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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 28 Nov 2014 20:50:40 +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/28/t1417207998dhfdsjnvwkfsdmi.htm/, Retrieved Tue, 10 Feb 2026 11:38:19 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261024, Retrieved Tue, 10 Feb 2026 11:38:19 +0000

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Estimated Impact

324

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Gemiddelde consum...] [2014-11-28 20:50:40] [34904d4daa687a283c33410e9d0f3c21] [Current]

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4,53
4,53
4,53
4,61
4,63
4,63
4,63
4,63
4,63
4,63
4,63
4,63
4,63
4,63
4,66
4,7
4,72
4,73
4,73
4,74
4,74
4,74
4,76
4,88
4,88
4,88
4,88
4,89
4,97
4,97
4,97
4,97
4,97
4,97
4,97
4,97
4,97
4,97
4,97
4,98
5
5,03
5,04
5,04
5,05
5,05
5,05
5,06
5,06
5,06
5,07
5,09
5,18
5,23
5,25
5,26
5,28
5,29
5,29
5,29
5,29
5,3
5,3
5,3
5,32
5,33
5,33
5,37
5,45
5,47
5,5
5,51

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=261024&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=261024&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261024&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 Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	4.53	NA	NA	-0.0071875	NA
2	4.53	NA	NA	-0.0171875	NA
3	4.53	NA	NA	-0.0221875	NA
4	4.61	NA	NA	-0.0200208	NA
5	4.63	NA	NA	0.0117292	NA
6	4.63	NA	NA	0.0171458	NA
7	4.63	4.63081	4.6075	0.0233125	-0.0008125
8	4.63	4.6304	4.61583	0.0145625	-0.000395833
9	4.63	4.63315	4.62542	0.00772917	-0.00314583
10	4.63	4.63215	4.63458	-0.0024375	-0.00214583
11	4.63	4.63215	4.64208	-0.0099375	-0.00214583
12	4.63	4.65448	4.65	0.00447917	-0.0244792
13	4.63	4.65115	4.65833	-0.0071875	-0.0211458
14	4.63	4.6499	4.66708	-0.0171875	-0.0198958
15	4.66	4.65406	4.67625	-0.0221875	0.0059375
16	4.7	4.6654	4.68542	-0.0200208	0.0346042
17	4.72	4.70715	4.69542	0.0117292	0.0128542
18	4.73	4.7284	4.71125	0.0171458	0.00160417
19	4.73	4.7554	4.73208	0.0233125	-0.0253958
20	4.74	4.76748	4.75292	0.0145625	-0.0274792
21	4.74	4.78023	4.7725	0.00772917	-0.0402292
22	4.74	4.78715	4.78958	-0.0024375	-0.0471458
23	4.76	4.79798	4.80792	-0.0099375	-0.0379792
24	4.88	4.83281	4.82833	0.00447917	0.0471875
25	4.88	4.84115	4.84833	-0.0071875	0.0388542
26	4.88	4.85073	4.86792	-0.0171875	0.0292708
27	4.88	4.8649	4.88708	-0.0221875	0.0151042
28	4.89	4.88623	4.90625	-0.0200208	0.00377083
29	4.97	4.93631	4.92458	0.0117292	0.0336875
30	4.97	4.95423	4.93708	0.0171458	0.0157708
31	4.97	4.9679	4.94458	0.0233125	0.00210417
32	4.97	4.96665	4.95208	0.0145625	0.00335417
33	4.97	4.96731	4.95958	0.00772917	0.0026875
34	4.97	4.96465	4.96708	-0.0024375	0.00535417
35	4.97	4.96215	4.97208	-0.0099375	0.00785417
