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

Sun, 30 Nov 2014 09:42:21 +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/30/t1417340608ioc30khhaljvhc2.htm/, Retrieved Wed, 26 Aug 2026 20:34:07 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261311, Retrieved Wed, 26 Aug 2026 20:34:07 +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

504

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

-       [Classical Decomposition] [] [2014-11-30 09:42:21] [4b199ad8119df16cb977784959786033] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

1,11
1,11
1,2
1,21
1,31
1,37
1,37
1,26
1,23
1,17
1,06
0,95
0,92
0,92
0,9
0,93
0,93
0,97
0,96
0,99
0,98
0,96
1
0,99
1,03
1,02
1,07
1,13
1,15
1,16
1,14
1,15
1,15
1,16
1,17
1,22
1,26
1,29
1,36
1,38
1,37
1,37
1,37
1,36
1,38
1,4
1,44
1,42
1,45
1,45
1,49
1,48
1,44
1,39
1,41
1,48
1,51
1,49
1,46
1,43
1,42
1,43
1,42
1,39
1,36
1,36
1,39
1,39
1,43
1,38
1,36
1,38

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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261311&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261311&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261311&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.11	NA	NA	-0.0216667	NA
2	1.11	NA	NA	-0.0169167	NA
3	1.2	NA	NA	0.00633333	NA
4	1.21	NA	NA	0.0169167	NA
5	1.31	NA	NA	0.000666667	NA
6	1.37	NA	NA	-0.00541667	NA
7	1.37	1.21567	1.18792	0.02775	0.154333
8	1.26	1.19258	1.17208	0.0205	0.0674167
9	1.23	1.16967	1.15167	0.018	0.0603333
10	1.17	1.12817	1.1275	0.000666667	0.0418333
11	1.06	1.08875	1.1	-0.01125	-0.02875
12	0.95	1.03192	1.0675	-0.0355833	-0.0819167
13	0.92	1.01208	1.03375	-0.0216667	-0.0920833
14	0.92	0.9885	1.00542	-0.0169167	-0.0685
15	0.9	0.990083	0.98375	0.00633333	-0.0900833
16	0.93	0.9815	0.964583	0.0169167	-0.0515
17	0.93	0.954	0.953333	0.000666667	-0.024
18	0.97	0.947083	0.9525	-0.00541667	0.0229167
19	0.96	0.9865	0.95875	0.02775	-0.0265
20	0.99	0.988	0.9675	0.0205	0.002
21	0.98	0.99675	0.97875	0.018	-0.01675
22	0.96	0.994833	0.994167	0.000666667	-0.0348333
23	1	1.00042	1.01167	-0.01125	-0.000416667
24	0.99	0.993167	1.02875	-0.0355833	-0.00316667
25	1.03	1.0225	1.04417	-0.0216667	0.0075
26	1.02	1.04142	1.05833	-0.0169167	-0.0214167
27	1.07	1.07842	1.07208	0.00633333	-0.00841667
28	1.13	1.10442	1.0875	0.0169167	0.0255833
29	1.15	1.10358	1.10292	0.000666667	0.0464167
30	1.16	1.11417	1.11958	-0.00541667	0.0458333
31	1.14	1.1665	1.13875	0.02775	-0.0265
32	1.15	1.18008	1.15958	0.0205	-0.0300833
33	1.15	1.20092	1.18292	0.018	-0.0509167
34	1.16	1.20608	1.20542	0.000666667	-0.0460833
35	1.17	1.21375	1.225	-0.01125	-0.04375
36	1.22	1.20733	1.24292	-0.0355833	0.0126667
