Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Fri, 28 Nov 2014 16:38:41 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/28/t14171927488zkkvn2btub163y.htm/, Retrieved Sun, 19 May 2024 14:06:06 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=260968, Retrieved Sun, 19 May 2024 14:06:06 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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 16:38:41] [d41d8cd98f00b204e9800998ecf8427e] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

2,37
2,45
2,53
2,56
2,62
2,67
2,62
2,6
2,53
2,49
2,48
2,44
2,36
2,35
2,44
2,5
2,58
2,55
2,44
2,3
2,24
2,19
2,25
2,28
2,27
2,37
2,47
2,5
2,47
2,61
2,61
2,65
2,43
2,43
2,33
2,27
2,22
2,17
2,28
2,3
2,33
2,44
2,41
2,4
2,34
2,37
2,38
2,3
2,29
2,34
2,35
2,38
2,37
2,45
2,51
2,46
2,42
2,48
2,44
2,43
2,36
2,42
2,42
2,43
2,47
2,54
2,55
2,55
2,49
2,54
2,55
2,5

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=260968&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=260968&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260968&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	2.37	NA	NA	-0.10625	NA
2	2.45	NA	NA	-0.07525	NA
3	2.53	NA	NA	-0.0125	NA
4	2.56	NA	NA	0.0174167	NA
5	2.62	NA	NA	0.0384167	NA
6	2.67	NA	NA	0.111333	NA
7	2.62	2.6315	2.52958	0.101917	-0.0115
8	2.6	2.59125	2.525	0.06625	0.00875
9	2.53	2.4945	2.51708	-0.0225833	0.0355
10	2.49	2.49025	2.51083	-0.0205833	-0.00025
11	2.48	2.47242	2.50667	-0.03425	0.00758333
12	2.44	2.43608	2.5	-0.0639167	0.00391667
13	2.36	2.38125	2.4875	-0.10625	-0.02125
14	2.35	2.39225	2.4675	-0.07525	-0.04225
15	2.44	2.43042	2.44292	-0.0125	0.00958333
16	2.5	2.43575	2.41833	0.0174167	0.06425
17	2.58	2.43467	2.39625	0.0384167	0.145333
18	2.55	2.49133	2.38	0.111333	0.0586667
19	2.44	2.4715	2.36958	0.101917	-0.0315
20	2.3	2.43292	2.36667	0.06625	-0.132917
21	2.24	2.34617	2.36875	-0.0225833	-0.106167
22	2.19	2.34942	2.37	-0.0205833	-0.159417
23	2.25	2.33117	2.36542	-0.03425	-0.0811667
24	2.28	2.29942	2.36333	-0.0639167	-0.0194167
25	2.27	2.26667	2.37292	-0.10625	0.00333333
26	2.37	2.31933	2.39458	-0.07525	0.0506667
27	2.47	2.40458	2.41708	-0.0125	0.0654167
28	2.5	2.45242	2.435	0.0174167	0.0475833
29	2.47	2.48675	2.44833	0.0384167	-0.01675
30	2.61	2.56258	2.45125	0.111333	0.0474167
31	2.61	2.55067	2.44875	0.101917	0.0593333
32	2.65	2.50458	2.43833	0.06625	0.145417
33	2.43	2.3995	2.42208	-0.0225833	0.0305
34	2.43	2.38525	2.40583	-0.0205833	0.04475
35	2.33	2.35742	2.39167	-0.03425	-0.0274167
36	2.27	2.31483	2.37875	-0.0639167	-0.0448333
37	2.22	2.25708	2.36333	-0.10625	-0.0370833
38	2.17	2.26933	2.34458	-0.07525	-0.0993333
39	2.28	2.31792	2.33042	-0.0125	-0.0379167
