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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 14:14:25 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/12/t13868757521yrqmye2gwoakh0.htm/, Retrieved Sun, 05 Dec 2021 17:48:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232271, Retrieved Sun, 05 Dec 2021 17:48:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 19:14:25] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
20.1
20.1
20.1
20.3
20.7
20.6
20.3
19.9
19.7
19.4
19.1
18.8
18.9
18.7
18.8
19.5
19.3
19.1
19.1
19
18.8
19.2
18.9
18.7
18.5
18.4
18.3
18.3
18.3
18.5
19.2
19.4
19.1
19.5
18.8
19.3
20.4
20.9
21.1
20.6
20.4
20.8
21.1
21.6
22
22.2
22.4
22.8
22.7
22.8
22.9
22.9
22.6
21.9
20.8
20.3
20.4
21.2
21.4
20.9
20
19.5
19.2
19.3
19.4
19.5
20
20.1
19.5
18.6
18.4
18.4
19.3
19.8
19.8
19.8
20.1
20.3
19.7
20.2
20.6
21
21.4
21.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 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 & 6 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232271&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]6 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=232271&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232271&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
120.1NANA0.0068287NA
220.1NANA0.058912NA
320.1NANA0.0505787NA
420.3NANA0.0832176NA
520.7NANA0.00613426NA
620.6NANA-0.0313657NA
720.319.96119.8750.08599540.339005
819.919.82719.76670.06030090.0730324
919.719.585319.6542-0.06886570.114699
1019.419.603419.56670.0366898-0.203356
1119.119.33619.475-0.139005-0.235995
1218.819.204719.3542-0.149421-0.404745
1318.919.248519.24170.0068287-0.348495
1418.719.213119.15420.058912-0.513079
1518.819.129719.07920.0505787-0.329745
1619.519.116619.03330.08321760.383449
1719.319.022819.01670.006134260.277199
1819.118.972819.0042-0.03136570.127199
1919.119.069318.98330.08599540.0306713
201919.014518.95420.0603009-0.0144676
2118.818.85218.9208-0.0688657-0.0519676
2219.218.886718.850.03668980.31331
2318.918.619318.7583-0.1390050.280671
2418.718.542218.6917-0.1494210.157755
2518.518.677718.67080.0068287-0.177662
2618.418.750618.69170.058912-0.350579
2718.318.771418.72080.0505787-0.471412
2818.318.829118.74580.0832176-0.529051
2918.318.760318.75420.00613426-0.460301
3018.518.743618.775-0.0313657-0.243634
3119.218.965218.87920.08599540.234838
3219.419.122819.06250.06030090.277199
3319.119.214519.2833-0.0688657-0.114468
3419.519.532519.49580.0366898-0.0325231
3518.819.540219.6792-0.139005-0.740162
3619.319.713119.8625-0.149421-0.413079
3720.420.044320.03750.00682870.355671
3820.920.267220.20830.0589120.632755