36	4.97	4.98031	4.97583	0.00447917	-0.0103125
37	4.97	4.97406	4.98125	-0.0071875	-0.0040625
38	4.97	4.9699	4.98708	-0.0171875	0.000104167
39	4.97	4.97115	4.99333	-0.0221875	-0.00114583
40	4.98	4.97998	5	-0.0200208	2.08333e-05
41	5	5.0184	5.00667	0.0117292	-0.0183958
42	5.03	5.0309	5.01375	0.0171458	-0.000895833
43	5.04	5.04456	5.02125	0.0233125	-0.0045625
44	5.04	5.04331	5.02875	0.0145625	-0.0033125
45	5.05	5.0444	5.03667	0.00772917	0.00560417
46	5.05	5.04298	5.04542	-0.0024375	0.00702083
47	5.05	5.04756	5.0575	-0.0099375	0.0024375
48	5.06	5.07781	5.07333	0.00447917	-0.0178125
49	5.06	5.08323	5.09042	-0.0071875	-0.0232292
50	5.06	5.09115	5.10833	-0.0171875	-0.0311458
51	5.07	5.1049	5.12708	-0.0221875	-0.0348958
52	5.09	5.12665	5.14667	-0.0200208	-0.0366458
53	5.18	5.1784	5.16667	0.0117292	0.00160417
54	5.23	5.2034	5.18625	0.0171458	0.0266042
55	5.25	5.22873	5.20542	0.0233125	0.0212708
56	5.26	5.23956	5.225	0.0145625	0.0204375
57	5.28	5.25231	5.24458	0.00772917	0.0276875
58	5.29	5.26048	5.26292	-0.0024375	0.0295208
59	5.29	5.26756	5.2775	-0.0099375	0.0224375
60	5.29	5.29198	5.2875	0.00447917	-0.00197917
61	5.29	5.28781	5.295	-0.0071875	0.0021875
62	5.3	5.28573	5.30292	-0.0171875	0.0142708
63	5.3	5.2924	5.31458	-0.0221875	0.00760417
64	5.3	5.30915	5.32917	-0.0200208	-0.00914583
65	5.32	5.35715	5.34542	0.0117292	-0.0371458
66	5.33	5.38048	5.36333	0.0171458	-0.0504792
67	5.33	NA	NA	0.0233125	NA
68	5.37	NA	NA	0.0145625	NA
69	5.45	NA	NA	0.00772917	NA
70	5.47	NA	NA	-0.0024375	NA
71	5.5	NA	NA	-0.0099375	NA
72	5.51	NA	NA	0.00447917	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 4.53 & NA & NA & -0.0071875 & NA \tabularnewline
2 & 4.53 & NA & NA & -0.0171875 & NA \tabularnewline
3 & 4.53 & NA & NA & -0.0221875 & NA \tabularnewline
4 & 4.61 & NA & NA & -0.0200208 & NA \tabularnewline
5 & 4.63 & NA & NA & 0.0117292 & NA \tabularnewline
6 & 4.63 & NA & NA & 0.0171458 & NA \tabularnewline
7 & 4.63 & 4.63081 & 4.6075 & 0.0233125 & -0.0008125 \tabularnewline
8 & 4.63 & 4.6304 & 4.61583 & 0.0145625 & -0.000395833 \tabularnewline
9 & 4.63 & 4.63315 & 4.62542 & 0.00772917 & -0.00314583 \tabularnewline
10 & 4.63 & 4.63215 & 4.63458 & -0.0024375 & -0.00214583 \tabularnewline
11 & 4.63 & 4.63215 & 4.64208 & -0.0099375 & -0.00214583 \tabularnewline
12 & 4.63 & 4.65448 & 4.65 & 0.00447917 & -0.0244792 \tabularnewline
13 & 4.63 & 4.65115 & 4.65833 & -0.0071875 & -0.0211458 \tabularnewline
14 & 4.63 & 4.6499 & 4.66708 & -0.0171875 & -0.0198958 \tabularnewline
15 & 4.66 & 4.65406 & 4.67625 & -0.0221875 & 0.0059375 \tabularnewline
16 & 4.7 & 4.6654 & 4.68542 & -0.0200208 & 0.0346042 \tabularnewline
17 & 4.72 & 4.70715 & 4.69542 & 0.0117292 & 0.0128542 \tabularnewline
18 & 4.73 & 4.7284 & 4.71125 & 0.0171458 & 0.00160417 \tabularnewline