40	2.3	2.34158	2.32417	0.0174167	-0.0415833
41	2.33	2.36217	2.32375	0.0384167	-0.0321667
42	2.44	2.43842	2.32708	0.111333	0.00158333
43	2.41	2.43317	2.33125	0.101917	-0.0231667
44	2.4	2.4075	2.34125	0.06625	-0.0075
45	2.34	2.32867	2.35125	-0.0225833	0.0113333
46	2.37	2.33692	2.3575	-0.0205833	0.0330833
47	2.38	2.32825	2.3625	-0.03425	0.05175
48	2.3	2.30067	2.36458	-0.0639167	-0.000666667
49	2.29	2.26292	2.36917	-0.10625	0.0270833
50	2.34	2.30058	2.37583	-0.07525	0.0394167
51	2.35	2.36917	2.38167	-0.0125	-0.0191667
52	2.38	2.407	2.38958	0.0174167	-0.027
53	2.37	2.43508	2.39667	0.0384167	-0.0650833
54	2.45	2.51592	2.40458	0.111333	-0.0659167
55	2.51	2.51483	2.41292	0.101917	-0.00483333
56	2.46	2.48542	2.41917	0.06625	-0.0254167
57	2.42	2.40283	2.42542	-0.0225833	0.0171667
58	2.48	2.40983	2.43042	-0.0205833	0.0701667
59	2.44	2.40242	2.43667	-0.03425	0.0375833
60	2.43	2.38067	2.44458	-0.0639167	0.0493333
61	2.36	2.34375	2.45	-0.10625	0.01625
62	2.42	2.38017	2.45542	-0.07525	0.0398333
63	2.42	2.44958	2.46208	-0.0125	-0.0295833
64	2.43	2.48492	2.4675	0.0174167	-0.0549167
65	2.47	2.513	2.47458	0.0384167	-0.043
66	2.54	2.59342	2.48208	0.111333	-0.0534167
67	2.55	NA	NA	0.101917	NA
68	2.55	NA	NA	0.06625	NA
69	2.49	NA	NA	-0.0225833	NA
70	2.54	NA	NA	-0.0205833	NA
71	2.55	NA	NA	-0.03425	NA
72	2.5	NA	NA	-0.0639167	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.37 & NA & NA & -0.10625 & NA \tabularnewline
2 & 2.45 & NA & NA & -0.07525 & NA \tabularnewline
3 & 2.53 & NA & NA & -0.0125 & NA \tabularnewline
4 & 2.56 & NA & NA & 0.0174167 & NA \tabularnewline
5 & 2.62 & NA & NA & 0.0384167 & NA \tabularnewline
6 & 2.67 & NA & NA & 0.111333 & NA \tabularnewline
7 & 2.62 & 2.6315 & 2.52958 & 0.101917 & -0.0115 \tabularnewline
8 & 2.6 & 2.59125 & 2.525 & 0.06625 & 0.00875 \tabularnewline
9 & 2.53 & 2.4945 & 2.51708 & -0.0225833 & 0.0355 \tabularnewline
10 & 2.49 & 2.49025 & 2.51083 & -0.0205833 & -0.00025 \tabularnewline
11 & 2.48 & 2.47242 & 2.50667 & -0.03425 & 0.00758333 \tabularnewline
12 & 2.44 & 2.43608 & 2.5 & -0.0639167 & 0.00391667 \tabularnewline
13 & 2.36 & 2.38125 & 2.4875 & -0.10625 & -0.02125 \tabularnewline
14 & 2.35 & 2.39225 & 2.4675 & -0.07525 & -0.04225 \tabularnewline
15 & 2.44 & 2.43042 & 2.44292 & -0.0125 & 0.00958333 \tabularnewline
16 & 2.5 & 2.43575 & 2.41833 & 0.0174167 & 0.06425 \tabularnewline
17 & 2.58 & 2.43467 & 2.39625 & 0.0384167 & 0.145333 \tabularnewline
18 & 2.55 & 2.49133 & 2.38 & 0.111333 & 0.0586667 \tabularnewline
19 & 2.44 & 2.4715 & 2.36958 & 0.101917 & -0.0315 \tabularnewline
20 & 2.3 & 2.43292 & 2.36667 & 0.06625 & -0.132917 \tabularnewline