3921.120.471420.42080.05057870.628588
4020.620.737420.65420.0832176-0.137384
4120.420.922820.91670.00613426-0.522801
4220.821.181121.2125-0.0313657-0.381134
4321.121.540221.45420.0859954-0.440162
4421.621.689521.62920.0603009-0.0894676
452221.714521.7833-0.06886570.285532
4622.221.990921.95420.03668980.209144
4722.422.002722.1417-0.1390050.397338
4822.822.129722.2792-0.1494210.670255
4922.722.319322.31250.00682870.380671
5022.822.304722.24580.0589120.495255
5122.922.175622.1250.05057870.724421
5222.922.099922.01670.08321760.800116
5322.621.939521.93330.006134260.660532
5421.921.781121.8125-0.03136570.118866
5520.821.706821.62080.0859954-0.906829
5620.321.431121.37080.0603009-1.13113
5720.421.010321.0792-0.0688657-0.610301
5821.220.811720.7750.03668980.38831
5921.420.352720.4917-0.1390051.04734
6020.920.108920.2583-0.1494210.791088
612020.131820.1250.0068287-0.131829
6219.520.142220.08330.058912-0.642245
6319.220.088120.03750.0505787-0.888079
6419.319.974919.89170.0832176-0.674884
6519.419.664519.65830.00613426-0.264468
6619.519.397819.4292-0.03136570.102199
672019.381819.29580.08599540.618171
6820.119.339519.27920.06030090.760532
6919.519.247819.3167-0.06886570.252199
7018.619.399219.36250.0366898-0.79919
7118.419.273519.4125-0.139005-0.873495
7218.419.325619.475-0.149421-0.925579
7319.319.502719.49580.0068287-0.202662
7419.819.546419.48750.0589120.253588
7519.819.588119.53750.05057870.211921
7619.819.766619.68330.08321760.0334491
7720.119.914519.90830.006134260.185532
7820.320.147820.1792-0.03136570.152199
7919.7NANA0.0859954NA
8020.2NANA0.0603009NA
8120.6NANA-0.0688657NA
8221NANA0.0366898NA
8321.4NANA-0.139005NA
8421.9NANA-0.149421NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 20.1 & NA & NA & 0.0068287 & NA \tabularnewline
2 & 20.1 & NA & NA & 0.058912 & NA \tabularnewline
3 & 20.1 & NA & NA & 0.0505787 & NA \tabularnewline
4 & 20.3 & NA & NA & 0.0832176 & NA \tabularnewline
5 & 20.7 & NA & NA & 0.00613426 & NA \tabularnewline
6 & 20.6 & NA & NA & -0.0313657 & NA \tabularnewline
7 & 20.3 & 19.961 & 19.875 & 0.0859954 & 0.339005 \tabularnewline
8 & 19.9 & 19.827 & 19.7667 & 0.0603009 & 0.0730324 \tabularnewline
9 & 19.7 & 19.5853 & 19.6542 & -0.0688657 & 0.114699 \tabularnewline
10 & 19.4 & 19.6034 & 19.5667 & 0.0366898 & -0.203356 \tabularnewline
11 & 19.1 & 19.336 & 19.475 & -0.139005 & -0.235995 \tabularnewline
12 & 18.8 & 19.2047 & 19.3542 & -0.149421 & -0.404745 \tabularnewline
13 & 18.9 & 19.2485 & 19.2417 & 0.0068287 & -0.348495 \tabularnewline
14 & 18.7 & 19.2131 & 19.1542 & 0.058912 & -0.513079 \tabularnewline
15 & 18.8 & 19.1297 & 19.0792 & 0.0505787 & -0.329745 \tabularnewline
