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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 11 Dec 2013 17:08:23 -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/11/t1386799757o91d4eb1ca0z370.htm/, Retrieved Thu, 28 Mar 2024 13:47:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232195, Retrieved Thu, 28 Mar 2024 13:47:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-11 22:08:23] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
1,94
1,82
1,8
1,79
1,79
1,78
1,81
1,84
1,87
1,87
1,87
1,84
1,82
1,83
1,83
1,82
1,83
1,87
1,88
1,9
1,98
2,03
2,14
2,42
2,73
2,84
2,85
2,94
3,06
3,24
3,18
3,01
2,87
2,73
2,63
2,39
2,26
2,11
2,01
1,99
1,96
1,93
1,98
2,07
2,24
2,31
2,23
2,26
2,28
2,3
2,33
2,26
2,24
2,47
2,55
2,89
3,21
3,21
2,92
2,68
2,4
2,28
2,24
2,2
2,18
2,23
2,24
2,25
2,23
2,25
2,23
2,21
2,17
2,17
2,13
2,12
2,13
2,17
2,33
2,5
2,57
2,59
2,58
2,31




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=232195&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=232195&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232195&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
11.94NANA0.994742NA
21.82NANA0.98125NA
31.8NANA0.966346NA
41.79NANA0.957015NA
51.79NANA0.957076NA
61.78NANA0.987042NA
71.811.829851.830.9999180.989152
81.841.864661.825421.02150.986777
91.871.921511.827081.051680.973194
101.871.923241.829581.051190.972317
111.871.876971.83251.024270.996284
121.841.852571.837921.007970.993214
131.821.834891.844580.9947420.991888
141.831.815311.850.981251.00809
151.831.794591.857080.9663461.01973
161.821.788021.868330.9570151.01788
171.831.805281.886250.9570761.01369
181.871.896771.921670.9870420.985889
191.881.983591.983750.9999180.947778
201.92.108112.063751.02150.90128
211.982.259362.148331.051680.876355
222.032.352042.23751.051190.863081
232.142.39212.335421.024270.894613
242.422.463242.443751.007970.982448
252.732.541572.5550.9947421.07414
262.842.605632.655420.981251.08995
272.852.646582.738750.9663461.07686
282.942.684432.8050.9570151.09521
293.062.732052.854580.9570761.12004
303.242.836512.873750.9870421.14225
313.182.852682.852920.9999181.11474
323.012.863172.802921.02151.05128
332.872.878972.73751.051680.996883
342.732.799232.662921.051190.975267
352.632.640052.57751.024270.996191
362.392.496832.477081.007970.957212
372.262.360032.37250.9947420.957617
382.112.240522.283330.981250.941746
392.012.143272.217920.9663460.937817
401.992.080712.174170.9570150.956404
411.962.048142.140.9570760.956964
421.932.090472.117920.9870420.923236
431.982.113162.113330.9999180.936985
442.072.16772.122081.02150.954929
452.242.25412.143331.051680.993744
462.312.278892.167921.051191.01365
472.232.2442.190831.024270.993759
482.262.242742.2251.007971.0077
492.282.259312.271250.9947421.00916
502.32.285492.329170.981251.00635
512.332.322852.403750.9663461.00308