21 & 2.24 & 2.34617 & 2.36875 & -0.0225833 & -0.106167 \tabularnewline
22 & 2.19 & 2.34942 & 2.37 & -0.0205833 & -0.159417 \tabularnewline
23 & 2.25 & 2.33117 & 2.36542 & -0.03425 & -0.0811667 \tabularnewline
24 & 2.28 & 2.29942 & 2.36333 & -0.0639167 & -0.0194167 \tabularnewline
25 & 2.27 & 2.26667 & 2.37292 & -0.10625 & 0.00333333 \tabularnewline
26 & 2.37 & 2.31933 & 2.39458 & -0.07525 & 0.0506667 \tabularnewline
27 & 2.47 & 2.40458 & 2.41708 & -0.0125 & 0.0654167 \tabularnewline
28 & 2.5 & 2.45242 & 2.435 & 0.0174167 & 0.0475833 \tabularnewline
29 & 2.47 & 2.48675 & 2.44833 & 0.0384167 & -0.01675 \tabularnewline
30 & 2.61 & 2.56258 & 2.45125 & 0.111333 & 0.0474167 \tabularnewline
31 & 2.61 & 2.55067 & 2.44875 & 0.101917 & 0.0593333 \tabularnewline
32 & 2.65 & 2.50458 & 2.43833 & 0.06625 & 0.145417 \tabularnewline
33 & 2.43 & 2.3995 & 2.42208 & -0.0225833 & 0.0305 \tabularnewline
34 & 2.43 & 2.38525 & 2.40583 & -0.0205833 & 0.04475 \tabularnewline
35 & 2.33 & 2.35742 & 2.39167 & -0.03425 & -0.0274167 \tabularnewline
36 & 2.27 & 2.31483 & 2.37875 & -0.0639167 & -0.0448333 \tabularnewline
37 & 2.22 & 2.25708 & 2.36333 & -0.10625 & -0.0370833 \tabularnewline
38 & 2.17 & 2.26933 & 2.34458 & -0.07525 & -0.0993333 \tabularnewline
39 & 2.28 & 2.31792 & 2.33042 & -0.0125 & -0.0379167 \tabularnewline
40 & 2.3 & 2.34158 & 2.32417 & 0.0174167 & -0.0415833 \tabularnewline
41 & 2.33 & 2.36217 & 2.32375 & 0.0384167 & -0.0321667 \tabularnewline
42 & 2.44 & 2.43842 & 2.32708 & 0.111333 & 0.00158333 \tabularnewline
43 & 2.41 & 2.43317 & 2.33125 & 0.101917 & -0.0231667 \tabularnewline
44 & 2.4 & 2.4075 & 2.34125 & 0.06625 & -0.0075 \tabularnewline
45 & 2.34 & 2.32867 & 2.35125 & -0.0225833 & 0.0113333 \tabularnewline
46 & 2.37 & 2.33692 & 2.3575 & -0.0205833 & 0.0330833 \tabularnewline
47 & 2.38 & 2.32825 & 2.3625 & -0.03425 & 0.05175 \tabularnewline
48 & 2.3 & 2.30067 & 2.36458 & -0.0639167 & -0.000666667 \tabularnewline
49 & 2.29 & 2.26292 & 2.36917 & -0.10625 & 0.0270833 \tabularnewline
50 & 2.34 & 2.30058 & 2.37583 & -0.07525 & 0.0394167 \tabularnewline
51 & 2.35 & 2.36917 & 2.38167 & -0.0125 & -0.0191667 \tabularnewline
52 & 2.38 & 2.407 & 2.38958 & 0.0174167 & -0.027 \tabularnewline
53 & 2.37 & 2.43508 & 2.39667 & 0.0384167 & -0.0650833 \tabularnewline
54 & 2.45 & 2.51592 & 2.40458 & 0.111333 & -0.0659167 \tabularnewline
55 & 2.51 & 2.51483 & 2.41292 & 0.101917 & -0.00483333 \tabularnewline
56 & 2.46 & 2.48542 & 2.41917 & 0.06625 & -0.0254167 \tabularnewline
57 & 2.42 & 2.40283 & 2.42542 & -0.0225833 & 0.0171667 \tabularnewline
58 & 2.48 & 2.40983 & 2.43042 & -0.0205833 & 0.0701667 \tabularnewline