16 & 19.5 & 19.1166 & 19.0333 & 0.0832176 & 0.383449 \tabularnewline
17 & 19.3 & 19.0228 & 19.0167 & 0.00613426 & 0.277199 \tabularnewline
18 & 19.1 & 18.9728 & 19.0042 & -0.0313657 & 0.127199 \tabularnewline
19 & 19.1 & 19.0693 & 18.9833 & 0.0859954 & 0.0306713 \tabularnewline
20 & 19 & 19.0145 & 18.9542 & 0.0603009 & -0.0144676 \tabularnewline
21 & 18.8 & 18.852 & 18.9208 & -0.0688657 & -0.0519676 \tabularnewline
22 & 19.2 & 18.8867 & 18.85 & 0.0366898 & 0.31331 \tabularnewline
23 & 18.9 & 18.6193 & 18.7583 & -0.139005 & 0.280671 \tabularnewline
24 & 18.7 & 18.5422 & 18.6917 & -0.149421 & 0.157755 \tabularnewline
25 & 18.5 & 18.6777 & 18.6708 & 0.0068287 & -0.177662 \tabularnewline
26 & 18.4 & 18.7506 & 18.6917 & 0.058912 & -0.350579 \tabularnewline
27 & 18.3 & 18.7714 & 18.7208 & 0.0505787 & -0.471412 \tabularnewline
28 & 18.3 & 18.8291 & 18.7458 & 0.0832176 & -0.529051 \tabularnewline
29 & 18.3 & 18.7603 & 18.7542 & 0.00613426 & -0.460301 \tabularnewline
30 & 18.5 & 18.7436 & 18.775 & -0.0313657 & -0.243634 \tabularnewline
31 & 19.2 & 18.9652 & 18.8792 & 0.0859954 & 0.234838 \tabularnewline
32 & 19.4 & 19.1228 & 19.0625 & 0.0603009 & 0.277199 \tabularnewline
33 & 19.1 & 19.2145 & 19.2833 & -0.0688657 & -0.114468 \tabularnewline
34 & 19.5 & 19.5325 & 19.4958 & 0.0366898 & -0.0325231 \tabularnewline
35 & 18.8 & 19.5402 & 19.6792 & -0.139005 & -0.740162 \tabularnewline
36 & 19.3 & 19.7131 & 19.8625 & -0.149421 & -0.413079 \tabularnewline
37 & 20.4 & 20.0443 & 20.0375 & 0.0068287 & 0.355671 \tabularnewline
38 & 20.9 & 20.2672 & 20.2083 & 0.058912 & 0.632755 \tabularnewline
39 & 21.1 & 20.4714 & 20.4208 & 0.0505787 & 0.628588 \tabularnewline
40 & 20.6 & 20.7374 & 20.6542 & 0.0832176 & -0.137384 \tabularnewline
41 & 20.4 & 20.9228 & 20.9167 & 0.00613426 & -0.522801 \tabularnewline
42 & 20.8 & 21.1811 & 21.2125 & -0.0313657 & -0.381134 \tabularnewline
43 & 21.1 & 21.5402 & 21.4542 & 0.0859954 & -0.440162 \tabularnewline
44 & 21.6 & 21.6895 & 21.6292 & 0.0603009 & -0.0894676 \tabularnewline
45 & 22 & 21.7145 & 21.7833 & -0.0688657 & 0.285532 \tabularnewline
46 & 22.2 & 21.9909 & 21.9542 & 0.0366898 & 0.209144 \tabularnewline
47 & 22.4 & 22.0027 & 22.1417 & -0.139005 & 0.397338 \tabularnewline
48 & 22.8 & 22.1297 & 22.2792 & -0.149421 & 0.670255 \tabularnewline
49 & 22.7 & 22.3193 & 22.3125 & 0.0068287 & 0.380671 \tabularnewline
50 & 22.8 & 22.3047 & 22.2458 & 0.058912 & 0.495255 \tabularnewline
51 & 22.9 & 22.1756 & 22.125 & 0.0505787 & 0.724421 \tabularnewline
52 & 22.9 & 22.0999 & 22.0167 & 0.0832176 & 0.800116 \tabularnewline
53 & 22.6 & 21.9395 & 21.9333 & 0.00613426 & 0.660532 \tabularnewline