19 & 4.73 & 4.7554 & 4.73208 & 0.0233125 & -0.0253958 \tabularnewline
20 & 4.74 & 4.76748 & 4.75292 & 0.0145625 & -0.0274792 \tabularnewline
21 & 4.74 & 4.78023 & 4.7725 & 0.00772917 & -0.0402292 \tabularnewline
22 & 4.74 & 4.78715 & 4.78958 & -0.0024375 & -0.0471458 \tabularnewline
23 & 4.76 & 4.79798 & 4.80792 & -0.0099375 & -0.0379792 \tabularnewline
24 & 4.88 & 4.83281 & 4.82833 & 0.00447917 & 0.0471875 \tabularnewline
25 & 4.88 & 4.84115 & 4.84833 & -0.0071875 & 0.0388542 \tabularnewline
26 & 4.88 & 4.85073 & 4.86792 & -0.0171875 & 0.0292708 \tabularnewline
27 & 4.88 & 4.8649 & 4.88708 & -0.0221875 & 0.0151042 \tabularnewline
28 & 4.89 & 4.88623 & 4.90625 & -0.0200208 & 0.00377083 \tabularnewline
29 & 4.97 & 4.93631 & 4.92458 & 0.0117292 & 0.0336875 \tabularnewline
30 & 4.97 & 4.95423 & 4.93708 & 0.0171458 & 0.0157708 \tabularnewline
31 & 4.97 & 4.9679 & 4.94458 & 0.0233125 & 0.00210417 \tabularnewline
32 & 4.97 & 4.96665 & 4.95208 & 0.0145625 & 0.00335417 \tabularnewline
33 & 4.97 & 4.96731 & 4.95958 & 0.00772917 & 0.0026875 \tabularnewline
34 & 4.97 & 4.96465 & 4.96708 & -0.0024375 & 0.00535417 \tabularnewline
35 & 4.97 & 4.96215 & 4.97208 & -0.0099375 & 0.00785417 \tabularnewline
36 & 4.97 & 4.98031 & 4.97583 & 0.00447917 & -0.0103125 \tabularnewline
37 & 4.97 & 4.97406 & 4.98125 & -0.0071875 & -0.0040625 \tabularnewline
38 & 4.97 & 4.9699 & 4.98708 & -0.0171875 & 0.000104167 \tabularnewline
39 & 4.97 & 4.97115 & 4.99333 & -0.0221875 & -0.00114583 \tabularnewline
40 & 4.98 & 4.97998 & 5 & -0.0200208 & 2.08333e-05 \tabularnewline
41 & 5 & 5.0184 & 5.00667 & 0.0117292 & -0.0183958 \tabularnewline
42 & 5.03 & 5.0309 & 5.01375 & 0.0171458 & -0.000895833 \tabularnewline
43 & 5.04 & 5.04456 & 5.02125 & 0.0233125 & -0.0045625 \tabularnewline
44 & 5.04 & 5.04331 & 5.02875 & 0.0145625 & -0.0033125 \tabularnewline
45 & 5.05 & 5.0444 & 5.03667 & 0.00772917 & 0.00560417 \tabularnewline
46 & 5.05 & 5.04298 & 5.04542 & -0.0024375 & 0.00702083 \tabularnewline
47 & 5.05 & 5.04756 & 5.0575 & -0.0099375 & 0.0024375 \tabularnewline
48 & 5.06 & 5.07781 & 5.07333 & 0.00447917 & -0.0178125 \tabularnewline
49 & 5.06 & 5.08323 & 5.09042 & -0.0071875 & -0.0232292 \tabularnewline
50 & 5.06 & 5.09115 & 5.10833 & -0.0171875 & -0.0311458 \tabularnewline
51 & 5.07 & 5.1049 & 5.12708 & -0.0221875 & -0.0348958 \tabularnewline
52 & 5.09 & 5.12665 & 5.14667 & -0.0200208 & -0.0366458 \tabularnewline
53 & 5.18 & 5.1784 & 5.16667 & 0.0117292 & 0.00160417 \tabularnewline
54 & 5.23 & 5.2034 & 5.18625 & 0.0171458 & 0.0266042 \tabularnewline
55 & 5.25 & 5.22873 & 5.20542 & 0.0233125 & 0.0212708 \tabularnewline
56 & 5.26 & 5.23956 & 5.225 & 0.0145625 & 0.0204375 \tabularnewline
57 & 5.28 & 5.25231 & 5.24458 & 0.00772917 & 0.0276875 \tabularnewline