59 & 2.44 & 2.40242 & 2.43667 & -0.03425 & 0.0375833 \tabularnewline
60 & 2.43 & 2.38067 & 2.44458 & -0.0639167 & 0.0493333 \tabularnewline
61 & 2.36 & 2.34375 & 2.45 & -0.10625 & 0.01625 \tabularnewline
62 & 2.42 & 2.38017 & 2.45542 & -0.07525 & 0.0398333 \tabularnewline
63 & 2.42 & 2.44958 & 2.46208 & -0.0125 & -0.0295833 \tabularnewline
64 & 2.43 & 2.48492 & 2.4675 & 0.0174167 & -0.0549167 \tabularnewline
65 & 2.47 & 2.513 & 2.47458 & 0.0384167 & -0.043 \tabularnewline
66 & 2.54 & 2.59342 & 2.48208 & 0.111333 & -0.0534167 \tabularnewline
67 & 2.55 & NA & NA & 0.101917 & NA \tabularnewline
68 & 2.55 & NA & NA & 0.06625 & NA \tabularnewline
69 & 2.49 & NA & NA & -0.0225833 & NA \tabularnewline
70 & 2.54 & NA & NA & -0.0205833 & NA \tabularnewline
71 & 2.55 & NA & NA & -0.03425 & NA \tabularnewline
72 & 2.5 & NA & NA & -0.0639167 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=260968&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]2.37[/C][C]NA[/C][C]NA[/C][C]-0.10625[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.45[/C][C]NA[/C][C]NA[/C][C]-0.07525[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.53[/C][C]NA[/C][C]NA[/C][C]-0.0125[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.56[/C][C]NA[/C][C]NA[/C][C]0.0174167[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.62[/C][C]NA[/C][C]NA[/C][C]0.0384167[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.67[/C][C]NA[/C][C]NA[/C][C]0.111333[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.62[/C][C]2.6315[/C][C]2.52958[/C][C]0.101917[/C][C]-0.0115[/C][/ROW]
[ROW][C]8[/C][C]2.6[/C][C]2.59125[/C][C]2.525[/C][C]0.06625[/C][C]0.00875[/C][/ROW]
[ROW][C]9[/C][C]2.53[/C][C]2.4945[/C][C]2.51708[/C][C]-0.0225833[/C][C]0.0355[/C][/ROW]
[ROW][C]10[/C][C]2.49[/C][C]2.49025[/C][C]2.51083[/C][C]-0.0205833[/C][C]-0.00025[/C][/ROW]
[ROW][C]11[/C][C]2.48[/C][C]2.47242[/C][C]2.50667[/C][C]-0.03425[/C][C]0.00758333[/C][/ROW]
[ROW][C]12[/C][C]2.44[/C][C]2.43608[/C][C]2.5[/C][C]-0.0639167[/C][C]0.00391667[/C][/ROW]
[ROW][C]13[/C][C]2.36[/C][C]2.38125[/C][C]2.4875[/C][C]-0.10625[/C][C]-0.02125[/C][/ROW]
[ROW][C]14[/C][C]2.35[/C][C]2.39225[/C][C]2.4675[/C][C]-0.07525[/C][C]-0.04225[/C][/ROW]
[ROW][C]15[/C][C]2.44[/C][C]2.43042[/C][C]2.44292[/C][C]-0.0125[/C][C]0.00958333[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]2.43575[/C][C]2.41833[/C][C]0.0174167[/C][C]0.06425[/C][/ROW]
[ROW][C]17[/C][C]2.58[/C][C]2.43467[/C][C]2.39625[/C][C]0.0384167[/C][C]0.145333[/C][/ROW]
[ROW][C]18[/C][C]2.55[/C][C]2.49133[/C][C]2.38[/C][C]0.111333[/C][C]0.0586667[/C][/ROW]
[ROW][C]19[/C][C]2.44[/C][C]2.4715[/C][C]2.36958[/C][C]0.101917[/C][C]-0.0315[/C][/ROW]
