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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 29 Nov 2011 16:43:16 -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/2011/Nov/29/t1322603011bzi7yfatvjclzvu.htm/, Retrieved Thu, 31 Oct 2024 23:12:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=148743, Retrieved Thu, 31 Oct 2024 23:12:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD    [Classical Decomposition] [test] [2011-11-29 21:43:16] [8aedcf735e397266388b06f47fe45218] [Current]
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Dataseries X:
13328
12873
14000
13477
14237
13674
13529
14058
12975
14326
14008
16193
14483
14011
15057
14884
15414
14440
14900
15074
14442
15307
14938
17193
15528
14765
15838
15723
16150
15486
15986
15983
15692
16490
15686
18897
16316
15636
17163
16534
16518
16375
16290
16352
15943
16362
16393
19051
16747
16320
17910
16961
17480
17049
16879
17473
16998
17307
17418
20169
17871
17226
19062
17804
19100
18522
18060
18869
18127
18871
18890
21263
19547
18450
20254
19240
20216
19420
19415
20018
18652
19978
19509
21971




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148743&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148743&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148743&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 time2 seconds
R Server'George Udny Yule' @ yule.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
113328NANA-42.3935185185186NA
212873NANA-805.324074074074NA
314000NANA593.196759259259NA
413477NANA-175.143518518519NA
514237NANA369.405092592592NA
613674NANA-306.587962962964NA
71352913578.835648148113937.9583333333-359.122685185186-49.835648148146
81405813953.293981481514033.5-80.2060185185185104.70601851852
91297513357.259259259314124.9583333333-767.699074074074-382.259259259257
101432614124.141203703714227.625-103.483796296296201.858796296297
111400813928.59953703714335.2916666667-406.69212962962979.4004629629635
121619316500.300925925914416.252084.05092592593-307.300925925927
131448314462.898148148114505.2916666667-42.393518518518620.1018518518504
141401113799.425925925914604.75-805.324074074074211.574074074073
151505715301.405092592614708.2083333333593.196759259259-244.405092592591
161488414635.064814814814810.2083333333-175.143518518519248.935185185186
171541415259.238425925914889.8333333333369.405092592592154.761574074075
181444014663.66203703714970.25-306.587962962964-223.662037037036
191490014696.335648148115055.4583333333-359.122685185186203.66435185185
201507415050.210648148115130.4166666667-80.206018518518523.7893518518522
211444214426.675925925915194.375-767.69907407407415.3240740740766
221530715158.391203703715261.875-103.483796296296148.608796296297
231493814920.807870370415327.5-406.69212962962917.1921296296296
241719317485.800925925915401.752084.05092592593-292.800925925925
251552815448.189814814815490.5833333333-42.393518518518679.8101851851843
261476514768.384259259315573.7083333333-805.324074074074-3.38425925926094
271583816256.863425925915663.6666666667593.196759259259-418.863425925925
281572315589.898148148115765.0416666667-175.143518518519133.101851851852
291615016214.905092592615845.5369.405092592592-64.905092592593
301548615641.078703703715947.6666666667-306.587962962964-155.078703703704
311598615692.377314814816051.5-359.122685185186293.622685185186
321598316040.418981481516120.625-80.2060185185185-57.4189814814836
331569215444.425925925916212.125-767.699074074074247.574074074075
341649016197.641203703716301.125-103.483796296296292.358796296297
351568615943.557870370416350.25-406.692129629629-257.557870370367
361889718486.675925925916402.6252084.05092592593410.324074074077
371631616409.939814814816452.3333333333-42.3935185185186-93.9398148148102
381563615675.050925925916480.375-805.324074074074-39.0509259259234