54 & 21.9 & 21.7811 & 21.8125 & -0.0313657 & 0.118866 \tabularnewline
55 & 20.8 & 21.7068 & 21.6208 & 0.0859954 & -0.906829 \tabularnewline
56 & 20.3 & 21.4311 & 21.3708 & 0.0603009 & -1.13113 \tabularnewline
57 & 20.4 & 21.0103 & 21.0792 & -0.0688657 & -0.610301 \tabularnewline
58 & 21.2 & 20.8117 & 20.775 & 0.0366898 & 0.38831 \tabularnewline
59 & 21.4 & 20.3527 & 20.4917 & -0.139005 & 1.04734 \tabularnewline
60 & 20.9 & 20.1089 & 20.2583 & -0.149421 & 0.791088 \tabularnewline
61 & 20 & 20.1318 & 20.125 & 0.0068287 & -0.131829 \tabularnewline
62 & 19.5 & 20.1422 & 20.0833 & 0.058912 & -0.642245 \tabularnewline
63 & 19.2 & 20.0881 & 20.0375 & 0.0505787 & -0.888079 \tabularnewline
64 & 19.3 & 19.9749 & 19.8917 & 0.0832176 & -0.674884 \tabularnewline
65 & 19.4 & 19.6645 & 19.6583 & 0.00613426 & -0.264468 \tabularnewline
66 & 19.5 & 19.3978 & 19.4292 & -0.0313657 & 0.102199 \tabularnewline
67 & 20 & 19.3818 & 19.2958 & 0.0859954 & 0.618171 \tabularnewline
68 & 20.1 & 19.3395 & 19.2792 & 0.0603009 & 0.760532 \tabularnewline
69 & 19.5 & 19.2478 & 19.3167 & -0.0688657 & 0.252199 \tabularnewline
70 & 18.6 & 19.3992 & 19.3625 & 0.0366898 & -0.79919 \tabularnewline
71 & 18.4 & 19.2735 & 19.4125 & -0.139005 & -0.873495 \tabularnewline
72 & 18.4 & 19.3256 & 19.475 & -0.149421 & -0.925579 \tabularnewline
73 & 19.3 & 19.5027 & 19.4958 & 0.0068287 & -0.202662 \tabularnewline
74 & 19.8 & 19.5464 & 19.4875 & 0.058912 & 0.253588 \tabularnewline
75 & 19.8 & 19.5881 & 19.5375 & 0.0505787 & 0.211921 \tabularnewline
76 & 19.8 & 19.7666 & 19.6833 & 0.0832176 & 0.0334491 \tabularnewline
77 & 20.1 & 19.9145 & 19.9083 & 0.00613426 & 0.185532 \tabularnewline
78 & 20.3 & 20.1478 & 20.1792 & -0.0313657 & 0.152199 \tabularnewline
79 & 19.7 & NA & NA & 0.0859954 & NA \tabularnewline
80 & 20.2 & NA & NA & 0.0603009 & NA \tabularnewline
81 & 20.6 & NA & NA & -0.0688657 & NA \tabularnewline
82 & 21 & NA & NA & 0.0366898 & NA \tabularnewline
83 & 21.4 & NA & NA & -0.139005 & NA \tabularnewline
84 & 21.9 & NA & NA & -0.149421 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232271&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]20.1[/C][C]NA[/C][C]NA[/C][C]0.0068287[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]20.1[/C][C]NA[/C][C]NA[/C][C]0.058912[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]20.1[/C][C]NA[/C][C]NA[/C][C]0.0505787[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]20.3[/C][C]NA[/C][C]NA[/C][C]0.0832176[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]20.7[/C][C]NA[/C][C]NA[/C][C]0.00613426[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]20.6[/C][C]NA[/C][C]NA[/C][C]-0.0313657[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]20.3[/C][C]19.961[/C][C]19.875[/C][C]0.0859954[/C][C]0.339005[/C][/ROW]
