/C][/ROW]
[ROW][C]71[/C][C]29.6[/C][C]29.6876[/C][C]29.6987[/C][C]-0.0111169[/C][C]-0.0876331[/C][/ROW]
[ROW][C]72[/C][C]29.54[/C][C]29.6657[/C][C]29.6725[/C][C]-0.00681134[/C][C]-0.125689[/C][/ROW]
[ROW][C]73[/C][C]29.54[/C][C]29.6576[/C][C]29.6467[/C][C]0.0109664[/C][C]-0.117633[/C][/ROW]
[ROW][C]74[/C][C]29.54[/C][C]29.6119[/C][C]29.6196[/C][C]-0.00771412[/C][C]-0.0718692[/C][/ROW]
[ROW][C]75[/C][C]29.48[/C][C]29.5405[/C][C]29.595[/C][C]-0.0544502[/C][C]-0.0605498[/C][/ROW]
[ROW][C]76[/C][C]29.55[/C][C]29.5908[/C][C]29.5858[/C][C]0.00492477[/C][C]-0.0407581[/C][/ROW]
[ROW][C]77[/C][C]29.58[/C][C]29.5436[/C][C]29.5725[/C][C]-0.0288947[/C][C]0.0363947[/C][/ROW]
[ROW][C]78[/C][C]29.6[/C][C]29.5495[/C][C]29.5467[/C][C]0.00284144[/C][C]0.0504919[/C][/ROW]
[ROW][C]79[/C][C]29.6[/C][C]NA[/C][C]NA[/C][C]0.020897[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]29.56[/C][C]NA[/C][C]NA[/C][C]0.0799942[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]29.7[/C][C]NA[/C][C]NA[/C][C]0.0447859[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]29.76[/C][C]NA[/C][C]NA[/C][C]-0.0554225[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]29.24[/C][C]NA[/C][C]NA[/C][C]-0.0111169[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]29.28[/C][C]NA[/C][C]NA[/C][C]-0.00681134[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231593&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231593&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	31.5	NA	NA	0.0109664	NA
2	31.29	NA	NA	-0.00771412	NA
3	31.3	NA	NA	-0.0544502	NA
4	31.06	NA	NA	0.00492477	NA
5	31.09	NA	NA	-0.0288947	NA
6	31.11	NA	NA	0.00284144	NA
7	31.13	31.0751	31.0542	0.020897	0.0549363
8	31.1	31.0821	31.0021	0.0799942	0.0179225
9	31.03	30.9994	30.9546	0.0447859	0.0306308
10	30.74	30.8546	30.91	-0.0554225	-0.114578
11	30.83	30.863	30.8742	-0.0111169	-0.0330498
12	30.82	30.8344	30.8412	-0.00681134	-0.0144387
13	30.8	30.8172	30.8062	0.0109664	-0.0172164
14	30.74	30.7648	30.7725	-0.00771412	-0.0247859
15	30.71	30.6876	30.7421	-0.0544502	0.0223669
16	30.58	30.7341	30.7292	0.00492477	-0.154091
17	30.71	30.7024	30.7312	-0.0288947	0.00764468
18	30.7	30.7337	30.7308	0.00284144	-0.0336748
19	30.7	30.7509	30.73	0.020897	-0.050897
20	30.72	30.8158	30.7358	0.0799942	-0.0958275
21	30.68	30.7931	30.7483	0.0447859	-0.113119
22	30.78	30.7137	30.7692	-0.0554225	0.0662558
23	30.84	30.7768	30.7879	-0.0111169	0.0632002
24	30.8	30.7878	30.7946	-0.00681134	0.012228
25	30.8	30.8097	30.7987	0.0109664	-0.00971644
26	30.88	30.7944	30.8021	-0.00771412	0.0856308
27	30.87	30.7468	30.8012	-0.0544502	0.1232
28	30.92	30.7933	30.7883	0.00492477	0.126742