391716317099.405092592616506.2083333333593.19675925925963.5949074074124
401653416336.189814814816511.3333333333-175.143518518519197.810185185186
411651816904.863425925916535.4583333333369.405092592592-386.863425925925
421637516264.745370370416571.3333333333-306.587962962964110.254629629631
431629016236.585648148116595.7083333333-359.12268518518653.414351851854
441635216561.960648148116642.1666666667-80.2060185185185-209.960648148146
451594315934.092592592616701.7916666667-767.6990740740748.90740740740875
461636216647.22453703716750.7083333333-103.483796296296-285.224537037036
471639316401.891203703716808.5833333333-406.692129629629-8.89120370370438
481905118960.800925925916876.752084.0509259259390.199074074073
491674716886.981481481516929.375-42.3935185185186-139.981481481482
501632016195.300925925917000.625-805.324074074074124.699074074069
511791017684.488425925917091.2916666667593.196759259259225.511574074073
521696116999.481481481517174.625-175.143518518519-38.4814814814818
531748017626.113425925917256.7083333333369.405092592592-146.113425925923
541704917039.41203703717346-306.5879629629649.5879629629635
551687917080.293981481517439.4166666667-359.122685185186-201.293981481478
561747317443.793981481517524-80.206018518518529.2060185185182
571699816842.050925925917609.75-767.699074074074155.949074074073
581730717589.391203703717692.875-103.483796296296-282.391203703704
591741817388.807870370417795.5-406.69212962962929.1921296296277
602016920008.425925925917924.3752084.05092592593160.574074074073
611787117992.564814814818034.9583333333-42.3935185185186-121.564814814814
621722617337.009259259318142.3333333333-805.324074074074-111.009259259259
631906218840.738425925918247.5416666667593.196759259259221.261574074077
641780418184.606481481518359.75-175.143518518519-380.606481481478
651910018855.655092592618486.25369.405092592592244.344907407412
661852218286.578703703718593.1666666667-306.587962962964235.421296296299
671806018349.460648148118708.5833333333-359.122685185186-289.460648148146
681886918749.210648148118829.4166666667-80.2060185185185119.789351851854
691812718162.384259259318930.0833333333-767.699074074074-35.3842592592628
701887118936.09953703719039.5833333333-103.483796296296-65.0995370370365
711889018739.22453703719145.9166666667-406.692129629629150.775462962964
722126321313.884259259319229.83333333332084.05092592593-50.8842592592591
731954719281.314814814819323.7083333333-42.3935185185186265.685185185186
741845018622.717592592619428.0416666667-805.324074074074-172.717592592588
752025420090.988425925919497.7916666667593.196759259259163.011574074073
761924019390.648148148119565.7916666667-175.143518518519-150.64814814815
772021620007.113425925919637.7083333333369.405092592592208.886574074073
781942019386.41203703719693-306.58796296296433.5879629629635
7919415NANA-359.122685185186NA
8020018NANA-80.2060185185185NA
8118652NANA-767.699074074074NA
8219978NANA-103.483796296296NA
8319509NANA-406.692129629629NA
8421971NANA2084.05092592593NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 13328 & NA & NA & -42.3935185185186 & NA \tabularnewline
2 & 12873 & NA & NA & -805.324074074074 & NA \tabularnewline
3 & 14000 & NA & NA & 593.196759259259 & NA \tabularnewline
4 & 13477 & NA & NA & -175.143518518519 & NA \tabularnewline
5 & 14237 & NA & NA & 369.405092592592 & NA \tabularnewline
6 & 13674 & NA & NA & -306.587962962964 & NA \tabularnewline
7 & 13529 & 13578.8356481481 & 13937.9583333333 & -359.122685185186 & -49.835648148146 \tabularnewline
8 & 14058 & 13953.2939814815 & 14033.5 & -80.2060185185185 & 104.70601851852 \tabularnewline
9 & 12975 & 13357.2592592593 & 14124.9583333333 & -767.699074074074 & -382.259259259257 \tabularnewline
10 & 14326 & 14124.1412037037 & 14227.625 & -103.483796296296 & 201.858796296297 \tabularnewline