[ROW][C]8[/C][C]19.9[/C][C]19.827[/C][C]19.7667[/C][C]0.0603009[/C][C]0.0730324[/C][/ROW]
[ROW][C]9[/C][C]19.7[/C][C]19.5853[/C][C]19.6542[/C][C]-0.0688657[/C][C]0.114699[/C][/ROW]
[ROW][C]10[/C][C]19.4[/C][C]19.6034[/C][C]19.5667[/C][C]0.0366898[/C][C]-0.203356[/C][/ROW]
[ROW][C]11[/C][C]19.1[/C][C]19.336[/C][C]19.475[/C][C]-0.139005[/C][C]-0.235995[/C][/ROW]
[ROW][C]12[/C][C]18.8[/C][C]19.2047[/C][C]19.3542[/C][C]-0.149421[/C][C]-0.404745[/C][/ROW]
[ROW][C]13[/C][C]18.9[/C][C]19.2485[/C][C]19.2417[/C][C]0.0068287[/C][C]-0.348495[/C][/ROW]
[ROW][C]14[/C][C]18.7[/C][C]19.2131[/C][C]19.1542[/C][C]0.058912[/C][C]-0.513079[/C][/ROW]
[ROW][C]15[/C][C]18.8[/C][C]19.1297[/C][C]19.0792[/C][C]0.0505787[/C][C]-0.329745[/C][/ROW]
[ROW][C]16[/C][C]19.5[/C][C]19.1166[/C][C]19.0333[/C][C]0.0832176[/C][C]0.383449[/C][/ROW]
[ROW][C]17[/C][C]19.3[/C][C]19.0228[/C][C]19.0167[/C][C]0.00613426[/C][C]0.277199[/C][/ROW]
[ROW][C]18[/C][C]19.1[/C][C]18.9728[/C][C]19.0042[/C][C]-0.0313657[/C][C]0.127199[/C][/ROW]
[ROW][C]19[/C][C]19.1[/C][C]19.0693[/C][C]18.9833[/C][C]0.0859954[/C][C]0.0306713[/C][/ROW]
[ROW][C]20[/C][C]19[/C][C]19.0145[/C][C]18.9542[/C][C]0.0603009[/C][C]-0.0144676[/C][/ROW]
[ROW][C]21[/C][C]18.8[/C][C]18.852[/C][C]18.9208[/C][C]-0.0688657[/C][C]-0.0519676[/C][/ROW]
[ROW][C]22[/C][C]19.2[/C][C]18.8867[/C][C]18.85[/C][C]0.0366898[/C][C]0.31331[/C][/ROW]
[ROW][C]23[/C][C]18.9[/C][C]18.6193[/C][C]18.7583[/C][C]-0.139005[/C][C]0.280671[/C][/ROW]
[ROW][C]24[/C][C]18.7[/C][C]18.5422[/C][C]18.6917[/C][C]-0.149421[/C][C]0.157755[/C][/ROW]
[ROW][C]25[/C][C]18.5[/C][C]18.6777[/C][C]18.6708[/C][C]0.0068287[/C][C]-0.177662[/C][/ROW]
[ROW][C]26[/C][C]18.4[/C][C]18.7506[/C][C]18.6917[/C][C]0.058912[/C][C]-0.350579[/C][/ROW]
[ROW][C]27[/C][C]18.3[/C][C]18.7714[/C][C]18.7208[/C][C]0.0505787[/C][C]-0.471412[/C][/ROW]
[ROW][C]28[/C][C]18.3[/C][C]18.8291[/C][C]18.7458[/C][C]0.0832176[/C][C]-0.529051[/C][/ROW]
[ROW][C]29[/C][C]18.3[/C][C]18.7603[/C][C]18.7542[/C][C]0.00613426[/C][C]-0.460301[/C][/ROW]
[ROW][C]30[/C][C]18.5[/C][C]18.7436[/C][C]18.775[/C][C]-0.0313657[/C][C]-0.243634[/C][/ROW]
[ROW][C]31[/C][C]19.2[/C][C]18.9652[/C][C]18.8792[/C][C]0.0859954[/C][C]0.234838[/C][/ROW]
[ROW][C]32[/C][C]19.4[/C][C]19.1228[/C][C]19.0625[/C][C]0.0603009[/C][C]0.277199[/C][/ROW]
[ROW][C]33[/C][C]19.1[/C][C]19.2145[/C][C]19.2833[/C][C]-0.0688657[/C][C]-0.114468[/C][/ROW]
[ROW][C]34[/C][C]19.5[/C][C]19.5325[/C][C]19.4958[/C][C]0.0366898[/C][C]-0.0325231[/C][/ROW]