522.262.374992.481670.9570150.951582
532.242.438552.547920.9570760.918579
542.472.560552.594170.9870420.964636
552.552.616452.616670.9999180.974602
562.892.677172.620831.02151.0795
573.212.751462.616251.051681.16665
583.212.743612.611.051191.16999
592.922.668222.6051.024271.09436
602.682.613172.59251.007971.02557
612.42.556072.569580.9947420.93894
622.282.482562.530.981250.918406
632.242.379632.46250.9663460.941324
642.22.279292.381670.9570150.965212
652.182.213642.312920.9570760.984805
662.232.235242.264580.9870420.997656
672.242.235232.235420.9999181.00213
682.252.2692.221251.02150.991626
692.232.32642.212081.051680.958561
702.252.3172.204171.051190.971084
712.232.252112.198751.024270.990181
722.212.211662.194171.007970.999248
732.172.183872.195420.9947420.993647
742.172.168152.209580.981251.00085
752.132.158982.234170.9663460.986578
762.122.165252.26250.9570150.979103
772.132.19292.291250.9570760.971316
782.172.280072.310.9870420.951726
792.33NANA0.999918NA
802.5NANA1.0215NA
812.57NANA1.05168NA
822.59NANA1.05119NA
832.58NANA1.02427NA
842.31NANA1.00797NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.94 & NA & NA & 0.994742 & NA \tabularnewline
2 & 1.82 & NA & NA & 0.98125 & NA \tabularnewline
3 & 1.8 & NA & NA & 0.966346 & NA \tabularnewline
4 & 1.79 & NA & NA & 0.957015 & NA \tabularnewline
5 & 1.79 & NA & NA & 0.957076 & NA \tabularnewline
6 & 1.78 & NA & NA & 0.987042 & NA \tabularnewline
7 & 1.81 & 1.82985 & 1.83 & 0.999918 & 0.989152 \tabularnewline
8 & 1.84 & 1.86466 & 1.82542 & 1.0215 & 0.986777 \tabularnewline
9 & 1.87 & 1.92151 & 1.82708 & 1.05168 & 0.973194 \tabularnewline
10 & 1.87 & 1.92324 & 1.82958 & 1.05119 & 0.972317 \tabularnewline
11 & 1.87 & 1.87697 & 1.8325 & 1.02427 & 0.996284 \tabularnewline
12 & 1.84 & 1.85257 & 1.83792 & 1.00797 & 0.993214 \tabularnewline
13 & 1.82 & 1.83489 & 1.84458 & 0.994742 & 0.991888 \tabularnewline
14 & 1.83 & 1.81531 & 1.85 & 0.98125 & 1.00809 \tabularnewline
15 & 1.83 & 1.79459 & 1.85708 & 0.966346 & 1.01973 \tabularnewline
16 & 1.82 & 1.78802 & 1.86833 & 0.957015 & 1.01788 \tabularnewline
17 & 1.83 & 1.80528 & 1.88625 & 0.957076 & 1.01369 \tabularnewline
18 & 1.87 & 1.89677 & 1.92167 & 0.987042 & 0.985889 \tabularnewline
19 & 1.88 & 1.98359 & 1.98375 & 0.999918 & 0.947778 \tabularnewline
20 & 1.9 & 2.10811 & 2.06375 & 1.0215 & 0.90128 \tabularnewline
21 & 1.98 & 2.25936 & 2.14833 & 1.05168 & 0.876355 \tabularnewline
22 & 2.03 & 2.35204 & 2.2375 & 1.05119 & 0.863081 \tabularnewline
23 & 2.14 & 2.3921 & 2.33542 & 1.02427 & 0.894613 \tabularnewline
24 & 2.42 & 2.46324 & 2.44375 & 1.00797 & 0.982448 \tabularnewline
25 & 2.73 & 2.54157 & 2.555 & 0.994742 & 1.07414 \tabularnewline
26 & 2.84 & 2.60563 & 2.65542 & 0.98125 & 1.08995 \tabularnewline
27 & 2.85 & 2.64658 & 2.73875 & 0.966346 & 1.07686 \tabularnewline
28 & 2.94 & 2.68443 & 2.805 & 0.957015 & 1.09521 \tabularnewline