11 & 14008 & 13928.599537037 & 14335.2916666667 & -406.692129629629 & 79.4004629629635 \tabularnewline
12 & 16193 & 16500.3009259259 & 14416.25 & 2084.05092592593 & -307.300925925927 \tabularnewline
13 & 14483 & 14462.8981481481 & 14505.2916666667 & -42.3935185185186 & 20.1018518518504 \tabularnewline
14 & 14011 & 13799.4259259259 & 14604.75 & -805.324074074074 & 211.574074074073 \tabularnewline
15 & 15057 & 15301.4050925926 & 14708.2083333333 & 593.196759259259 & -244.405092592591 \tabularnewline
16 & 14884 & 14635.0648148148 & 14810.2083333333 & -175.143518518519 & 248.935185185186 \tabularnewline
17 & 15414 & 15259.2384259259 & 14889.8333333333 & 369.405092592592 & 154.761574074075 \tabularnewline
18 & 14440 & 14663.662037037 & 14970.25 & -306.587962962964 & -223.662037037036 \tabularnewline
19 & 14900 & 14696.3356481481 & 15055.4583333333 & -359.122685185186 & 203.66435185185 \tabularnewline
20 & 15074 & 15050.2106481481 & 15130.4166666667 & -80.2060185185185 & 23.7893518518522 \tabularnewline
21 & 14442 & 14426.6759259259 & 15194.375 & -767.699074074074 & 15.3240740740766 \tabularnewline
22 & 15307 & 15158.3912037037 & 15261.875 & -103.483796296296 & 148.608796296297 \tabularnewline
23 & 14938 & 14920.8078703704 & 15327.5 & -406.692129629629 & 17.1921296296296 \tabularnewline
24 & 17193 & 17485.8009259259 & 15401.75 & 2084.05092592593 & -292.800925925925 \tabularnewline
25 & 15528 & 15448.1898148148 & 15490.5833333333 & -42.3935185185186 & 79.8101851851843 \tabularnewline
26 & 14765 & 14768.3842592593 & 15573.7083333333 & -805.324074074074 & -3.38425925926094 \tabularnewline
27 & 15838 & 16256.8634259259 & 15663.6666666667 & 593.196759259259 & -418.863425925925 \tabularnewline
28 & 15723 & 15589.8981481481 & 15765.0416666667 & -175.143518518519 & 133.101851851852 \tabularnewline
29 & 16150 & 16214.9050925926 & 15845.5 & 369.405092592592 & -64.905092592593 \tabularnewline
30 & 15486 & 15641.0787037037 & 15947.6666666667 & -306.587962962964 & -155.078703703704 \tabularnewline
31 & 15986 & 15692.3773148148 & 16051.5 & -359.122685185186 & 293.622685185186 \tabularnewline
32 & 15983 & 16040.4189814815 & 16120.625 & -80.2060185185185 & -57.4189814814836 \tabularnewline
33 & 15692 & 15444.4259259259 & 16212.125 & -767.699074074074 & 247.574074074075 \tabularnewline
34 & 16490 & 16197.6412037037 & 16301.125 & -103.483796296296 & 292.358796296297 \tabularnewline
35 & 15686 & 15943.5578703704 & 16350.25 & -406.692129629629 & -257.557870370367 \tabularnewline
36 & 18897 & 18486.6759259259 & 16402.625 & 2084.05092592593 & 410.324074074077 \tabularnewline
37 & 16316 & 16409.9398148148 & 16452.3333333333 & -42.3935185185186 & -93.9398148148102 \tabularnewline
38 & 15636 & 15675.0509259259 & 16480.375 & -805.324074074074 & -39.0509259259234 \tabularnewline
39 & 17163 & 17099.4050925926 & 16506.2083333333 & 593.196759259259 & 63.5949074074124 \tabularnewline
40 & 16534 & 16336.1898148148 & 16511.3333333333 & -175.143518518519 & 197.810185185186 \tabularnewline
41 & 16518 & 16904.8634259259 & 16535.4583333333 & 369.405092592592 & -386.863425925925 \tabularnewline
42 & 16375 & 16264.7453703704 & 16571.3333333333 & -306.587962962964 & 110.254629629631 \tabularnewline
43 & 16290 & 16236.5856481481 & 16595.7083333333 & -359.122685185186 & 53.414351851854 \tabularnewline
44 & 16352 & 16561.9606481481 & 16642.1666666667 & -80.2060185185185 & -209.960648148146 \tabularnewline
45 & 15943 & 15934.0925925926 & 16701.7916666667 & -767.699074074074 & 8.90740740740875 \tabularnewline
46 & 16362 & 16647.224537037 & 16750.7083333333 & -103.483796296296 & -285.224537037036 \tabularnewline
47 & 16393 & 16401.8912037037 & 16808.5833333333 & -406.692129629629 & -8.89120370370438 \tabularnewline
48 & 19051 & 18960.8009259259 & 16876.75 & 2084.05092592593 & 90.199074074073 \tabularnewline