[ROW][C]20[/C][C]2.3[/C][C]2.43292[/C][C]2.36667[/C][C]0.06625[/C][C]-0.132917[/C][/ROW]
[ROW][C]21[/C][C]2.24[/C][C]2.34617[/C][C]2.36875[/C][C]-0.0225833[/C][C]-0.106167[/C][/ROW]
[ROW][C]22[/C][C]2.19[/C][C]2.34942[/C][C]2.37[/C][C]-0.0205833[/C][C]-0.159417[/C][/ROW]
[ROW][C]23[/C][C]2.25[/C][C]2.33117[/C][C]2.36542[/C][C]-0.03425[/C][C]-0.0811667[/C][/ROW]
[ROW][C]24[/C][C]2.28[/C][C]2.29942[/C][C]2.36333[/C][C]-0.0639167[/C][C]-0.0194167[/C][/ROW]
[ROW][C]25[/C][C]2.27[/C][C]2.26667[/C][C]2.37292[/C][C]-0.10625[/C][C]0.00333333[/C][/ROW]
[ROW][C]26[/C][C]2.37[/C][C]2.31933[/C][C]2.39458[/C][C]-0.07525[/C][C]0.0506667[/C][/ROW]
[ROW][C]27[/C][C]2.47[/C][C]2.40458[/C][C]2.41708[/C][C]-0.0125[/C][C]0.0654167[/C][/ROW]
[ROW][C]28[/C][C]2.5[/C][C]2.45242[/C][C]2.435[/C][C]0.0174167[/C][C]0.0475833[/C][/ROW]
[ROW][C]29[/C][C]2.47[/C][C]2.48675[/C][C]2.44833[/C][C]0.0384167[/C][C]-0.01675[/C][/ROW]
[ROW][C]30[/C][C]2.61[/C][C]2.56258[/C][C]2.45125[/C][C]0.111333[/C][C]0.0474167[/C][/ROW]
[ROW][C]31[/C][C]2.61[/C][C]2.55067[/C][C]2.44875[/C][C]0.101917[/C][C]0.0593333[/C][/ROW]
[ROW][C]32[/C][C]2.65[/C][C]2.50458[/C][C]2.43833[/C][C]0.06625[/C][C]0.145417[/C][/ROW]
[ROW][C]33[/C][C]2.43[/C][C]2.3995[/C][C]2.42208[/C][C]-0.0225833[/C][C]0.0305[/C][/ROW]
[ROW][C]34[/C][C]2.43[/C][C]2.38525[/C][C]2.40583[/C][C]-0.0205833[/C][C]0.04475[/C][/ROW]
[ROW][C]35[/C][C]2.33[/C][C]2.35742[/C][C]2.39167[/C][C]-0.03425[/C][C]-0.0274167[/C][/ROW]
[ROW][C]36[/C][C]2.27[/C][C]2.31483[/C][C]2.37875[/C][C]-0.0639167[/C][C]-0.0448333[/C][/ROW]
[ROW][C]37[/C][C]2.22[/C][C]2.25708[/C][C]2.36333[/C][C]-0.10625[/C][C]-0.0370833[/C][/ROW]
[ROW][C]38[/C][C]2.17[/C][C]2.26933[/C][C]2.34458[/C][C]-0.07525[/C][C]-0.0993333[/C][/ROW]
[ROW][C]39[/C][C]2.28[/C][C]2.31792[/C][C]2.33042[/C][C]-0.0125[/C][C]-0.0379167[/C][/ROW]
[ROW][C]40[/C][C]2.3[/C][C]2.34158[/C][C]2.32417[/C][C]0.0174167[/C][C]-0.0415833[/C][/ROW]
[ROW][C]41[/C][C]2.33[/C][C]2.36217[/C][C]2.32375[/C][C]0.0384167[/C][C]-0.0321667[/C][/ROW]
[ROW][C]42[/C][C]2.44[/C][C]2.43842[/C][C]2.32708[/C][C]0.111333[/C][C]0.00158333[/C][/ROW]
[ROW][C]43[/C][C]2.41[/C][C]2.43317[/C][C]2.33125[/C][C]0.101917[/C][C]-0.0231667[/C][/ROW]
[ROW][C]44[/C][C]2.4[/C][C]2.4075[/C][C]2.34125[/C][C]0.06625[/C][C]-0.0075[/C][/ROW]
[ROW][C]45[/C][C]2.34[/C][C]2.32867[/C][C]2.35125[/C][C]-0.0225833[/C][C]0.0113333[/C][/ROW]
[ROW][C]46[/C][C]2.37[/C][C]2.33692[/C][C]2.3575[/C][C]-0.0205833[/C][C]0.0330833[/C][/ROW]
[ROW][C]47[/C][C]2.38[/C][C]2.32825[/C][C]2.3625[/C][C]-0.03425[/C][C]0.05175[/C][/ROW]
[ROW][C]48[/C][C]2.3[/C][C]2.30067[/C][C]2.36458[/C][C]-0.0639167[/C][C]-0.000666667[/C][/ROW]