29 & 3.06 & 2.73205 & 2.85458 & 0.957076 & 1.12004 \tabularnewline
30 & 3.24 & 2.83651 & 2.87375 & 0.987042 & 1.14225 \tabularnewline
31 & 3.18 & 2.85268 & 2.85292 & 0.999918 & 1.11474 \tabularnewline
32 & 3.01 & 2.86317 & 2.80292 & 1.0215 & 1.05128 \tabularnewline
33 & 2.87 & 2.87897 & 2.7375 & 1.05168 & 0.996883 \tabularnewline
34 & 2.73 & 2.79923 & 2.66292 & 1.05119 & 0.975267 \tabularnewline
35 & 2.63 & 2.64005 & 2.5775 & 1.02427 & 0.996191 \tabularnewline
36 & 2.39 & 2.49683 & 2.47708 & 1.00797 & 0.957212 \tabularnewline
37 & 2.26 & 2.36003 & 2.3725 & 0.994742 & 0.957617 \tabularnewline
38 & 2.11 & 2.24052 & 2.28333 & 0.98125 & 0.941746 \tabularnewline
39 & 2.01 & 2.14327 & 2.21792 & 0.966346 & 0.937817 \tabularnewline
40 & 1.99 & 2.08071 & 2.17417 & 0.957015 & 0.956404 \tabularnewline
41 & 1.96 & 2.04814 & 2.14 & 0.957076 & 0.956964 \tabularnewline
42 & 1.93 & 2.09047 & 2.11792 & 0.987042 & 0.923236 \tabularnewline
43 & 1.98 & 2.11316 & 2.11333 & 0.999918 & 0.936985 \tabularnewline
44 & 2.07 & 2.1677 & 2.12208 & 1.0215 & 0.954929 \tabularnewline
45 & 2.24 & 2.2541 & 2.14333 & 1.05168 & 0.993744 \tabularnewline
46 & 2.31 & 2.27889 & 2.16792 & 1.05119 & 1.01365 \tabularnewline
47 & 2.23 & 2.244 & 2.19083 & 1.02427 & 0.993759 \tabularnewline
48 & 2.26 & 2.24274 & 2.225 & 1.00797 & 1.0077 \tabularnewline
49 & 2.28 & 2.25931 & 2.27125 & 0.994742 & 1.00916 \tabularnewline
50 & 2.3 & 2.28549 & 2.32917 & 0.98125 & 1.00635 \tabularnewline
51 & 2.33 & 2.32285 & 2.40375 & 0.966346 & 1.00308 \tabularnewline
52 & 2.26 & 2.37499 & 2.48167 & 0.957015 & 0.951582 \tabularnewline
53 & 2.24 & 2.43855 & 2.54792 & 0.957076 & 0.918579 \tabularnewline
54 & 2.47 & 2.56055 & 2.59417 & 0.987042 & 0.964636 \tabularnewline
55 & 2.55 & 2.61645 & 2.61667 & 0.999918 & 0.974602 \tabularnewline
56 & 2.89 & 2.67717 & 2.62083 & 1.0215 & 1.0795 \tabularnewline
57 & 3.21 & 2.75146 & 2.61625 & 1.05168 & 1.16665 \tabularnewline
58 & 3.21 & 2.74361 & 2.61 & 1.05119 & 1.16999 \tabularnewline
59 & 2.92 & 2.66822 & 2.605 & 1.02427 & 1.09436 \tabularnewline
60 & 2.68 & 2.61317 & 2.5925 & 1.00797 & 1.02557 \tabularnewline
61 & 2.4 & 2.55607 & 2.56958 & 0.994742 & 0.93894 \tabularnewline
62 & 2.28 & 2.48256 & 2.53 & 0.98125 & 0.918406 \tabularnewline
63 & 2.24 & 2.37963 & 2.4625 & 0.966346 & 0.941324 \tabularnewline
64 & 2.2 & 2.27929 & 2.38167 & 0.957015 & 0.965212 \tabularnewline
65 & 2.18 & 2.21364 & 2.31292 & 0.957076 & 0.984805 \tabularnewline
66 & 2.23 & 2.23524 & 2.26458 & 0.987042 & 0.997656 \tabularnewline
67 & 2.24 & 2.23523 & 2.23542 & 0.999918 & 1.00213 \tabularnewline
68 & 2.25 & 2.269 & 2.22125 & 1.0215 & 0.991626 \tabularnewline
69 & 2.23 & 2.3264 & 2.21208 & 1.05168 & 0.958561 \tabularnewline
70 & 2.25 & 2.317 & 2.20417 & 1.05119 & 0.971084 \tabularnewline