58 & 5.29 & 5.26048 & 5.26292 & -0.0024375 & 0.0295208 \tabularnewline
59 & 5.29 & 5.26756 & 5.2775 & -0.0099375 & 0.0224375 \tabularnewline
60 & 5.29 & 5.29198 & 5.2875 & 0.00447917 & -0.00197917 \tabularnewline
61 & 5.29 & 5.28781 & 5.295 & -0.0071875 & 0.0021875 \tabularnewline
62 & 5.3 & 5.28573 & 5.30292 & -0.0171875 & 0.0142708 \tabularnewline
63 & 5.3 & 5.2924 & 5.31458 & -0.0221875 & 0.00760417 \tabularnewline
64 & 5.3 & 5.30915 & 5.32917 & -0.0200208 & -0.00914583 \tabularnewline
65 & 5.32 & 5.35715 & 5.34542 & 0.0117292 & -0.0371458 \tabularnewline
66 & 5.33 & 5.38048 & 5.36333 & 0.0171458 & -0.0504792 \tabularnewline
67 & 5.33 & NA & NA & 0.0233125 & NA \tabularnewline
68 & 5.37 & NA & NA & 0.0145625 & NA \tabularnewline
69 & 5.45 & NA & NA & 0.00772917 & NA \tabularnewline
70 & 5.47 & NA & NA & -0.0024375 & NA \tabularnewline
71 & 5.5 & NA & NA & -0.0099375 & NA \tabularnewline
72 & 5.51 & NA & NA & 0.00447917 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261024&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]4.53[/C][C]NA[/C][C]NA[/C][C]-0.0071875[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]4.53[/C][C]NA[/C][C]NA[/C][C]-0.0171875[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]4.53[/C][C]NA[/C][C]NA[/C][C]-0.0221875[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]4.61[/C][C]NA[/C][C]NA[/C][C]-0.0200208[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]4.63[/C][C]NA[/C][C]NA[/C][C]0.0117292[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]4.63[/C][C]NA[/C][C]NA[/C][C]0.0171458[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]4.63[/C][C]4.63081[/C][C]4.6075[/C][C]0.0233125[/C][C]-0.0008125[/C][/ROW]
[ROW][C]8[/C][C]4.63[/C][C]4.6304[/C][C]4.61583[/C][C]0.0145625[/C][C]-0.000395833[/C][/ROW]
[ROW][C]9[/C][C]4.63[/C][C]4.63315[/C][C]4.62542[/C][C]0.00772917[/C][C]-0.00314583[/C][/ROW]
[ROW][C]10[/C][C]4.63[/C][C]4.63215[/C][C]4.63458[/C][C]-0.0024375[/C][C]-0.00214583[/C][/ROW]
[ROW][C]11[/C][C]4.63[/C][C]4.63215[/C][C]4.64208[/C][C]-0.0099375[/C][C]-0.00214583[/C][/ROW]
[ROW][C]12[/C][C]4.63[/C][C]4.65448[/C][C]4.65[/C][C]0.00447917[/C][C]-0.0244792[/C][/ROW]
[ROW][C]13[/C][C]4.63[/C][C]4.65115[/C][C]4.65833[/C][C]-0.0071875[/C][C]-0.0211458[/C][/ROW]
[ROW][C]14[/C][C]4.63[/C][C]4.6499[/C][C]4.66708[/C][C]-0.0171875[/C][C]-0.0198958[/C][/ROW]
[ROW][C]15[/C][C]4.66[/C][C]4.65406[/C][C]4.67625[/C][C]-0.0221875[/C][C]0.0059375[/C][/ROW]
[ROW][C]16[/C][C]4.7[/C][C]4.6654[/C][C]4.68542[/C][C]-0.0200208[/C][C]0.0346042[/C][/ROW]
[ROW][C]17[/C][C]4.72[/C][C]4.70715[/C][C]4.69542[/C][C]0.0117292[/C][C]0.0128542[/C][/ROW]
[ROW][C]18[/C][C]4.73[/C][C]4.7284[/C][C]4.71125[/C][C]0.0171458[/C][C]0.00160417[/C][/ROW]