[ROW][C]35[/C][C]18.8[/C][C]19.5402[/C][C]19.6792[/C][C]-0.139005[/C][C]-0.740162[/C][/ROW]
[ROW][C]36[/C][C]19.3[/C][C]19.7131[/C][C]19.8625[/C][C]-0.149421[/C][C]-0.413079[/C][/ROW]
[ROW][C]37[/C][C]20.4[/C][C]20.0443[/C][C]20.0375[/C][C]0.0068287[/C][C]0.355671[/C][/ROW]
[ROW][C]38[/C][C]20.9[/C][C]20.2672[/C][C]20.2083[/C][C]0.058912[/C][C]0.632755[/C][/ROW]
[ROW][C]39[/C][C]21.1[/C][C]20.4714[/C][C]20.4208[/C][C]0.0505787[/C][C]0.628588[/C][/ROW]
[ROW][C]40[/C][C]20.6[/C][C]20.7374[/C][C]20.6542[/C][C]0.0832176[/C][C]-0.137384[/C][/ROW]
[ROW][C]41[/C][C]20.4[/C][C]20.9228[/C][C]20.9167[/C][C]0.00613426[/C][C]-0.522801[/C][/ROW]
[ROW][C]42[/C][C]20.8[/C][C]21.1811[/C][C]21.2125[/C][C]-0.0313657[/C][C]-0.381134[/C][/ROW]
[ROW][C]43[/C][C]21.1[/C][C]21.5402[/C][C]21.4542[/C][C]0.0859954[/C][C]-0.440162[/C][/ROW]
[ROW][C]44[/C][C]21.6[/C][C]21.6895[/C][C]21.6292[/C][C]0.0603009[/C][C]-0.0894676[/C][/ROW]
[ROW][C]45[/C][C]22[/C][C]21.7145[/C][C]21.7833[/C][C]-0.0688657[/C][C]0.285532[/C][/ROW]
[ROW][C]46[/C][C]22.2[/C][C]21.9909[/C][C]21.9542[/C][C]0.0366898[/C][C]0.209144[/C][/ROW]
[ROW][C]47[/C][C]22.4[/C][C]22.0027[/C][C]22.1417[/C][C]-0.139005[/C][C]0.397338[/C][/ROW]
[ROW][C]48[/C][C]22.8[/C][C]22.1297[/C][C]22.2792[/C][C]-0.149421[/C][C]0.670255[/C][/ROW]
[ROW][C]49[/C][C]22.7[/C][C]22.3193[/C][C]22.3125[/C][C]0.0068287[/C][C]0.380671[/C][/ROW]
[ROW][C]50[/C][C]22.8[/C][C]22.3047[/C][C]22.2458[/C][C]0.058912[/C][C]0.495255[/C][/ROW]
[ROW][C]51[/C][C]22.9[/C][C]22.1756[/C][C]22.125[/C][C]0.0505787[/C][C]0.724421[/C][/ROW]
[ROW][C]52[/C][C]22.9[/C][C]22.0999[/C][C]22.0167[/C][C]0.0832176[/C][C]0.800116[/C][/ROW]
[ROW][C]53[/C][C]22.6[/C][C]21.9395[/C][C]21.9333[/C][C]0.00613426[/C][C]0.660532[/C][/ROW]
[ROW][C]54[/C][C]21.9[/C][C]21.7811[/C][C]21.8125[/C][C]-0.0313657[/C][C]0.118866[/C][/ROW]
[ROW][C]55[/C][C]20.8[/C][C]21.7068[/C][C]21.6208[/C][C]0.0859954[/C][C]-0.906829[/C][/ROW]
[ROW][C]56[/C][C]20.3[/C][C]21.4311[/C][C]21.3708[/C][C]0.0603009[/C][C]-1.13113[/C][/ROW]
[ROW][C]57[/C][C]20.4[/C][C]21.0103[/C][C]21.0792[/C][C]-0.0688657[/C][C]-0.610301[/C][/ROW]
[ROW][C]58[/C][C]21.2[/C][C]20.8117[/C][C]20.775[/C][C]0.0366898[/C][C]0.38831[/C][/ROW]
[ROW][C]59[/C][C]21.4[/C][C]20.3527[/C][C]20.4917[/C][C]-0.139005[/C][C]1.04734[/C][/ROW]
[ROW][C]60[/C][C]20.9[/C][C]20.1089[/C][C]20.2583[/C][C]-0.149421[/C][C]0.791088[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]20.1318[/C][C]20.125[/C][C]0.0068287[/C][C]-0.131829[/C][/ROW]
[ROW][C]62[/C][C]19.5[/C][C]20.1422[/C][C]20.0833[/C][C]0.058912[/C][C]-0.642245[/C][/ROW]