71 & 2.23 & 2.25211 & 2.19875 & 1.02427 & 0.990181 \tabularnewline
72 & 2.21 & 2.21166 & 2.19417 & 1.00797 & 0.999248 \tabularnewline
73 & 2.17 & 2.18387 & 2.19542 & 0.994742 & 0.993647 \tabularnewline
74 & 2.17 & 2.16815 & 2.20958 & 0.98125 & 1.00085 \tabularnewline
75 & 2.13 & 2.15898 & 2.23417 & 0.966346 & 0.986578 \tabularnewline
76 & 2.12 & 2.16525 & 2.2625 & 0.957015 & 0.979103 \tabularnewline
77 & 2.13 & 2.1929 & 2.29125 & 0.957076 & 0.971316 \tabularnewline
78 & 2.17 & 2.28007 & 2.31 & 0.987042 & 0.951726 \tabularnewline
79 & 2.33 & NA & NA & 0.999918 & NA \tabularnewline
80 & 2.5 & NA & NA & 1.0215 & NA \tabularnewline
81 & 2.57 & NA & NA & 1.05168 & NA \tabularnewline
82 & 2.59 & NA & NA & 1.05119 & NA \tabularnewline
83 & 2.58 & NA & NA & 1.02427 & NA \tabularnewline
84 & 2.31 & NA & NA & 1.00797 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232195&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]1.94[/C][C]NA[/C][C]NA[/C][C]0.994742[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.82[/C][C]NA[/C][C]NA[/C][C]0.98125[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]0.966346[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.79[/C][C]NA[/C][C]NA[/C][C]0.957015[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.79[/C][C]NA[/C][C]NA[/C][C]0.957076[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.78[/C][C]NA[/C][C]NA[/C][C]0.987042[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.81[/C][C]1.82985[/C][C]1.83[/C][C]0.999918[/C][C]0.989152[/C][/ROW]
[ROW][C]8[/C][C]1.84[/C][C]1.86466[/C][C]1.82542[/C][C]1.0215[/C][C]0.986777[/C][/ROW]
[ROW][C]9[/C][C]1.87[/C][C]1.92151[/C][C]1.82708[/C][C]1.05168[/C][C]0.973194[/C][/ROW]
[ROW][C]10[/C][C]1.87[/C][C]1.92324[/C][C]1.82958[/C][C]1.05119[/C][C]0.972317[/C][/ROW]
[ROW][C]11[/C][C]1.87[/C][C]1.87697[/C][C]1.8325[/C][C]1.02427[/C][C]0.996284[/C][/ROW]
[ROW][C]12[/C][C]1.84[/C][C]1.85257[/C][C]1.83792[/C][C]1.00797[/C][C]0.993214[/C][/ROW]
[ROW][C]13[/C][C]1.82[/C][C]1.83489[/C][C]1.84458[/C][C]0.994742[/C][C]0.991888[/C][/ROW]
[ROW][C]14[/C][C]1.83[/C][C]1.81531[/C][C]1.85[/C][C]0.98125[/C][C]1.00809[/C][/ROW]
[ROW][C]15[/C][C]1.83[/C][C]1.79459[/C][C]1.85708[/C][C]0.966346[/C][C]1.01973[/C][/ROW]
[ROW][C]16[/C][C]1.82[/C][C]1.78802[/C][C]1.86833[/C][C]0.957015[/C][C]1.01788[/C][/ROW]
[ROW][C]17[/C][C]1.83[/C][C]1.80528[/C][C]1.88625[/C][C]0.957076[/C][C]1.01369[/C][/ROW]
[ROW][C]18[/C][C]1.87[/C][C]1.89677[/C][C]1.92167[/C][C]0.987042[/C][C]0.985889[/C][/ROW]
[ROW][C]19[/C][C]1.88[/C][C]1.98359[/C][C]1.98375[/C][C]0.999918[/C][C]0.947778[/C][/ROW]
[ROW][C]20[/C][C]1.9[/C][C]2.10811[/C][C]2.06375[/C][C]1.0215[/C][C]0.90128[/C][/ROW]
[ROW][C]21[/C][C]1.98[/C][C]2.25936[/C][C]2.14833[/C][C]1.05168[/C][C]0.876355[/C][/ROW]
[ROW][C]22[/C][C]2.03[/C][C]2.35204[/C][C]2.2375[/C][C]1.05119[/C][C]0.863081[/C][/ROW]