[ROW][C]19[/C][C]4.73[/C][C]4.7554[/C][C]4.73208[/C][C]0.0233125[/C][C]-0.0253958[/C][/ROW]
[ROW][C]20[/C][C]4.74[/C][C]4.76748[/C][C]4.75292[/C][C]0.0145625[/C][C]-0.0274792[/C][/ROW]
[ROW][C]21[/C][C]4.74[/C][C]4.78023[/C][C]4.7725[/C][C]0.00772917[/C][C]-0.0402292[/C][/ROW]
[ROW][C]22[/C][C]4.74[/C][C]4.78715[/C][C]4.78958[/C][C]-0.0024375[/C][C]-0.0471458[/C][/ROW]
[ROW][C]23[/C][C]4.76[/C][C]4.79798[/C][C]4.80792[/C][C]-0.0099375[/C][C]-0.0379792[/C][/ROW]
[ROW][C]24[/C][C]4.88[/C][C]4.83281[/C][C]4.82833[/C][C]0.00447917[/C][C]0.0471875[/C][/ROW]
[ROW][C]25[/C][C]4.88[/C][C]4.84115[/C][C]4.84833[/C][C]-0.0071875[/C][C]0.0388542[/C][/ROW]
[ROW][C]26[/C][C]4.88[/C][C]4.85073[/C][C]4.86792[/C][C]-0.0171875[/C][C]0.0292708[/C][/ROW]
[ROW][C]27[/C][C]4.88[/C][C]4.8649[/C][C]4.88708[/C][C]-0.0221875[/C][C]0.0151042[/C][/ROW]
[ROW][C]28[/C][C]4.89[/C][C]4.88623[/C][C]4.90625[/C][C]-0.0200208[/C][C]0.00377083[/C][/ROW]
[ROW][C]29[/C][C]4.97[/C][C]4.93631[/C][C]4.92458[/C][C]0.0117292[/C][C]0.0336875[/C][/ROW]
[ROW][C]30[/C][C]4.97[/C][C]4.95423[/C][C]4.93708[/C][C]0.0171458[/C][C]0.0157708[/C][/ROW]
[ROW][C]31[/C][C]4.97[/C][C]4.9679[/C][C]4.94458[/C][C]0.0233125[/C][C]0.00210417[/C][/ROW]
[ROW][C]32[/C][C]4.97[/C][C]4.96665[/C][C]4.95208[/C][C]0.0145625[/C][C]0.00335417[/C][/ROW]
[ROW][C]33[/C][C]4.97[/C][C]4.96731[/C][C]4.95958[/C][C]0.00772917[/C][C]0.0026875[/C][/ROW]
[ROW][C]34[/C][C]4.97[/C][C]4.96465[/C][C]4.96708[/C][C]-0.0024375[/C][C]0.00535417[/C][/ROW]
[ROW][C]35[/C][C]4.97[/C][C]4.96215[/C][C]4.97208[/C][C]-0.0099375[/C][C]0.00785417[/C][/ROW]
[ROW][C]36[/C][C]4.97[/C][C]4.98031[/C][C]4.97583[/C][C]0.00447917[/C][C]-0.0103125[/C][/ROW]
[ROW][C]37[/C][C]4.97[/C][C]4.97406[/C][C]4.98125[/C][C]-0.0071875[/C][C]-0.0040625[/C][/ROW]
[ROW][C]38[/C][C]4.97[/C][C]4.9699[/C][C]4.98708[/C][C]-0.0171875[/C][C]0.000104167[/C][/ROW]
[ROW][C]39[/C][C]4.97[/C][C]4.97115[/C][C]4.99333[/C][C]-0.0221875[/C][C]-0.00114583[/C][/ROW]
[ROW][C]40[/C][C]4.98[/C][C]4.97998[/C][C]5[/C][C]-0.0200208[/C][C]2.08333e-05[/C][/ROW]
[ROW][C]41[/C][C]5[/C][C]5.0184[/C][C]5.00667[/C][C]0.0117292[/C][C]-0.0183958[/C][/ROW]
[ROW][C]42[/C][C]5.03[/C][C]5.0309[/C][C]5.01375[/C][C]0.0171458[/C][C]-0.000895833[/C][/ROW]
[ROW][C]43[/C][C]5.04[/C][C]5.04456[/C][C]5.02125[/C][C]0.0233125[/C][C]-0.0045625[/C][/ROW]
[ROW][C]44[/C][C]5.04[/C][C]5.04331[/C][C]5.02875[/C][C]0.0145625[/C][C]-0.0033125[/C][/ROW]
[ROW][C]45[/C][C]5.05[/C][C]5.0444[/C][C]5.03667[/C][C]0.00772917[/C][C]0.00560417[/C][/ROW]
[ROW][C]46[/C][C]5.05[/C][C]5.04298[/C][C]5.04542[/C][C]-0.0024375[/C][C]0.00702083[/C][/ROW]
[ROW][C]47[/C][C]5.05[/C][C]5.04756[/C][C]5.0575[/C][C]-0.0099375[/C][C]0.0024375[/C][/ROW]
[ROW][C]48[/C][C]5.06[/C][C]5.07781[/C][C]5.07333[/C][C]0.00447917[/C][C]-0.0178125[/C][/ROW]