37	1.26	1.23958	1.26125	-0.0216667	0.0204167
38	1.29	1.26267	1.27958	-0.0169167	0.0273333
39	1.36	1.30425	1.29792	0.00633333	0.05575
40	1.38	1.33442	1.3175	0.0169167	0.0455833
41	1.37	1.33942	1.33875	0.000666667	0.0305833
42	1.37	1.35292	1.35833	-0.00541667	0.0170833
43	1.37	1.40233	1.37458	0.02775	-0.0323333
44	1.36	1.40967	1.38917	0.0205	-0.0496667
45	1.38	1.41925	1.40125	0.018	-0.03925
46	1.4	1.4115	1.41083	0.000666667	-0.0115
47	1.44	1.40667	1.41792	-0.01125	0.0333333
48	1.42	1.38608	1.42167	-0.0355833	0.0339167
49	1.45	1.4025	1.42417	-0.0216667	0.0475
50	1.45	1.41392	1.43083	-0.0169167	0.0360833
51	1.49	1.44758	1.44125	0.00633333	0.0424167
52	1.48	1.46733	1.45042	0.0169167	0.0126667
53	1.44	1.45567	1.455	0.000666667	-0.0156667
54	1.39	1.45083	1.45625	-0.00541667	-0.0608333
55	1.41	1.48317	1.45542	0.02775	-0.0731667
56	1.48	1.47383	1.45333	0.0205	0.00616667
57	1.51	1.46758	1.44958	0.018	0.0424167
58	1.49	1.44358	1.44292	0.000666667	0.0464167
59	1.46	1.42458	1.43583	-0.01125	0.0354167
60	1.43	1.39567	1.43125	-0.0355833	0.0343333
61	1.42	1.4075	1.42917	-0.0216667	0.0125
62	1.43	1.40767	1.42458	-0.0169167	0.0223333
63	1.42	1.42383	1.4175	0.00633333	-0.00383333
64	1.39	1.4265	1.40958	0.0169167	-0.0365
65	1.36	1.4015	1.40083	0.000666667	-0.0415
66	1.36	1.38917	1.39458	-0.00541667	-0.0291667
67	1.39	NA	NA	0.02775	NA
68	1.39	NA	NA	0.0205	NA
69	1.43	NA	NA	0.018	NA
70	1.38	NA	NA	0.000666667	NA
71	1.36	NA	NA	-0.01125	NA
72	1.38	NA	NA	-0.0355833	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.11 & NA & NA & -0.0216667 & NA \tabularnewline
2 & 1.11 & NA & NA & -0.0169167 & NA \tabularnewline
3 & 1.2 & NA & NA & 0.00633333 & NA \tabularnewline
4 & 1.21 & NA & NA & 0.0169167 & NA \tabularnewline
5 & 1.31 & NA & NA & 0.000666667 & NA \tabularnewline
6 & 1.37 & NA & NA & -0.00541667 & NA \tabularnewline
7 & 1.37 & 1.21567 & 1.18792 & 0.02775 & 0.154333 \tabularnewline
8 & 1.26 & 1.19258 & 1.17208 & 0.0205 & 0.0674167 \tabularnewline
9 & 1.23 & 1.16967 & 1.15167 & 0.018 & 0.0603333 \tabularnewline
10 & 1.17 & 1.12817 & 1.1275 & 0.000666667 & 0.0418333 \tabularnewline
11 & 1.06 & 1.08875 & 1.1 & -0.01125 & -0.02875 \tabularnewline
12 & 0.95 & 1.03192 & 1.0675 & -0.0355833 & -0.0819167 \tabularnewline
13 & 0.92 & 1.01208 & 1.03375 & -0.0216667 & -0.0920833 \tabularnewline
14 & 0.92 & 0.9885 & 1.00542 & -0.0169167 & -0.0685 \tabularnewline
15 & 0.9 & 0.990083 & 0.98375 & 0.00633333 & -0.0900833 \tabularnewline
16 & 0.93 & 0.9815 & 0.964583 & 0.0169167 & -0.0515 \tabularnewline
17 & 0.93 & 0.954 & 0.953333 & 0.000666667 & -0.024 \tabularnewline
18 & 0.97 & 0.947083 & 0.9525 & -0.00541667 & 0.0229167 \tabularnewline
19 & 0.96 & 0.9865 & 0.95875 & 0.02775 & -0.0265 \tabularnewline