[ROW][C]23[/C][C]2.14[/C][C]2.3921[/C][C]2.33542[/C][C]1.02427[/C][C]0.894613[/C][/ROW]
[ROW][C]24[/C][C]2.42[/C][C]2.46324[/C][C]2.44375[/C][C]1.00797[/C][C]0.982448[/C][/ROW]
[ROW][C]25[/C][C]2.73[/C][C]2.54157[/C][C]2.555[/C][C]0.994742[/C][C]1.07414[/C][/ROW]
[ROW][C]26[/C][C]2.84[/C][C]2.60563[/C][C]2.65542[/C][C]0.98125[/C][C]1.08995[/C][/ROW]
[ROW][C]27[/C][C]2.85[/C][C]2.64658[/C][C]2.73875[/C][C]0.966346[/C][C]1.07686[/C][/ROW]
[ROW][C]28[/C][C]2.94[/C][C]2.68443[/C][C]2.805[/C][C]0.957015[/C][C]1.09521[/C][/ROW]
[ROW][C]29[/C][C]3.06[/C][C]2.73205[/C][C]2.85458[/C][C]0.957076[/C][C]1.12004[/C][/ROW]
[ROW][C]30[/C][C]3.24[/C][C]2.83651[/C][C]2.87375[/C][C]0.987042[/C][C]1.14225[/C][/ROW]
[ROW][C]31[/C][C]3.18[/C][C]2.85268[/C][C]2.85292[/C][C]0.999918[/C][C]1.11474[/C][/ROW]
[ROW][C]32[/C][C]3.01[/C][C]2.86317[/C][C]2.80292[/C][C]1.0215[/C][C]1.05128[/C][/ROW]
[ROW][C]33[/C][C]2.87[/C][C]2.87897[/C][C]2.7375[/C][C]1.05168[/C][C]0.996883[/C][/ROW]
[ROW][C]34[/C][C]2.73[/C][C]2.79923[/C][C]2.66292[/C][C]1.05119[/C][C]0.975267[/C][/ROW]
[ROW][C]35[/C][C]2.63[/C][C]2.64005[/C][C]2.5775[/C][C]1.02427[/C][C]0.996191[/C][/ROW]
[ROW][C]36[/C][C]2.39[/C][C]2.49683[/C][C]2.47708[/C][C]1.00797[/C][C]0.957212[/C][/ROW]
[ROW][C]37[/C][C]2.26[/C][C]2.36003[/C][C]2.3725[/C][C]0.994742[/C][C]0.957617[/C][/ROW]
[ROW][C]38[/C][C]2.11[/C][C]2.24052[/C][C]2.28333[/C][C]0.98125[/C][C]0.941746[/C][/ROW]
[ROW][C]39[/C][C]2.01[/C][C]2.14327[/C][C]2.21792[/C][C]0.966346[/C][C]0.937817[/C][/ROW]
[ROW][C]40[/C][C]1.99[/C][C]2.08071[/C][C]2.17417[/C][C]0.957015[/C][C]0.956404[/C][/ROW]
[ROW][C]41[/C][C]1.96[/C][C]2.04814[/C][C]2.14[/C][C]0.957076[/C][C]0.956964[/C][/ROW]
[ROW][C]42[/C][C]1.93[/C][C]2.09047[/C][C]2.11792[/C][C]0.987042[/C][C]0.923236[/C][/ROW]
[ROW][C]43[/C][C]1.98[/C][C]2.11316[/C][C]2.11333[/C][C]0.999918[/C][C]0.936985[/C][/ROW]
[ROW][C]44[/C][C]2.07[/C][C]2.1677[/C][C]2.12208[/C][C]1.0215[/C][C]0.954929[/C][/ROW]
[ROW][C]45[/C][C]2.24[/C][C]2.2541[/C][C]2.14333[/C][C]1.05168[/C][C]0.993744[/C][/ROW]
[ROW][C]46[/C][C]2.31[/C][C]2.27889[/C][C]2.16792[/C][C]1.05119[/C][C]1.01365[/C][/ROW]
[ROW][C]47[/C][C]2.23[/C][C]2.244[/C][C]2.19083[/C][C]1.02427[/C][C]0.993759[/C][/ROW]
[ROW][C]48[/C][C]2.26[/C][C]2.24274[/C][C]2.225[/C][C]1.00797[/C][C]1.0077[/C][/ROW]
[ROW][C]49[/C][C]2.28[/C][C]2.25931[/C][C]2.27125[/C][C]0.994742[/C][C]1.00916[/C][/ROW]
[ROW][C]50[/C][C]2.3[/C][C]2.28549[/C][C]2.32917[/C][C]0.98125[/C][C]1.00635[/C][/ROW]
[ROW][C]51[/C][C]2.33[/C][C]2.32285[/C][C]2.40375[/C][C]0.966346[/C][C]1.00308[/C][/ROW]
[ROW][C]52[/C][C]2.26[/C][C]2.37499[/C][C]2.48167[/C][C]0.957015[/C][C]0.951582[/C][/ROW]
[ROW][C]53[/C][C]2.24[/C][C]2.43855[/C][C]2.54792[/C][C]0.957076[/C][C]0.918579[/C][/ROW]
[ROW][C]54[/C][C]2.47[/C][C]2.56055[/C][C]2.59417[/C][C]0.987042[/C][C]0.964636[/C][/ROW]