[ROW][C]49[/C][C]5.06[/C][C]5.08323[/C][C]5.09042[/C][C]-0.0071875[/C][C]-0.0232292[/C][/ROW]
[ROW][C]50[/C][C]5.06[/C][C]5.09115[/C][C]5.10833[/C][C]-0.0171875[/C][C]-0.0311458[/C][/ROW]
[ROW][C]51[/C][C]5.07[/C][C]5.1049[/C][C]5.12708[/C][C]-0.0221875[/C][C]-0.0348958[/C][/ROW]
[ROW][C]52[/C][C]5.09[/C][C]5.12665[/C][C]5.14667[/C][C]-0.0200208[/C][C]-0.0366458[/C][/ROW]
[ROW][C]53[/C][C]5.18[/C][C]5.1784[/C][C]5.16667[/C][C]0.0117292[/C][C]0.00160417[/C][/ROW]
[ROW][C]54[/C][C]5.23[/C][C]5.2034[/C][C]5.18625[/C][C]0.0171458[/C][C]0.0266042[/C][/ROW]
[ROW][C]55[/C][C]5.25[/C][C]5.22873[/C][C]5.20542[/C][C]0.0233125[/C][C]0.0212708[/C][/ROW]
[ROW][C]56[/C][C]5.26[/C][C]5.23956[/C][C]5.225[/C][C]0.0145625[/C][C]0.0204375[/C][/ROW]
[ROW][C]57[/C][C]5.28[/C][C]5.25231[/C][C]5.24458[/C][C]0.00772917[/C][C]0.0276875[/C][/ROW]
[ROW][C]58[/C][C]5.29[/C][C]5.26048[/C][C]5.26292[/C][C]-0.0024375[/C][C]0.0295208[/C][/ROW]
[ROW][C]59[/C][C]5.29[/C][C]5.26756[/C][C]5.2775[/C][C]-0.0099375[/C][C]0.0224375[/C][/ROW]
[ROW][C]60[/C][C]5.29[/C][C]5.29198[/C][C]5.2875[/C][C]0.00447917[/C][C]-0.00197917[/C][/ROW]
[ROW][C]61[/C][C]5.29[/C][C]5.28781[/C][C]5.295[/C][C]-0.0071875[/C][C]0.0021875[/C][/ROW]
[ROW][C]62[/C][C]5.3[/C][C]5.28573[/C][C]5.30292[/C][C]-0.0171875[/C][C]0.0142708[/C][/ROW]
[ROW][C]63[/C][C]5.3[/C][C]5.2924[/C][C]5.31458[/C][C]-0.0221875[/C][C]0.00760417[/C][/ROW]
[ROW][C]64[/C][C]5.3[/C][C]5.30915[/C][C]5.32917[/C][C]-0.0200208[/C][C]-0.00914583[/C][/ROW]
[ROW][C]65[/C][C]5.32[/C][C]5.35715[/C][C]5.34542[/C][C]0.0117292[/C][C]-0.0371458[/C][/ROW]
[ROW][C]66[/C][C]5.33[/C][C]5.38048[/C][C]5.36333[/C][C]0.0171458[/C][C]-0.0504792[/C][/ROW]
[ROW][C]67[/C][C]5.33[/C][C]NA[/C][C]NA[/C][C]0.0233125[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]5.37[/C][C]NA[/C][C]NA[/C][C]0.0145625[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]5.45[/C][C]NA[/C][C]NA[/C][C]0.00772917[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]5.47[/C][C]NA[/C][C]NA[/C][C]-0.0024375[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]5.5[/C][C]NA[/C][C]NA[/C][C]-0.0099375[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]5.51[/C][C]NA[/C][C]NA[/C][C]0.00447917[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261024&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261024&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	4.53	NA	NA	-0.0071875	NA
2	4.53	NA	NA	-0.0171875	NA
3	4.53	NA	NA	-0.0221875	NA
4	4.61	NA	NA	-0.0200208	NA
5	4.63	NA	NA	0.0117292	NA
6	4.63	NA	NA	0.0171458	NA
7	4.63	4.63081	4.6075	0.0233125	-0.0008125
8	4.63	4.6304	4.61583	0.0145625	-0.000395833
9	4.63	4.63315	4.62542	0.00772917	-0.00314583
10	4.63	4.63215	4.63458	-0.0024375	-0.00214583
11	4.63	4.63215	4.64208	-0.0099375	-0.00214583