20 & 0.99 & 0.988 & 0.9675 & 0.0205 & 0.002 \tabularnewline
21 & 0.98 & 0.99675 & 0.97875 & 0.018 & -0.01675 \tabularnewline
22 & 0.96 & 0.994833 & 0.994167 & 0.000666667 & -0.0348333 \tabularnewline
23 & 1 & 1.00042 & 1.01167 & -0.01125 & -0.000416667 \tabularnewline
24 & 0.99 & 0.993167 & 1.02875 & -0.0355833 & -0.00316667 \tabularnewline
25 & 1.03 & 1.0225 & 1.04417 & -0.0216667 & 0.0075 \tabularnewline
26 & 1.02 & 1.04142 & 1.05833 & -0.0169167 & -0.0214167 \tabularnewline
27 & 1.07 & 1.07842 & 1.07208 & 0.00633333 & -0.00841667 \tabularnewline
28 & 1.13 & 1.10442 & 1.0875 & 0.0169167 & 0.0255833 \tabularnewline
29 & 1.15 & 1.10358 & 1.10292 & 0.000666667 & 0.0464167 \tabularnewline
30 & 1.16 & 1.11417 & 1.11958 & -0.00541667 & 0.0458333 \tabularnewline
31 & 1.14 & 1.1665 & 1.13875 & 0.02775 & -0.0265 \tabularnewline
32 & 1.15 & 1.18008 & 1.15958 & 0.0205 & -0.0300833 \tabularnewline
33 & 1.15 & 1.20092 & 1.18292 & 0.018 & -0.0509167 \tabularnewline
34 & 1.16 & 1.20608 & 1.20542 & 0.000666667 & -0.0460833 \tabularnewline
35 & 1.17 & 1.21375 & 1.225 & -0.01125 & -0.04375 \tabularnewline
36 & 1.22 & 1.20733 & 1.24292 & -0.0355833 & 0.0126667 \tabularnewline
37 & 1.26 & 1.23958 & 1.26125 & -0.0216667 & 0.0204167 \tabularnewline
38 & 1.29 & 1.26267 & 1.27958 & -0.0169167 & 0.0273333 \tabularnewline
39 & 1.36 & 1.30425 & 1.29792 & 0.00633333 & 0.05575 \tabularnewline
40 & 1.38 & 1.33442 & 1.3175 & 0.0169167 & 0.0455833 \tabularnewline
41 & 1.37 & 1.33942 & 1.33875 & 0.000666667 & 0.0305833 \tabularnewline
42 & 1.37 & 1.35292 & 1.35833 & -0.00541667 & 0.0170833 \tabularnewline
43 & 1.37 & 1.40233 & 1.37458 & 0.02775 & -0.0323333 \tabularnewline
44 & 1.36 & 1.40967 & 1.38917 & 0.0205 & -0.0496667 \tabularnewline
45 & 1.38 & 1.41925 & 1.40125 & 0.018 & -0.03925 \tabularnewline
46 & 1.4 & 1.4115 & 1.41083 & 0.000666667 & -0.0115 \tabularnewline
47 & 1.44 & 1.40667 & 1.41792 & -0.01125 & 0.0333333 \tabularnewline
48 & 1.42 & 1.38608 & 1.42167 & -0.0355833 & 0.0339167 \tabularnewline
49 & 1.45 & 1.4025 & 1.42417 & -0.0216667 & 0.0475 \tabularnewline
50 & 1.45 & 1.41392 & 1.43083 & -0.0169167 & 0.0360833 \tabularnewline
51 & 1.49 & 1.44758 & 1.44125 & 0.00633333 & 0.0424167 \tabularnewline
52 & 1.48 & 1.46733 & 1.45042 & 0.0169167 & 0.0126667 \tabularnewline
53 & 1.44 & 1.45567 & 1.455 & 0.000666667 & -0.0156667 \tabularnewline
54 & 1.39 & 1.45083 & 1.45625 & -0.00541667 & -0.0608333 \tabularnewline
55 & 1.41 & 1.48317 & 1.45542 & 0.02775 & -0.0731667 \tabularnewline
56 & 1.48 & 1.47383 & 1.45333 & 0.0205 & 0.00616667 \tabularnewline
57 & 1.51 & 1.46758 & 1.44958 & 0.018 & 0.0424167 \tabularnewline