[ROW][C]55[/C][C]2.55[/C][C]2.61645[/C][C]2.61667[/C][C]0.999918[/C][C]0.974602[/C][/ROW]
[ROW][C]56[/C][C]2.89[/C][C]2.67717[/C][C]2.62083[/C][C]1.0215[/C][C]1.0795[/C][/ROW]
[ROW][C]57[/C][C]3.21[/C][C]2.75146[/C][C]2.61625[/C][C]1.05168[/C][C]1.16665[/C][/ROW]
[ROW][C]58[/C][C]3.21[/C][C]2.74361[/C][C]2.61[/C][C]1.05119[/C][C]1.16999[/C][/ROW]
[ROW][C]59[/C][C]2.92[/C][C]2.66822[/C][C]2.605[/C][C]1.02427[/C][C]1.09436[/C][/ROW]
[ROW][C]60[/C][C]2.68[/C][C]2.61317[/C][C]2.5925[/C][C]1.00797[/C][C]1.02557[/C][/ROW]
[ROW][C]61[/C][C]2.4[/C][C]2.55607[/C][C]2.56958[/C][C]0.994742[/C][C]0.93894[/C][/ROW]
[ROW][C]62[/C][C]2.28[/C][C]2.48256[/C][C]2.53[/C][C]0.98125[/C][C]0.918406[/C][/ROW]
[ROW][C]63[/C][C]2.24[/C][C]2.37963[/C][C]2.4625[/C][C]0.966346[/C][C]0.941324[/C][/ROW]
[ROW][C]64[/C][C]2.2[/C][C]2.27929[/C][C]2.38167[/C][C]0.957015[/C][C]0.965212[/C][/ROW]
[ROW][C]65[/C][C]2.18[/C][C]2.21364[/C][C]2.31292[/C][C]0.957076[/C][C]0.984805[/C][/ROW]
[ROW][C]66[/C][C]2.23[/C][C]2.23524[/C][C]2.26458[/C][C]0.987042[/C][C]0.997656[/C][/ROW]
[ROW][C]67[/C][C]2.24[/C][C]2.23523[/C][C]2.23542[/C][C]0.999918[/C][C]1.00213[/C][/ROW]
[ROW][C]68[/C][C]2.25[/C][C]2.269[/C][C]2.22125[/C][C]1.0215[/C][C]0.991626[/C][/ROW]
[ROW][C]69[/C][C]2.23[/C][C]2.3264[/C][C]2.21208[/C][C]1.05168[/C][C]0.958561[/C][/ROW]
[ROW][C]70[/C][C]2.25[/C][C]2.317[/C][C]2.20417[/C][C]1.05119[/C][C]0.971084[/C][/ROW]
[ROW][C]71[/C][C]2.23[/C][C]2.25211[/C][C]2.19875[/C][C]1.02427[/C][C]0.990181[/C][/ROW]
[ROW][C]72[/C][C]2.21[/C][C]2.21166[/C][C]2.19417[/C][C]1.00797[/C][C]0.999248[/C][/ROW]
[ROW][C]73[/C][C]2.17[/C][C]2.18387[/C][C]2.19542[/C][C]0.994742[/C][C]0.993647[/C][/ROW]
[ROW][C]74[/C][C]2.17[/C][C]2.16815[/C][C]2.20958[/C][C]0.98125[/C][C]1.00085[/C][/ROW]
[ROW][C]75[/C][C]2.13[/C][C]2.15898[/C][C]2.23417[/C][C]0.966346[/C][C]0.986578[/C][/ROW]
[ROW][C]76[/C][C]2.12[/C][C]2.16525[/C][C]2.2625[/C][C]0.957015[/C][C]0.979103[/C][/ROW]
[ROW][C]77[/C][C]2.13[/C][C]2.1929[/C][C]2.29125[/C][C]0.957076[/C][C]0.971316[/C][/ROW]
[ROW][C]78[/C][C]2.17[/C][C]2.28007[/C][C]2.31[/C][C]0.987042[/C][C]0.951726[/C][/ROW]
[ROW][C]79[/C][C]2.33[/C][C]NA[/C][C]NA[/C][C]0.999918[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]2.5[/C][C]NA[/C][C]NA[/C][C]1.0215[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]2.57[/C][C]NA[/C][C]NA[/C][C]1.05168[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]2.59[/C][C]NA[/C][C]NA[/C][C]1.05119[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]2.58[/C][C]NA[/C][C]NA[/C][C]1.02427[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]2.31[/C][C]NA[/C][C]NA[/C][C]1.00797[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232195&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232195&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
11.94NANA0.994742NA
21.82NANA0.98125NA
31.8NANA0.966346NA
41.79NANA0.957015NA