49 & 16747 & 16886.9814814815 & 16929.375 & -42.3935185185186 & -139.981481481482 \tabularnewline
50 & 16320 & 16195.3009259259 & 17000.625 & -805.324074074074 & 124.699074074069 \tabularnewline
51 & 17910 & 17684.4884259259 & 17091.2916666667 & 593.196759259259 & 225.511574074073 \tabularnewline
52 & 16961 & 16999.4814814815 & 17174.625 & -175.143518518519 & -38.4814814814818 \tabularnewline
53 & 17480 & 17626.1134259259 & 17256.7083333333 & 369.405092592592 & -146.113425925923 \tabularnewline
54 & 17049 & 17039.412037037 & 17346 & -306.587962962964 & 9.5879629629635 \tabularnewline
55 & 16879 & 17080.2939814815 & 17439.4166666667 & -359.122685185186 & -201.293981481478 \tabularnewline
56 & 17473 & 17443.7939814815 & 17524 & -80.2060185185185 & 29.2060185185182 \tabularnewline
57 & 16998 & 16842.0509259259 & 17609.75 & -767.699074074074 & 155.949074074073 \tabularnewline
58 & 17307 & 17589.3912037037 & 17692.875 & -103.483796296296 & -282.391203703704 \tabularnewline
59 & 17418 & 17388.8078703704 & 17795.5 & -406.692129629629 & 29.1921296296277 \tabularnewline
60 & 20169 & 20008.4259259259 & 17924.375 & 2084.05092592593 & 160.574074074073 \tabularnewline
61 & 17871 & 17992.5648148148 & 18034.9583333333 & -42.3935185185186 & -121.564814814814 \tabularnewline
62 & 17226 & 17337.0092592593 & 18142.3333333333 & -805.324074074074 & -111.009259259259 \tabularnewline
63 & 19062 & 18840.7384259259 & 18247.5416666667 & 593.196759259259 & 221.261574074077 \tabularnewline
64 & 17804 & 18184.6064814815 & 18359.75 & -175.143518518519 & -380.606481481478 \tabularnewline
65 & 19100 & 18855.6550925926 & 18486.25 & 369.405092592592 & 244.344907407412 \tabularnewline
66 & 18522 & 18286.5787037037 & 18593.1666666667 & -306.587962962964 & 235.421296296299 \tabularnewline
67 & 18060 & 18349.4606481481 & 18708.5833333333 & -359.122685185186 & -289.460648148146 \tabularnewline
68 & 18869 & 18749.2106481481 & 18829.4166666667 & -80.2060185185185 & 119.789351851854 \tabularnewline
69 & 18127 & 18162.3842592593 & 18930.0833333333 & -767.699074074074 & -35.3842592592628 \tabularnewline
70 & 18871 & 18936.099537037 & 19039.5833333333 & -103.483796296296 & -65.0995370370365 \tabularnewline
71 & 18890 & 18739.224537037 & 19145.9166666667 & -406.692129629629 & 150.775462962964 \tabularnewline
72 & 21263 & 21313.8842592593 & 19229.8333333333 & 2084.05092592593 & -50.8842592592591 \tabularnewline
73 & 19547 & 19281.3148148148 & 19323.7083333333 & -42.3935185185186 & 265.685185185186 \tabularnewline
74 & 18450 & 18622.7175925926 & 19428.0416666667 & -805.324074074074 & -172.717592592588 \tabularnewline
75 & 20254 & 20090.9884259259 & 19497.7916666667 & 593.196759259259 & 163.011574074073 \tabularnewline
76 & 19240 & 19390.6481481481 & 19565.7916666667 & -175.143518518519 & -150.64814814815 \tabularnewline
77 & 20216 & 20007.1134259259 & 19637.7083333333 & 369.405092592592 & 208.886574074073 \tabularnewline
78 & 19420 & 19386.412037037 & 19693 & -306.587962962964 & 33.5879629629635 \tabularnewline
79 & 19415 & NA & NA & -359.122685185186 & NA \tabularnewline
80 & 20018 & NA & NA & -80.2060185185185 & NA \tabularnewline
81 & 18652 & NA & NA & -767.699074074074 & NA \tabularnewline
82 & 19978 & NA & NA & -103.483796296296 & NA \tabularnewline
83 & 19509 & NA & NA & -406.692129629629 & NA \tabularnewline
84 & 21971 & NA & NA & 2084.05092592593 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=148743&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]13328[/C][C]NA[/C][C]NA[/C][C]-42.3935185185186[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]12873[/C][C]NA[/C][C]NA[/C][C]-805.324074074074[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]14000[/C][C]NA[/C][C]NA[/C][C]593.196759259259[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]13477[/C][C]NA[/C][C]NA[/C][C]-175.143518518519[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]14237[/C][C]NA[/C][C]NA[/C][C]369.405092592592[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]13674[/C][C]NA[/C][C]NA[/C][C]-306.587962962964[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]13529[/C][C]13578.8356481481[/C][C]13937.9583333333[/C][C]-359.122685185186[/C][C]-49.835648148146[/C][/ROW]