58 & 1.49 & 1.44358 & 1.44292 & 0.000666667 & 0.0464167 \tabularnewline
59 & 1.46 & 1.42458 & 1.43583 & -0.01125 & 0.0354167 \tabularnewline
60 & 1.43 & 1.39567 & 1.43125 & -0.0355833 & 0.0343333 \tabularnewline
61 & 1.42 & 1.4075 & 1.42917 & -0.0216667 & 0.0125 \tabularnewline
62 & 1.43 & 1.40767 & 1.42458 & -0.0169167 & 0.0223333 \tabularnewline
63 & 1.42 & 1.42383 & 1.4175 & 0.00633333 & -0.00383333 \tabularnewline
64 & 1.39 & 1.4265 & 1.40958 & 0.0169167 & -0.0365 \tabularnewline
65 & 1.36 & 1.4015 & 1.40083 & 0.000666667 & -0.0415 \tabularnewline
66 & 1.36 & 1.38917 & 1.39458 & -0.00541667 & -0.0291667 \tabularnewline
67 & 1.39 & NA & NA & 0.02775 & NA \tabularnewline
68 & 1.39 & NA & NA & 0.0205 & NA \tabularnewline
69 & 1.43 & NA & NA & 0.018 & NA \tabularnewline
70 & 1.38 & NA & NA & 0.000666667 & NA \tabularnewline
71 & 1.36 & NA & NA & -0.01125 & NA \tabularnewline
72 & 1.38 & NA & NA & -0.0355833 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261311&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]1.11[/C][C]NA[/C][C]NA[/C][C]-0.0216667[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.11[/C][C]NA[/C][C]NA[/C][C]-0.0169167[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.2[/C][C]NA[/C][C]NA[/C][C]0.00633333[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.21[/C][C]NA[/C][C]NA[/C][C]0.0169167[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.31[/C][C]NA[/C][C]NA[/C][C]0.000666667[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.37[/C][C]NA[/C][C]NA[/C][C]-0.00541667[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.37[/C][C]1.21567[/C][C]1.18792[/C][C]0.02775[/C][C]0.154333[/C][/ROW]
[ROW][C]8[/C][C]1.26[/C][C]1.19258[/C][C]1.17208[/C][C]0.0205[/C][C]0.0674167[/C][/ROW]
[ROW][C]9[/C][C]1.23[/C][C]1.16967[/C][C]1.15167[/C][C]0.018[/C][C]0.0603333[/C][/ROW]
[ROW][C]10[/C][C]1.17[/C][C]1.12817[/C][C]1.1275[/C][C]0.000666667[/C][C]0.0418333[/C][/ROW]
[ROW][C]11[/C][C]1.06[/C][C]1.08875[/C][C]1.1[/C][C]-0.01125[/C][C]-0.02875[/C][/ROW]
[ROW][C]12[/C][C]0.95[/C][C]1.03192[/C][C]1.0675[/C][C]-0.0355833[/C][C]-0.0819167[/C][/ROW]
[ROW][C]13[/C][C]0.92[/C][C]1.01208[/C][C]1.03375[/C][C]-0.0216667[/C][C]-0.0920833[/C][/ROW]
[ROW][C]14[/C][C]0.92[/C][C]0.9885[/C][C]1.00542[/C][C]-0.0169167[/C][C]-0.0685[/C][/ROW]
[ROW][C]15[/C][C]0.9[/C][C]0.990083[/C][C]0.98375[/C][C]0.00633333[/C][C]-0.0900833[/C][/ROW]
[ROW][C]16[/C][C]0.93[/C][C]0.9815[/C][C]0.964583[/C][C]0.0169167[/C][C]-0.0515[/C][/ROW]
[ROW][C]17[/C][C]0.93[/C][C]0.954[/C][C]0.953333[/C][C]0.000666667[/C][C]-0.024[/C][/ROW]
[ROW][C]18[/C][C]0.97[/C][C]0.947083[/C][C]0.9525[/C][C]-0.00541667[/C][C]0.0229167[/C][/ROW]