[ROW][C]63[/C][C]19.2[/C][C]20.0881[/C][C]20.0375[/C][C]0.0505787[/C][C]-0.888079[/C][/ROW]
[ROW][C]64[/C][C]19.3[/C][C]19.9749[/C][C]19.8917[/C][C]0.0832176[/C][C]-0.674884[/C][/ROW]
[ROW][C]65[/C][C]19.4[/C][C]19.6645[/C][C]19.6583[/C][C]0.00613426[/C][C]-0.264468[/C][/ROW]
[ROW][C]66[/C][C]19.5[/C][C]19.3978[/C][C]19.4292[/C][C]-0.0313657[/C][C]0.102199[/C][/ROW]
[ROW][C]67[/C][C]20[/C][C]19.3818[/C][C]19.2958[/C][C]0.0859954[/C][C]0.618171[/C][/ROW]
[ROW][C]68[/C][C]20.1[/C][C]19.3395[/C][C]19.2792[/C][C]0.0603009[/C][C]0.760532[/C][/ROW]
[ROW][C]69[/C][C]19.5[/C][C]19.2478[/C][C]19.3167[/C][C]-0.0688657[/C][C]0.252199[/C][/ROW]
[ROW][C]70[/C][C]18.6[/C][C]19.3992[/C][C]19.3625[/C][C]0.0366898[/C][C]-0.79919[/C][/ROW]
[ROW][C]71[/C][C]18.4[/C][C]19.2735[/C][C]19.4125[/C][C]-0.139005[/C][C]-0.873495[/C][/ROW]
[ROW][C]72[/C][C]18.4[/C][C]19.3256[/C][C]19.475[/C][C]-0.149421[/C][C]-0.925579[/C][/ROW]
[ROW][C]73[/C][C]19.3[/C][C]19.5027[/C][C]19.4958[/C][C]0.0068287[/C][C]-0.202662[/C][/ROW]
[ROW][C]74[/C][C]19.8[/C][C]19.5464[/C][C]19.4875[/C][C]0.058912[/C][C]0.253588[/C][/ROW]
[ROW][C]75[/C][C]19.8[/C][C]19.5881[/C][C]19.5375[/C][C]0.0505787[/C][C]0.211921[/C][/ROW]
[ROW][C]76[/C][C]19.8[/C][C]19.7666[/C][C]19.6833[/C][C]0.0832176[/C][C]0.0334491[/C][/ROW]
[ROW][C]77[/C][C]20.1[/C][C]19.9145[/C][C]19.9083[/C][C]0.00613426[/C][C]0.185532[/C][/ROW]
[ROW][C]78[/C][C]20.3[/C][C]20.1478[/C][C]20.1792[/C][C]-0.0313657[/C][C]0.152199[/C][/ROW]
[ROW][C]79[/C][C]19.7[/C][C]NA[/C][C]NA[/C][C]0.0859954[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]20.2[/C][C]NA[/C][C]NA[/C][C]0.0603009[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]20.6[/C][C]NA[/C][C]NA[/C][C]-0.0688657[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]21[/C][C]NA[/C][C]NA[/C][C]0.0366898[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]21.4[/C][C]NA[/C][C]NA[/C][C]-0.139005[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]21.9[/C][C]NA[/C][C]NA[/C][C]-0.149421[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232271&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232271&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
tObservationsFitTrendSeasonalRandom
120.1NANA0.0068287NA
220.1NANA0.058912NA
320.1NANA0.0505787NA
420.3NANA0.0832176NA
520.7NANA0.00613426NA
620.6NANA-0.0313657NA
720.319.96119.8750.08599540.339005
819.919.82719.76670.06030090.0730324
919.719.585319.6542-0.06886570.114699
1019.419.603419.56670.0366898-0.203356
1119.119.33619.475-0.139005-0.235995
1218.819.204719.3542-0.149421-0.404745
1318.919.248519.24170.0068287-0.348495
1418.719.213119.15420.058912-0.513079
1518.819.129719.07920.0505787-0.329745