[ROW][C]49[/C][C]2.29[/C][C]2.26292[/C][C]2.36917[/C][C]-0.10625[/C][C]0.0270833[/C][/ROW]
[ROW][C]50[/C][C]2.34[/C][C]2.30058[/C][C]2.37583[/C][C]-0.07525[/C][C]0.0394167[/C][/ROW]
[ROW][C]51[/C][C]2.35[/C][C]2.36917[/C][C]2.38167[/C][C]-0.0125[/C][C]-0.0191667[/C][/ROW]
[ROW][C]52[/C][C]2.38[/C][C]2.407[/C][C]2.38958[/C][C]0.0174167[/C][C]-0.027[/C][/ROW]
[ROW][C]53[/C][C]2.37[/C][C]2.43508[/C][C]2.39667[/C][C]0.0384167[/C][C]-0.0650833[/C][/ROW]
[ROW][C]54[/C][C]2.45[/C][C]2.51592[/C][C]2.40458[/C][C]0.111333[/C][C]-0.0659167[/C][/ROW]
[ROW][C]55[/C][C]2.51[/C][C]2.51483[/C][C]2.41292[/C][C]0.101917[/C][C]-0.00483333[/C][/ROW]
[ROW][C]56[/C][C]2.46[/C][C]2.48542[/C][C]2.41917[/C][C]0.06625[/C][C]-0.0254167[/C][/ROW]
[ROW][C]57[/C][C]2.42[/C][C]2.40283[/C][C]2.42542[/C][C]-0.0225833[/C][C]0.0171667[/C][/ROW]
[ROW][C]58[/C][C]2.48[/C][C]2.40983[/C][C]2.43042[/C][C]-0.0205833[/C][C]0.0701667[/C][/ROW]
[ROW][C]59[/C][C]2.44[/C][C]2.40242[/C][C]2.43667[/C][C]-0.03425[/C][C]0.0375833[/C][/ROW]
[ROW][C]60[/C][C]2.43[/C][C]2.38067[/C][C]2.44458[/C][C]-0.0639167[/C][C]0.0493333[/C][/ROW]
[ROW][C]61[/C][C]2.36[/C][C]2.34375[/C][C]2.45[/C][C]-0.10625[/C][C]0.01625[/C][/ROW]
[ROW][C]62[/C][C]2.42[/C][C]2.38017[/C][C]2.45542[/C][C]-0.07525[/C][C]0.0398333[/C][/ROW]
[ROW][C]63[/C][C]2.42[/C][C]2.44958[/C][C]2.46208[/C][C]-0.0125[/C][C]-0.0295833[/C][/ROW]
[ROW][C]64[/C][C]2.43[/C][C]2.48492[/C][C]2.4675[/C][C]0.0174167[/C][C]-0.0549167[/C][/ROW]
[ROW][C]65[/C][C]2.47[/C][C]2.513[/C][C]2.47458[/C][C]0.0384167[/C][C]-0.043[/C][/ROW]
[ROW][C]66[/C][C]2.54[/C][C]2.59342[/C][C]2.48208[/C][C]0.111333[/C][C]-0.0534167[/C][/ROW]
[ROW][C]67[/C][C]2.55[/C][C]NA[/C][C]NA[/C][C]0.101917[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]2.55[/C][C]NA[/C][C]NA[/C][C]0.06625[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]2.49[/C][C]NA[/C][C]NA[/C][C]-0.0225833[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]2.54[/C][C]NA[/C][C]NA[/C][C]-0.0205833[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]2.55[/C][C]NA[/C][C]NA[/C][C]-0.03425[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]-0.0639167[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=260968&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=260968&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	2.37	NA	NA	-0.10625	NA
2	2.45	NA	NA	-0.07525	NA
3	2.53	NA	NA	-0.0125	NA
4	2.56	NA	NA	0.0174167	NA
5	2.62	NA	NA	0.0384167	NA
6	2.67	NA	NA	0.111333	NA
7	2.62	2.6315	2.52958	0.101917	-0.0115
8	2.6	2.59125	2.525	0.06625	0.00875
9	2.53	2.4945	2.51708	-0.0225833	0.0355
10	2.49	2.49025	2.51083	-0.0205833	-0.00025