[ROW][C]19[/C][C]0.96[/C][C]0.9865[/C][C]0.95875[/C][C]0.02775[/C][C]-0.0265[/C][/ROW]
[ROW][C]20[/C][C]0.99[/C][C]0.988[/C][C]0.9675[/C][C]0.0205[/C][C]0.002[/C][/ROW]
[ROW][C]21[/C][C]0.98[/C][C]0.99675[/C][C]0.97875[/C][C]0.018[/C][C]-0.01675[/C][/ROW]
[ROW][C]22[/C][C]0.96[/C][C]0.994833[/C][C]0.994167[/C][C]0.000666667[/C][C]-0.0348333[/C][/ROW]
[ROW][C]23[/C][C]1[/C][C]1.00042[/C][C]1.01167[/C][C]-0.01125[/C][C]-0.000416667[/C][/ROW]
[ROW][C]24[/C][C]0.99[/C][C]0.993167[/C][C]1.02875[/C][C]-0.0355833[/C][C]-0.00316667[/C][/ROW]
[ROW][C]25[/C][C]1.03[/C][C]1.0225[/C][C]1.04417[/C][C]-0.0216667[/C][C]0.0075[/C][/ROW]
[ROW][C]26[/C][C]1.02[/C][C]1.04142[/C][C]1.05833[/C][C]-0.0169167[/C][C]-0.0214167[/C][/ROW]
[ROW][C]27[/C][C]1.07[/C][C]1.07842[/C][C]1.07208[/C][C]0.00633333[/C][C]-0.00841667[/C][/ROW]
[ROW][C]28[/C][C]1.13[/C][C]1.10442[/C][C]1.0875[/C][C]0.0169167[/C][C]0.0255833[/C][/ROW]
[ROW][C]29[/C][C]1.15[/C][C]1.10358[/C][C]1.10292[/C][C]0.000666667[/C][C]0.0464167[/C][/ROW]
[ROW][C]30[/C][C]1.16[/C][C]1.11417[/C][C]1.11958[/C][C]-0.00541667[/C][C]0.0458333[/C][/ROW]
[ROW][C]31[/C][C]1.14[/C][C]1.1665[/C][C]1.13875[/C][C]0.02775[/C][C]-0.0265[/C][/ROW]
[ROW][C]32[/C][C]1.15[/C][C]1.18008[/C][C]1.15958[/C][C]0.0205[/C][C]-0.0300833[/C][/ROW]
[ROW][C]33[/C][C]1.15[/C][C]1.20092[/C][C]1.18292[/C][C]0.018[/C][C]-0.0509167[/C][/ROW]
[ROW][C]34[/C][C]1.16[/C][C]1.20608[/C][C]1.20542[/C][C]0.000666667[/C][C]-0.0460833[/C][/ROW]
[ROW][C]35[/C][C]1.17[/C][C]1.21375[/C][C]1.225[/C][C]-0.01125[/C][C]-0.04375[/C][/ROW]
[ROW][C]36[/C][C]1.22[/C][C]1.20733[/C][C]1.24292[/C][C]-0.0355833[/C][C]0.0126667[/C][/ROW]
[ROW][C]37[/C][C]1.26[/C][C]1.23958[/C][C]1.26125[/C][C]-0.0216667[/C][C]0.0204167[/C][/ROW]
[ROW][C]38[/C][C]1.29[/C][C]1.26267[/C][C]1.27958[/C][C]-0.0169167[/C][C]0.0273333[/C][/ROW]
[ROW][C]39[/C][C]1.36[/C][C]1.30425[/C][C]1.29792[/C][C]0.00633333[/C][C]0.05575[/C][/ROW]
[ROW][C]40[/C][C]1.38[/C][C]1.33442[/C][C]1.3175[/C][C]0.0169167[/C][C]0.0455833[/C][/ROW]
[ROW][C]41[/C][C]1.37[/C][C]1.33942[/C][C]1.33875[/C][C]0.000666667[/C][C]0.0305833[/C][/ROW]
[ROW][C]42[/C][C]1.37[/C][C]1.35292[/C][C]1.35833[/C][C]-0.00541667[/C][C]0.0170833[/C][/ROW]
[ROW][C]43[/C][C]1.37[/C][C]1.40233[/C][C]1.37458[/C][C]0.02775[/C][C]-0.0323333[/C][/ROW]
[ROW][C]44[/C][C]1.36[/C][C]1.40967[/C][C]1.38917[/C][C]0.0205[/C][C]-0.0496667[/C][/ROW]
[ROW][C]45[/C][C]1.38[/C][C]1.41925[/C][C]1.40125[/C][C]0.018[/C][C]-0.03925[/C][/ROW]
[ROW][C]46[/C][C]1.4[/C][C]1.4115[/C][C]1.41083[/C][C]0.000666667[/C][C]-0.0115[/C][/ROW]
[ROW][C]47[/C][C]1.44[/C][C]1.40667[/C][C]1.41792[/C][C]-0.01125[/C][C]0.0333333[/C][/ROW]
[ROW][C]48[/C][C]1.42[/C][C]1.38608[/C][C]1.42167[/C][C]-0.0355833[/C][C]0.0339167[/C][/ROW]