[ROW][C]8[/C][C]14058[/C][C]13953.2939814815[/C][C]14033.5[/C][C]-80.2060185185185[/C][C]104.70601851852[/C][/ROW]
[ROW][C]9[/C][C]12975[/C][C]13357.2592592593[/C][C]14124.9583333333[/C][C]-767.699074074074[/C][C]-382.259259259257[/C][/ROW]
[ROW][C]10[/C][C]14326[/C][C]14124.1412037037[/C][C]14227.625[/C][C]-103.483796296296[/C][C]201.858796296297[/C][/ROW]
[ROW][C]11[/C][C]14008[/C][C]13928.599537037[/C][C]14335.2916666667[/C][C]-406.692129629629[/C][C]79.4004629629635[/C][/ROW]
[ROW][C]12[/C][C]16193[/C][C]16500.3009259259[/C][C]14416.25[/C][C]2084.05092592593[/C][C]-307.300925925927[/C][/ROW]
[ROW][C]13[/C][C]14483[/C][C]14462.8981481481[/C][C]14505.2916666667[/C][C]-42.3935185185186[/C][C]20.1018518518504[/C][/ROW]
[ROW][C]14[/C][C]14011[/C][C]13799.4259259259[/C][C]14604.75[/C][C]-805.324074074074[/C][C]211.574074074073[/C][/ROW]
[ROW][C]15[/C][C]15057[/C][C]15301.4050925926[/C][C]14708.2083333333[/C][C]593.196759259259[/C][C]-244.405092592591[/C][/ROW]
[ROW][C]16[/C][C]14884[/C][C]14635.0648148148[/C][C]14810.2083333333[/C][C]-175.143518518519[/C][C]248.935185185186[/C][/ROW]
[ROW][C]17[/C][C]15414[/C][C]15259.2384259259[/C][C]14889.8333333333[/C][C]369.405092592592[/C][C]154.761574074075[/C][/ROW]
[ROW][C]18[/C][C]14440[/C][C]14663.662037037[/C][C]14970.25[/C][C]-306.587962962964[/C][C]-223.662037037036[/C][/ROW]
[ROW][C]19[/C][C]14900[/C][C]14696.3356481481[/C][C]15055.4583333333[/C][C]-359.122685185186[/C][C]203.66435185185[/C][/ROW]
[ROW][C]20[/C][C]15074[/C][C]15050.2106481481[/C][C]15130.4166666667[/C][C]-80.2060185185185[/C][C]23.7893518518522[/C][/ROW]
[ROW][C]21[/C][C]14442[/C][C]14426.6759259259[/C][C]15194.375[/C][C]-767.699074074074[/C][C]15.3240740740766[/C][/ROW]
[ROW][C]22[/C][C]15307[/C][C]15158.3912037037[/C][C]15261.875[/C][C]-103.483796296296[/C][C]148.608796296297[/C][/ROW]
[ROW][C]23[/C][C]14938[/C][C]14920.8078703704[/C][C]15327.5[/C][C]-406.692129629629[/C][C]17.1921296296296[/C][/ROW]
[ROW][C]24[/C][C]17193[/C][C]17485.8009259259[/C][C]15401.75[/C][C]2084.05092592593[/C][C]-292.800925925925[/C][/ROW]
[ROW][C]25[/C][C]15528[/C][C]15448.1898148148[/C][C]15490.5833333333[/C][C]-42.3935185185186[/C][C]79.8101851851843[/C][/ROW]
[ROW][C]26[/C][C]14765[/C][C]14768.3842592593[/C][C]15573.7083333333[/C][C]-805.324074074074[/C][C]-3.38425925926094[/C][/ROW]
[ROW][C]27[/C][C]15838[/C][C]16256.8634259259[/C][C]15663.6666666667[/C][C]593.196759259259[/C][C]-418.863425925925[/C][/ROW]
[ROW][C]28[/C][C]15723[/C][C]15589.8981481481[/C][C]15765.0416666667[/C][C]-175.143518518519[/C][C]133.101851851852[/C][/ROW]
[ROW][C]29[/C][C]16150[/C][C]16214.9050925926[/C][C]15845.5[/C][C]369.405092592592[/C][C]-64.905092592593[/C][/ROW]
[ROW][C]30[/C][C]15486[/C][C]15641.0787037037[/C][C]15947.6666666667[/C][C]-306.587962962964[/C][C]-155.078703703704[/C][/ROW]
[ROW][C]31[/C][C]15986[/C][C]15692.3773148148[/C][C]16051.5[/C][C]-359.122685185186[/C][C]293.622685185186[/C][/ROW]
[ROW][C]32[/C][C]15983[/C][C]16040.4189814815[/C][C]16120.625[/C][C]-80.2060185185185[/C][C]-57.4189814814836[/C][/ROW]
[ROW][C]33[/C][C]15692[/C][C]15444.4259259259[/C][C]16212.125[/C][C]-767.699074074074[/C][C]247.574074074075[/C][/ROW]
[ROW][C]34[/C][C]16490[/C][C]16197.6412037037[/C][C]16301.125[/C][C]-103.483796296296[/C][C]292.358796296297[/C][/ROW]
[ROW][C]35[/C][C]15686[/C][C]15943.5578703704[/C][C]16350.25[/C][C]-406.692129629629[/C][C]-257.557870370367[/C][/ROW]
[ROW][C]36[/C][C]18897[/C][C]18486.6759259259[/C][C]16402.625[/C][C]2084.05092592593[/C][C]410.324074074077[/C][/ROW]