51.79NANA0.957076NA
61.78NANA0.987042NA
71.811.829851.830.9999180.989152
81.841.864661.825421.02150.986777
91.871.921511.827081.051680.973194
101.871.923241.829581.051190.972317
111.871.876971.83251.024270.996284
121.841.852571.837921.007970.993214
131.821.834891.844580.9947420.991888
141.831.815311.850.981251.00809
151.831.794591.857080.9663461.01973
161.821.788021.868330.9570151.01788
171.831.805281.886250.9570761.01369
181.871.896771.921670.9870420.985889
191.881.983591.983750.9999180.947778
201.92.108112.063751.02150.90128
211.982.259362.148331.051680.876355
222.032.352042.23751.051190.863081
232.142.39212.335421.024270.894613
242.422.463242.443751.007970.982448
252.732.541572.5550.9947421.07414
262.842.605632.655420.981251.08995
272.852.646582.738750.9663461.07686
282.942.684432.8050.9570151.09521
293.062.732052.854580.9570761.12004
303.242.836512.873750.9870421.14225
313.182.852682.852920.9999181.11474
323.012.863172.802921.02151.05128
332.872.878972.73751.051680.996883
342.732.799232.662921.051190.975267
352.632.640052.57751.024270.996191
362.392.496832.477081.007970.957212
372.262.360032.37250.9947420.957617
382.112.240522.283330.981250.941746
392.012.143272.217920.9663460.937817
401.992.080712.174170.9570150.956404
411.962.048142.140.9570760.956964
421.932.090472.117920.9870420.923236
431.982.113162.113330.9999180.936985
442.072.16772.122081.02150.954929
452.242.25412.143331.051680.993744
462.312.278892.167921.051191.01365
472.232.2442.190831.024270.993759
482.262.242742.2251.007971.0077
492.282.259312.271250.9947421.00916
502.32.285492.329170.981251.00635
512.332.322852.403750.9663461.00308
522.262.374992.481670.9570150.951582
532.242.438552.547920.9570760.918579
542.472.560552.594170.9870420.964636
552.552.616452.616670.9999180.974602
562.892.677172.620831.02151.0795
573.212.751462.616251.051681.16665
583.212.743612.611.051191.16999
592.922.668222.6051.024271.09436
602.682.613172.59251.007971.02557
612.42.556072.569580.9947420.93894
622.282.482562.530.981250.918406
632.242.379632.46250.9663460.941324
642.22.279292.381670.9570150.965212
652.182.213642.312920.9570760.984805
662.232.235242.264580.9870420.997656
672.242.235232.235420.9999181.00213
682.252.2692.221251.02150.991626
692.232.32642.212081.051680.958561
702.252.3172.204171.051190.971084
712.232.252112.198751.024270.990181
722.212.211662.194171.007970.999248
732.172.183872.195420.9947420.993647
742.172.168152.209580.981251.00085
752.132.158982.234170.9663460.986578
762.122.165252.26250.9570150.979103
772.132.19292.291250.9570760.971316
782.172.280072.310.9870420.951726
792.33NANA0.999918NA
802.5NANA1.0215NA
812.57NANA1.05168NA
822.59NANA1.05119NA
832.58NANA1.02427NA
842.31NANA1.00797NA



Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = multiplicative ; 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')