29	30.82	30.7378	30.7667	-0.0288947	0.082228
30	30.75	30.7503	30.7475	0.00284144	-0.000341435
31	30.75	30.7517	30.7308	0.020897	-0.00173032
32	30.75	30.7921	30.7121	0.0799942	-0.0420775
33	30.63	30.7335	30.6888	0.0447859	-0.103536
34	30.52	30.6075	30.6629	-0.0554225	-0.0874942
35	30.58	30.6268	30.6379	-0.0111169	-0.0467998
36	30.6	30.6128	30.6196	-0.00681134	-0.012772
37	30.6	30.618	30.6071	0.0109664	-0.0180498
38	30.63	30.5881	30.5958	-0.00771412	0.0418808
39	30.56	30.5376	30.5921	-0.0544502	0.0223669
40	30.61	30.5908	30.5858	0.00492477	0.0192419
41	30.53	30.5386	30.5675	-0.0288947	-0.00860532
42	30.6	30.547	30.5442	0.00284144	0.0529919
43	30.6	30.5401	30.5192	0.020897	0.0599363
44	30.63	30.5637	30.4838	0.0799942	0.0662558
45	30.66	30.4806	30.4358	0.0447859	0.179381
46	30.34	30.3262	30.3817	-0.0554225	0.0137558
47	30.32	30.3122	30.3233	-0.0111169	0.00778356
48	30.3	30.2578	30.2646	-0.00681134	0.042228
49	30.3	30.2147	30.2037	0.0109664	0.0852836
50	30.08	30.141	30.1487	-0.00771412	-0.0610359
51	29.96	30.036	30.0904	-0.0544502	-0.0759664
52	29.91	30.0445	30.0396	0.00492477	-0.134508
53	29.83	29.9819	30.0108	-0.0288947	-0.151939
54	29.89	29.9899	29.9871	0.00284144	-0.0999248
55	29.85	29.9855	29.9646	0.020897	-0.13548
56	30.06	30.0283	29.9483	0.0799942	0.0316725
57	29.83	29.9835	29.9388	0.0447859	-0.153536
58	29.95	29.8875	29.9429	-0.0554225	0.0625058
59	30.02	29.9439	29.955	-0.0111169	0.0761169
60	30.03	29.9519	29.9588	-0.00681134	0.0780613
61	30.03	29.973	29.9621	0.0109664	0.0569502
62	29.96	29.9502	29.9579	-0.00771412	0.00979745
63	29.85	29.9018	29.9562	-0.0544502	-0.0517998
64	30.12	29.957	29.9521	0.00492477	0.162992
65	29.91	29.8961	29.925	-0.0288947	0.0138947
66	29.9	29.8899	29.8871	0.00284144	0.0100752
67	29.92	29.8671	29.8462	0.020897	0.052853
68	29.89	29.8883	29.8083	0.0799942	0.00167245
69	29.96	29.8202	29.7754	0.0447859	0.139797
70	29.72	29.6808	29.7362	-0.0554225	0.0391725
71	29.6	29.6876	29.6987	-0.0111169	-0.0876331
72	29.54	29.6657	29.6725	-0.00681134	-0.125689
73	29.54	29.6576	29.6467	0.0109664	-0.117633
74	29.54	29.6119	29.6196	-0.00771412	-0.0718692
75	29.48	29.5405	29.595	-0.0544502	-0.0605498
76	29.55	29.5908	29.5858	0.00492477	-0.0407581
77	29.58	29.5436	29.5725	-0.0288947	0.0363947
78	29.6	29.5495	29.5467	0.00284144	0.0504919
79	29.6	NA	NA	0.020897	NA
80	29.56	NA	NA	0.0799942	NA
81	29.7	NA	NA	0.0447859	NA
82	29.76	NA	NA	-0.0554225	NA
83	29.24	NA	NA	-0.0111169	NA
84	29.28	NA	NA	-0.00681134	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 <- '12'
par1 <- 'additive'
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