[ROW][C]49[/C][C]1.45[/C][C]1.4025[/C][C]1.42417[/C][C]-0.0216667[/C][C]0.0475[/C][/ROW]
[ROW][C]50[/C][C]1.45[/C][C]1.41392[/C][C]1.43083[/C][C]-0.0169167[/C][C]0.0360833[/C][/ROW]
[ROW][C]51[/C][C]1.49[/C][C]1.44758[/C][C]1.44125[/C][C]0.00633333[/C][C]0.0424167[/C][/ROW]
[ROW][C]52[/C][C]1.48[/C][C]1.46733[/C][C]1.45042[/C][C]0.0169167[/C][C]0.0126667[/C][/ROW]
[ROW][C]53[/C][C]1.44[/C][C]1.45567[/C][C]1.455[/C][C]0.000666667[/C][C]-0.0156667[/C][/ROW]
[ROW][C]54[/C][C]1.39[/C][C]1.45083[/C][C]1.45625[/C][C]-0.00541667[/C][C]-0.0608333[/C][/ROW]
[ROW][C]55[/C][C]1.41[/C][C]1.48317[/C][C]1.45542[/C][C]0.02775[/C][C]-0.0731667[/C][/ROW]
[ROW][C]56[/C][C]1.48[/C][C]1.47383[/C][C]1.45333[/C][C]0.0205[/C][C]0.00616667[/C][/ROW]
[ROW][C]57[/C][C]1.51[/C][C]1.46758[/C][C]1.44958[/C][C]0.018[/C][C]0.0424167[/C][/ROW]
[ROW][C]58[/C][C]1.49[/C][C]1.44358[/C][C]1.44292[/C][C]0.000666667[/C][C]0.0464167[/C][/ROW]
[ROW][C]59[/C][C]1.46[/C][C]1.42458[/C][C]1.43583[/C][C]-0.01125[/C][C]0.0354167[/C][/ROW]
[ROW][C]60[/C][C]1.43[/C][C]1.39567[/C][C]1.43125[/C][C]-0.0355833[/C][C]0.0343333[/C][/ROW]
[ROW][C]61[/C][C]1.42[/C][C]1.4075[/C][C]1.42917[/C][C]-0.0216667[/C][C]0.0125[/C][/ROW]
[ROW][C]62[/C][C]1.43[/C][C]1.40767[/C][C]1.42458[/C][C]-0.0169167[/C][C]0.0223333[/C][/ROW]
[ROW][C]63[/C][C]1.42[/C][C]1.42383[/C][C]1.4175[/C][C]0.00633333[/C][C]-0.00383333[/C][/ROW]
[ROW][C]64[/C][C]1.39[/C][C]1.4265[/C][C]1.40958[/C][C]0.0169167[/C][C]-0.0365[/C][/ROW]
[ROW][C]65[/C][C]1.36[/C][C]1.4015[/C][C]1.40083[/C][C]0.000666667[/C][C]-0.0415[/C][/ROW]
[ROW][C]66[/C][C]1.36[/C][C]1.38917[/C][C]1.39458[/C][C]-0.00541667[/C][C]-0.0291667[/C][/ROW]
[ROW][C]67[/C][C]1.39[/C][C]NA[/C][C]NA[/C][C]0.02775[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]1.39[/C][C]NA[/C][C]NA[/C][C]0.0205[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1.43[/C][C]NA[/C][C]NA[/C][C]0.018[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1.38[/C][C]NA[/C][C]NA[/C][C]0.000666667[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]1.36[/C][C]NA[/C][C]NA[/C][C]-0.01125[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]1.38[/C][C]NA[/C][C]NA[/C][C]-0.0355833[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261311&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261311&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	1.11	NA	NA	-0.0216667	NA
2	1.11	NA	NA	-0.0169167	NA
3	1.2	NA	NA	0.00633333	NA
4	1.21	NA	NA	0.0169167	NA
5	1.31	NA	NA	0.000666667	NA
6	1.37	NA	NA	-0.00541667	NA
7	1.37	1.21567	1.18792	0.02775	0.154333
8	1.26	1.19258	1.17208	0.0205	0.0674167
9	1.23	1.16967	1.15167	0.018	0.0603333