[ROW][C]37[/C][C]16316[/C][C]16409.9398148148[/C][C]16452.3333333333[/C][C]-42.3935185185186[/C][C]-93.9398148148102[/C][/ROW]
[ROW][C]38[/C][C]15636[/C][C]15675.0509259259[/C][C]16480.375[/C][C]-805.324074074074[/C][C]-39.0509259259234[/C][/ROW]
[ROW][C]39[/C][C]17163[/C][C]17099.4050925926[/C][C]16506.2083333333[/C][C]593.196759259259[/C][C]63.5949074074124[/C][/ROW]
[ROW][C]40[/C][C]16534[/C][C]16336.1898148148[/C][C]16511.3333333333[/C][C]-175.143518518519[/C][C]197.810185185186[/C][/ROW]
[ROW][C]41[/C][C]16518[/C][C]16904.8634259259[/C][C]16535.4583333333[/C][C]369.405092592592[/C][C]-386.863425925925[/C][/ROW]
[ROW][C]42[/C][C]16375[/C][C]16264.7453703704[/C][C]16571.3333333333[/C][C]-306.587962962964[/C][C]110.254629629631[/C][/ROW]
[ROW][C]43[/C][C]16290[/C][C]16236.5856481481[/C][C]16595.7083333333[/C][C]-359.122685185186[/C][C]53.414351851854[/C][/ROW]
[ROW][C]44[/C][C]16352[/C][C]16561.9606481481[/C][C]16642.1666666667[/C][C]-80.2060185185185[/C][C]-209.960648148146[/C][/ROW]
[ROW][C]45[/C][C]15943[/C][C]15934.0925925926[/C][C]16701.7916666667[/C][C]-767.699074074074[/C][C]8.90740740740875[/C][/ROW]
[ROW][C]46[/C][C]16362[/C][C]16647.224537037[/C][C]16750.7083333333[/C][C]-103.483796296296[/C][C]-285.224537037036[/C][/ROW]
[ROW][C]47[/C][C]16393[/C][C]16401.8912037037[/C][C]16808.5833333333[/C][C]-406.692129629629[/C][C]-8.89120370370438[/C][/ROW]
[ROW][C]48[/C][C]19051[/C][C]18960.8009259259[/C][C]16876.75[/C][C]2084.05092592593[/C][C]90.199074074073[/C][/ROW]
[ROW][C]49[/C][C]16747[/C][C]16886.9814814815[/C][C]16929.375[/C][C]-42.3935185185186[/C][C]-139.981481481482[/C][/ROW]
[ROW][C]50[/C][C]16320[/C][C]16195.3009259259[/C][C]17000.625[/C][C]-805.324074074074[/C][C]124.699074074069[/C][/ROW]
[ROW][C]51[/C][C]17910[/C][C]17684.4884259259[/C][C]17091.2916666667[/C][C]593.196759259259[/C][C]225.511574074073[/C][/ROW]
[ROW][C]52[/C][C]16961[/C][C]16999.4814814815[/C][C]17174.625[/C][C]-175.143518518519[/C][C]-38.4814814814818[/C][/ROW]
[ROW][C]53[/C][C]17480[/C][C]17626.1134259259[/C][C]17256.7083333333[/C][C]369.405092592592[/C][C]-146.113425925923[/C][/ROW]
[ROW][C]54[/C][C]17049[/C][C]17039.412037037[/C][C]17346[/C][C]-306.587962962964[/C][C]9.5879629629635[/C][/ROW]
[ROW][C]55[/C][C]16879[/C][C]17080.2939814815[/C][C]17439.4166666667[/C][C]-359.122685185186[/C][C]-201.293981481478[/C][/ROW]
[ROW][C]56[/C][C]17473[/C][C]17443.7939814815[/C][C]17524[/C][C]-80.2060185185185[/C][C]29.2060185185182[/C][/ROW]
[ROW][C]57[/C][C]16998[/C][C]16842.0509259259[/C][C]17609.75[/C][C]-767.699074074074[/C][C]155.949074074073[/C][/ROW]
[ROW][C]58[/C][C]17307[/C][C]17589.3912037037[/C][C]17692.875[/C][C]-103.483796296296[/C][C]-282.391203703704[/C][/ROW]
[ROW][C]59[/C][C]17418[/C][C]17388.8078703704[/C][C]17795.5[/C][C]-406.692129629629[/C][C]29.1921296296277[/C][/ROW]
[ROW][C]60[/C][C]20169[/C][C]20008.4259259259[/C][C]17924.375[/C][C]2084.05092592593[/C][C]160.574074074073[/C][/ROW]
[ROW][C]61[/C][C]17871[/C][C]17992.5648148148[/C][C]18034.9583333333[/C][C]-42.3935185185186[/C][C]-121.564814814814[/C][/ROW]
[ROW][C]62[/C][C]17226[/C][C]17337.0092592593[/C][C]18142.3333333333[/C][C]-805.324074074074[/C][C]-111.009259259259[/C][/ROW]
[ROW][C]63[/C][C]19062[/C][C]18840.7384259259[/C][C]18247.5416666667[/C][C]593.196759259259[/C][C]221.261574074077[/C][/ROW]
[ROW][C]64[/C][C]17804[/C][C]18184.6064814815[/C][C]18359.75[/C][C]-175.143518518519[/C][C]-380.606481481478[/C][/ROW]
[ROW][C]65[/C][C]19100[/C][C]18855.6550925926[/C][C]18486.25[/C][C]369.405092592592[/C][C]244.344907407412[/C][/ROW]
[ROW][C]66[/C][C]18522[/C][C]18286.5787037037[/C][C]18593.1666666667[/C][C]-306.587962962964[/C][C]235.421296296299[/C][/ROW]
[ROW][C]67[/C][C]18060[/C][C]18349.4606481481[/C][C]18708.5833333333[/C][C]-359.122685185186[/C][C]-289.460648148146[/C][/ROW]