11	2.48	2.47242	2.50667	-0.03425	0.00758333
12	2.44	2.43608	2.5	-0.0639167	0.00391667
13	2.36	2.38125	2.4875	-0.10625	-0.02125
14	2.35	2.39225	2.4675	-0.07525	-0.04225
15	2.44	2.43042	2.44292	-0.0125	0.00958333
16	2.5	2.43575	2.41833	0.0174167	0.06425
17	2.58	2.43467	2.39625	0.0384167	0.145333
18	2.55	2.49133	2.38	0.111333	0.0586667
19	2.44	2.4715	2.36958	0.101917	-0.0315
20	2.3	2.43292	2.36667	0.06625	-0.132917
21	2.24	2.34617	2.36875	-0.0225833	-0.106167
22	2.19	2.34942	2.37	-0.0205833	-0.159417
23	2.25	2.33117	2.36542	-0.03425	-0.0811667
24	2.28	2.29942	2.36333	-0.0639167	-0.0194167
25	2.27	2.26667	2.37292	-0.10625	0.00333333
26	2.37	2.31933	2.39458	-0.07525	0.0506667
27	2.47	2.40458	2.41708	-0.0125	0.0654167
28	2.5	2.45242	2.435	0.0174167	0.0475833
29	2.47	2.48675	2.44833	0.0384167	-0.01675
30	2.61	2.56258	2.45125	0.111333	0.0474167
31	2.61	2.55067	2.44875	0.101917	0.0593333
32	2.65	2.50458	2.43833	0.06625	0.145417
33	2.43	2.3995	2.42208	-0.0225833	0.0305
34	2.43	2.38525	2.40583	-0.0205833	0.04475
35	2.33	2.35742	2.39167	-0.03425	-0.0274167
36	2.27	2.31483	2.37875	-0.0639167	-0.0448333
37	2.22	2.25708	2.36333	-0.10625	-0.0370833
38	2.17	2.26933	2.34458	-0.07525	-0.0993333
39	2.28	2.31792	2.33042	-0.0125	-0.0379167
40	2.3	2.34158	2.32417	0.0174167	-0.0415833
41	2.33	2.36217	2.32375	0.0384167	-0.0321667
42	2.44	2.43842	2.32708	0.111333	0.00158333
43	2.41	2.43317	2.33125	0.101917	-0.0231667
44	2.4	2.4075	2.34125	0.06625	-0.0075
45	2.34	2.32867	2.35125	-0.0225833	0.0113333
46	2.37	2.33692	2.3575	-0.0205833	0.0330833
47	2.38	2.32825	2.3625	-0.03425	0.05175
48	2.3	2.30067	2.36458	-0.0639167	-0.000666667
49	2.29	2.26292	2.36917	-0.10625	0.0270833
50	2.34	2.30058	2.37583	-0.07525	0.0394167
51	2.35	2.36917	2.38167	-0.0125	-0.0191667
52	2.38	2.407	2.38958	0.0174167	-0.027
53	2.37	2.43508	2.39667	0.0384167	-0.0650833
54	2.45	2.51592	2.40458	0.111333	-0.0659167
55	2.51	2.51483	2.41292	0.101917	-0.00483333
56	2.46	2.48542	2.41917	0.06625	-0.0254167
57	2.42	2.40283	2.42542	-0.0225833	0.0171667
58	2.48	2.40983	2.43042	-0.0205833	0.0701667
59	2.44	2.40242	2.43667	-0.03425	0.0375833
60	2.43	2.38067	2.44458	-0.0639167	0.0493333
61	2.36	2.34375	2.45	-0.10625	0.01625
62	2.42	2.38017	2.45542	-0.07525	0.0398333
63	2.42	2.44958	2.46208	-0.0125	-0.0295833
64	2.43	2.48492	2.4675	0.0174167	-0.0549167
65	2.47	2.513	2.47458	0.0384167	-0.043
66	2.54	2.59342	2.48208	0.111333	-0.0534167
67	2.55	NA	NA	0.101917	NA
68	2.55	NA	NA	0.06625	NA
69	2.49	NA	NA	-0.0225833	NA
70	2.54	NA	NA	-0.0205833	NA
71	2.55	NA	NA	-0.03425	NA
72	2.5	NA	NA	-0.0639167	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