12	4.63	4.65448	4.65	0.00447917	-0.0244792
13	4.63	4.65115	4.65833	-0.0071875	-0.0211458
14	4.63	4.6499	4.66708	-0.0171875	-0.0198958
15	4.66	4.65406	4.67625	-0.0221875	0.0059375
16	4.7	4.6654	4.68542	-0.0200208	0.0346042
17	4.72	4.70715	4.69542	0.0117292	0.0128542
18	4.73	4.7284	4.71125	0.0171458	0.00160417
19	4.73	4.7554	4.73208	0.0233125	-0.0253958
20	4.74	4.76748	4.75292	0.0145625	-0.0274792
21	4.74	4.78023	4.7725	0.00772917	-0.0402292
22	4.74	4.78715	4.78958	-0.0024375	-0.0471458
23	4.76	4.79798	4.80792	-0.0099375	-0.0379792
24	4.88	4.83281	4.82833	0.00447917	0.0471875
25	4.88	4.84115	4.84833	-0.0071875	0.0388542
26	4.88	4.85073	4.86792	-0.0171875	0.0292708
27	4.88	4.8649	4.88708	-0.0221875	0.0151042
28	4.89	4.88623	4.90625	-0.0200208	0.00377083
29	4.97	4.93631	4.92458	0.0117292	0.0336875
30	4.97	4.95423	4.93708	0.0171458	0.0157708
31	4.97	4.9679	4.94458	0.0233125	0.00210417
32	4.97	4.96665	4.95208	0.0145625	0.00335417
33	4.97	4.96731	4.95958	0.00772917	0.0026875
34	4.97	4.96465	4.96708	-0.0024375	0.00535417
35	4.97	4.96215	4.97208	-0.0099375	0.00785417
36	4.97	4.98031	4.97583	0.00447917	-0.0103125
37	4.97	4.97406	4.98125	-0.0071875	-0.0040625
38	4.97	4.9699	4.98708	-0.0171875	0.000104167
39	4.97	4.97115	4.99333	-0.0221875	-0.00114583
40	4.98	4.97998	5	-0.0200208	2.08333e-05
41	5	5.0184	5.00667	0.0117292	-0.0183958
42	5.03	5.0309	5.01375	0.0171458	-0.000895833
43	5.04	5.04456	5.02125	0.0233125	-0.0045625
44	5.04	5.04331	5.02875	0.0145625	-0.0033125
45	5.05	5.0444	5.03667	0.00772917	0.00560417
46	5.05	5.04298	5.04542	-0.0024375	0.00702083
47	5.05	5.04756	5.0575	-0.0099375	0.0024375
48	5.06	5.07781	5.07333	0.00447917	-0.0178125
49	5.06	5.08323	5.09042	-0.0071875	-0.0232292
50	5.06	5.09115	5.10833	-0.0171875	-0.0311458
51	5.07	5.1049	5.12708	-0.0221875	-0.0348958
52	5.09	5.12665	5.14667	-0.0200208	-0.0366458
53	5.18	5.1784	5.16667	0.0117292	0.00160417
54	5.23	5.2034	5.18625	0.0171458	0.0266042
55	5.25	5.22873	5.20542	0.0233125	0.0212708
56	5.26	5.23956	5.225	0.0145625	0.0204375
57	5.28	5.25231	5.24458	0.00772917	0.0276875
58	5.29	5.26048	5.26292	-0.0024375	0.0295208
59	5.29	5.26756	5.2775	-0.0099375	0.0224375
60	5.29	5.29198	5.2875	0.00447917	-0.00197917
61	5.29	5.28781	5.295	-0.0071875	0.0021875
62	5.3	5.28573	5.30292	-0.0171875	0.0142708
63	5.3	5.2924	5.31458	-0.0221875	0.00760417
64	5.3	5.30915	5.32917	-0.0200208	-0.00914583
65	5.32	5.35715	5.34542	0.0117292	-0.0371458
66	5.33	5.38048	5.36333	0.0171458	-0.0504792
67	5.33	NA	NA	0.0233125	NA
68	5.37	NA	NA	0.0145625	NA
69	5.45	NA	NA	0.00772917	NA
70	5.47	NA	NA	-0.0024375	NA
71	5.5	NA	NA	-0.0099375	NA
72	5.51	NA	NA	0.00447917	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 <- 'multiplicative'
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