[ROW][C]68[/C][C]18869[/C][C]18749.2106481481[/C][C]18829.4166666667[/C][C]-80.2060185185185[/C][C]119.789351851854[/C][/ROW]
[ROW][C]69[/C][C]18127[/C][C]18162.3842592593[/C][C]18930.0833333333[/C][C]-767.699074074074[/C][C]-35.3842592592628[/C][/ROW]
[ROW][C]70[/C][C]18871[/C][C]18936.099537037[/C][C]19039.5833333333[/C][C]-103.483796296296[/C][C]-65.0995370370365[/C][/ROW]
[ROW][C]71[/C][C]18890[/C][C]18739.224537037[/C][C]19145.9166666667[/C][C]-406.692129629629[/C][C]150.775462962964[/C][/ROW]
[ROW][C]72[/C][C]21263[/C][C]21313.8842592593[/C][C]19229.8333333333[/C][C]2084.05092592593[/C][C]-50.8842592592591[/C][/ROW]
[ROW][C]73[/C][C]19547[/C][C]19281.3148148148[/C][C]19323.7083333333[/C][C]-42.3935185185186[/C][C]265.685185185186[/C][/ROW]
[ROW][C]74[/C][C]18450[/C][C]18622.7175925926[/C][C]19428.0416666667[/C][C]-805.324074074074[/C][C]-172.717592592588[/C][/ROW]
[ROW][C]75[/C][C]20254[/C][C]20090.9884259259[/C][C]19497.7916666667[/C][C]593.196759259259[/C][C]163.011574074073[/C][/ROW]
[ROW][C]76[/C][C]19240[/C][C]19390.6481481481[/C][C]19565.7916666667[/C][C]-175.143518518519[/C][C]-150.64814814815[/C][/ROW]
[ROW][C]77[/C][C]20216[/C][C]20007.1134259259[/C][C]19637.7083333333[/C][C]369.405092592592[/C][C]208.886574074073[/C][/ROW]
[ROW][C]78[/C][C]19420[/C][C]19386.412037037[/C][C]19693[/C][C]-306.587962962964[/C][C]33.5879629629635[/C][/ROW]
[ROW][C]79[/C][C]19415[/C][C]NA[/C][C]NA[/C][C]-359.122685185186[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]20018[/C][C]NA[/C][C]NA[/C][C]-80.2060185185185[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]18652[/C][C]NA[/C][C]NA[/C][C]-767.699074074074[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]19978[/C][C]NA[/C][C]NA[/C][C]-103.483796296296[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]19509[/C][C]NA[/C][C]NA[/C][C]-406.692129629629[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]21971[/C][C]NA[/C][C]NA[/C][C]2084.05092592593[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=148743&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=148743&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
113328NANA-42.3935185185186NA
212873NANA-805.324074074074NA
314000NANA593.196759259259NA
413477NANA-175.143518518519NA
514237NANA369.405092592592NA
613674NANA-306.587962962964NA
71352913578.835648148113937.9583333333-359.122685185186-49.835648148146
81405813953.293981481514033.5-80.2060185185185104.70601851852
91297513357.259259259314124.9583333333-767.699074074074-382.259259259257
101432614124.141203703714227.625-103.483796296296201.858796296297
111400813928.59953703714335.2916666667-406.69212962962979.4004629629635
121619316500.300925925914416.252084.05092592593-307.300925925927
131448314462.898148148114505.2916666667-42.393518518518620.1018518518504
141401113799.425925925914604.75-805.324074074074211.574074074073
151505715301.405092592614708.2083333333593.196759259259-244.405092592591
161488414635.064814814814810.2083333333-175.143518518519248.935185185186
171541415259.238425925914889.8333333333369.405092592592154.761574074075
181444014663.66203703714970.25-306.587962962964-223.662037037036
191490014696.335648148115055.4583333333-359.122685185186203.66435185185
201507415050.210648148115130.4166666667-80.206018518518523.7893518518522
211444214426.675925925915194.375-767.69907407407415.3240740740766
221530715158.391203703715261.875-103.483796296296148.608796296297
231493814920.807870370415327.5-406.69212962962917.1921296296296
241719317485.800925925915401.752084.05092592593-292.800925925925
251552815448.189814814815490.5833333333-42.393518518518679.8101851851843
261476514768.384259259315573.7083333333-805.324074074074-3.38425925926094
271583816256.863425925915663.6666666667593.196759259259-418.863425925925