1619.519.116619.03330.08321760.383449
1719.319.022819.01670.006134260.277199
1819.118.972819.0042-0.03136570.127199
1919.119.069318.98330.08599540.0306713
201919.014518.95420.0603009-0.0144676
2118.818.85218.9208-0.0688657-0.0519676
2219.218.886718.850.03668980.31331
2318.918.619318.7583-0.1390050.280671
2418.718.542218.6917-0.1494210.157755
2518.518.677718.67080.0068287-0.177662
2618.418.750618.69170.058912-0.350579
2718.318.771418.72080.0505787-0.471412
2818.318.829118.74580.0832176-0.529051
2918.318.760318.75420.00613426-0.460301
3018.518.743618.775-0.0313657-0.243634
3119.218.965218.87920.08599540.234838
3219.419.122819.06250.06030090.277199
3319.119.214519.2833-0.0688657-0.114468
3419.519.532519.49580.0366898-0.0325231
3518.819.540219.6792-0.139005-0.740162
3619.319.713119.8625-0.149421-0.413079
3720.420.044320.03750.00682870.355671
3820.920.267220.20830.0589120.632755
3921.120.471420.42080.05057870.628588
4020.620.737420.65420.0832176-0.137384
4120.420.922820.91670.00613426-0.522801
4220.821.181121.2125-0.0313657-0.381134
4321.121.540221.45420.0859954-0.440162
4421.621.689521.62920.0603009-0.0894676
452221.714521.7833-0.06886570.285532
4622.221.990921.95420.03668980.209144
4722.422.002722.1417-0.1390050.397338
4822.822.129722.2792-0.1494210.670255
4922.722.319322.31250.00682870.380671
5022.822.304722.24580.0589120.495255
5122.922.175622.1250.05057870.724421
5222.922.099922.01670.08321760.800116
5322.621.939521.93330.006134260.660532
5421.921.781121.8125-0.03136570.118866
5520.821.706821.62080.0859954-0.906829
5620.321.431121.37080.0603009-1.13113
5720.421.010321.0792-0.0688657-0.610301
5821.220.811720.7750.03668980.38831
5921.420.352720.4917-0.1390051.04734
6020.920.108920.2583-0.1494210.791088
612020.131820.1250.0068287-0.131829
6219.520.142220.08330.058912-0.642245
6319.220.088120.03750.0505787-0.888079
6419.319.974919.89170.0832176-0.674884
6519.419.664519.65830.00613426-0.264468
6619.519.397819.4292-0.03136570.102199
672019.381819.29580.08599540.618171
6820.119.339519.27920.06030090.760532
6919.519.247819.3167-0.06886570.252199
7018.619.399219.36250.0366898-0.79919
7118.419.273519.4125-0.139005-0.873495
7218.419.325619.475-0.149421-0.925579
7319.319.502719.49580.0068287-0.202662
7419.819.546419.48750.0589120.253588
7519.819.588119.53750.05057870.211921
7619.819.766619.68330.08321760.0334491
7720.119.914519.90830.006134260.185532
7820.320.147820.1792-0.03136570.152199
7919.7NANA0.0859954NA
8020.2NANA0.0603009NA
8120.6NANA-0.0688657NA
8221NANA0.0366898NA
8321.4NANA-0.139005NA
8421.9NANA-0.149421NA



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')