10	1.17	1.12817	1.1275	0.000666667	0.0418333
11	1.06	1.08875	1.1	-0.01125	-0.02875
12	0.95	1.03192	1.0675	-0.0355833	-0.0819167
13	0.92	1.01208	1.03375	-0.0216667	-0.0920833
14	0.92	0.9885	1.00542	-0.0169167	-0.0685
15	0.9	0.990083	0.98375	0.00633333	-0.0900833
16	0.93	0.9815	0.964583	0.0169167	-0.0515
17	0.93	0.954	0.953333	0.000666667	-0.024
18	0.97	0.947083	0.9525	-0.00541667	0.0229167
19	0.96	0.9865	0.95875	0.02775	-0.0265
20	0.99	0.988	0.9675	0.0205	0.002
21	0.98	0.99675	0.97875	0.018	-0.01675
22	0.96	0.994833	0.994167	0.000666667	-0.0348333
23	1	1.00042	1.01167	-0.01125	-0.000416667
24	0.99	0.993167	1.02875	-0.0355833	-0.00316667
25	1.03	1.0225	1.04417	-0.0216667	0.0075
26	1.02	1.04142	1.05833	-0.0169167	-0.0214167
27	1.07	1.07842	1.07208	0.00633333	-0.00841667
28	1.13	1.10442	1.0875	0.0169167	0.0255833
29	1.15	1.10358	1.10292	0.000666667	0.0464167
30	1.16	1.11417	1.11958	-0.00541667	0.0458333
31	1.14	1.1665	1.13875	0.02775	-0.0265
32	1.15	1.18008	1.15958	0.0205	-0.0300833
33	1.15	1.20092	1.18292	0.018	-0.0509167
34	1.16	1.20608	1.20542	0.000666667	-0.0460833
35	1.17	1.21375	1.225	-0.01125	-0.04375
36	1.22	1.20733	1.24292	-0.0355833	0.0126667
37	1.26	1.23958	1.26125	-0.0216667	0.0204167
38	1.29	1.26267	1.27958	-0.0169167	0.0273333
39	1.36	1.30425	1.29792	0.00633333	0.05575
40	1.38	1.33442	1.3175	0.0169167	0.0455833
41	1.37	1.33942	1.33875	0.000666667	0.0305833
42	1.37	1.35292	1.35833	-0.00541667	0.0170833
43	1.37	1.40233	1.37458	0.02775	-0.0323333
44	1.36	1.40967	1.38917	0.0205	-0.0496667
45	1.38	1.41925	1.40125	0.018	-0.03925
46	1.4	1.4115	1.41083	0.000666667	-0.0115
47	1.44	1.40667	1.41792	-0.01125	0.0333333
48	1.42	1.38608	1.42167	-0.0355833	0.0339167
49	1.45	1.4025	1.42417	-0.0216667	0.0475
50	1.45	1.41392	1.43083	-0.0169167	0.0360833
51	1.49	1.44758	1.44125	0.00633333	0.0424167
52	1.48	1.46733	1.45042	0.0169167	0.0126667
53	1.44	1.45567	1.455	0.000666667	-0.0156667
54	1.39	1.45083	1.45625	-0.00541667	-0.0608333
55	1.41	1.48317	1.45542	0.02775	-0.0731667
56	1.48	1.47383	1.45333	0.0205	0.00616667
57	1.51	1.46758	1.44958	0.018	0.0424167
58	1.49	1.44358	1.44292	0.000666667	0.0464167
59	1.46	1.42458	1.43583	-0.01125	0.0354167
60	1.43	1.39567	1.43125	-0.0355833	0.0343333
61	1.42	1.4075	1.42917	-0.0216667	0.0125
62	1.43	1.40767	1.42458	-0.0169167	0.0223333
63	1.42	1.42383	1.4175	0.00633333	-0.00383333
64	1.39	1.4265	1.40958	0.0169167	-0.0365
65	1.36	1.4015	1.40083	0.000666667	-0.0415
66	1.36	1.38917	1.39458	-0.00541667	-0.0291667
67	1.39	NA	NA	0.02775	NA
68	1.39	NA	NA	0.0205	NA
69	1.43	NA	NA	0.018	NA
70	1.38	NA	NA	0.000666667	NA
71	1.36	NA	NA	-0.01125	NA
72	1.38	NA	NA	-0.0355833	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