281572315589.898148148115765.0416666667-175.143518518519133.101851851852
291615016214.905092592615845.5369.405092592592-64.905092592593
301548615641.078703703715947.6666666667-306.587962962964-155.078703703704
311598615692.377314814816051.5-359.122685185186293.622685185186
321598316040.418981481516120.625-80.2060185185185-57.4189814814836
331569215444.425925925916212.125-767.699074074074247.574074074075
341649016197.641203703716301.125-103.483796296296292.358796296297
351568615943.557870370416350.25-406.692129629629-257.557870370367
361889718486.675925925916402.6252084.05092592593410.324074074077
371631616409.939814814816452.3333333333-42.3935185185186-93.9398148148102
381563615675.050925925916480.375-805.324074074074-39.0509259259234
391716317099.405092592616506.2083333333593.19675925925963.5949074074124
401653416336.189814814816511.3333333333-175.143518518519197.810185185186
411651816904.863425925916535.4583333333369.405092592592-386.863425925925
421637516264.745370370416571.3333333333-306.587962962964110.254629629631
431629016236.585648148116595.7083333333-359.12268518518653.414351851854
441635216561.960648148116642.1666666667-80.2060185185185-209.960648148146
451594315934.092592592616701.7916666667-767.6990740740748.90740740740875
461636216647.22453703716750.7083333333-103.483796296296-285.224537037036
471639316401.891203703716808.5833333333-406.692129629629-8.89120370370438
481905118960.800925925916876.752084.0509259259390.199074074073
491674716886.981481481516929.375-42.3935185185186-139.981481481482
501632016195.300925925917000.625-805.324074074074124.699074074069
511791017684.488425925917091.2916666667593.196759259259225.511574074073
521696116999.481481481517174.625-175.143518518519-38.4814814814818
531748017626.113425925917256.7083333333369.405092592592-146.113425925923
541704917039.41203703717346-306.5879629629649.5879629629635
551687917080.293981481517439.4166666667-359.122685185186-201.293981481478
561747317443.793981481517524-80.206018518518529.2060185185182
571699816842.050925925917609.75-767.699074074074155.949074074073
581730717589.391203703717692.875-103.483796296296-282.391203703704
591741817388.807870370417795.5-406.69212962962929.1921296296277
602016920008.425925925917924.3752084.05092592593160.574074074073
611787117992.564814814818034.9583333333-42.3935185185186-121.564814814814
621722617337.009259259318142.3333333333-805.324074074074-111.009259259259
631906218840.738425925918247.5416666667593.196759259259221.261574074077
641780418184.606481481518359.75-175.143518518519-380.606481481478
651910018855.655092592618486.25369.405092592592244.344907407412
661852218286.578703703718593.1666666667-306.587962962964235.421296296299
671806018349.460648148118708.5833333333-359.122685185186-289.460648148146
681886918749.210648148118829.4166666667-80.2060185185185119.789351851854
691812718162.384259259318930.0833333333-767.699074074074-35.3842592592628
701887118936.09953703719039.5833333333-103.483796296296-65.0995370370365
711889018739.22453703719145.9166666667-406.692129629629150.775462962964
722126321313.884259259319229.83333333332084.05092592593-50.8842592592591
731954719281.314814814819323.7083333333-42.3935185185186265.685185185186
741845018622.717592592619428.0416666667-805.324074074074-172.717592592588
752025420090.988425925919497.7916666667593.196759259259163.011574074073
761924019390.648148148119565.7916666667-175.143518518519-150.64814814815
772021620007.113425925919637.7083333333369.405092592592208.886574074073
781942019386.41203703719693-306.58796296296433.5879629629635
7919415NANA-359.122685185186NA
8020018NANA-80.2060185185185NA
8118652NANA-767.699074074074NA
8219978NANA-103.483796296296NA
8319509NANA-406.692129629629NA
8421971NANA2084.05092592593NA



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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')