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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 06 Dec 2012 13:42:10 -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/2012/Dec/06/t13548193941y5eyq599c83mst.htm/, Retrieved Fri, 29 Mar 2024 07:46:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197209, Retrieved Fri, 29 Mar 2024 07:46:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Ontvangsten geïnd...] [2012-10-07 17:57:08] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP   [Central Tendency] [Centrummaten ontv...] [2012-10-11 15:49:27] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- R  D    [Central Tendency] [Centrummaten ontv...] [2012-10-11 15:56:24] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP       [Mean Plot] [Ontvangsten schat...] [2012-10-18 14:12:08] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP         [(Partial) Autocorrelation Function] [schatkist autocor...] [2012-11-12 11:07:31] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP           [Blocked Bootstrap Plot - Central Tendency] [density plot rek ...] [2012-11-22 19:31:20] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- R P             [Blocked Bootstrap Plot - Central Tendency] [density plot rek ...] [2012-11-22 19:33:45] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
-   P               [Blocked Bootstrap Plot - Central Tendency] [density plot rek ...] [2012-11-22 19:35:27] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
- RMP                   [Classical Decomposition] [Classical Deompos...] [2012-12-06 18:42:10] [d41d8cd98f00b204e9800998ecf8427e] [Current]
- R P                     [Classical Decomposition] [Classical Deompos...] [2012-12-06 18:44:34] [74be16979710d4c4e7c6647856088456]
- RMP                       [Exponential Smoothing] [Exponential Smoot...] [2013-01-11 16:16:59] [7e0b1fc7e94581fb4f84255f8aa2fbc5]
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Dataseries X:
6848
5772
5251
11232
5908
6812
9962
6155
5673
7985
5780
11999
6973
5817
5844
11178
5533
6870
9521
5363
6031
9245
5621
11802
8364
6286
5071
10773
5821
7794
10636
6405
5811
8981
6228
11950
7523
6067
4825
12162
6989
8012
10893
6647
5938
9005
6262
12022
7683
6004
4724
10343
6604
7241
9331
6418
7094
10340
6814
12003
7481
5452
6380
11425
5905
8536
10785
6672
7293
9809
5658
12364
8078
5269
7787
11729
6236
8576
11216
6814
6019
9351
5464
12518




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197209&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197209&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197209&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
16848NANA-217.467592592593NA
25772NANA-2098.58564814815NA
35251NANA-2149.56481481481NA
411232NANA3335.0462962963NA
55908NANA-1759.24537037037NA
66812NANA-103.821759259259NA
799629821.601851851857453.291666666672368.31018518519140.398148148148
861555912.303240740747460.375-1548.07175925926242.69675925926
956735954.768518518527486.95833333333-1532.18981481482-281.768518518519
1079858876.997685185197509.416666666671367.58101851852-891.997685185185
1157805686.393518518527491.54166666667-1805.1481481481593.6064814814808
121199911621.49074074077478.333333333334143.15740740741377.509259259259
1369737244.907407407417462.375-217.467592592593-271.907407407408
1458175312.414351851857411-2098.58564814815504.585648148148
1558445243.351851851857392.91666666667-2149.56481481481600.648148148148
161117810795.37962962967460.333333333333335.0462962963382.62037037037
1755335746.962962962967506.20833333333-1759.24537037037-213.962962962963
1868707387.553240740747491.375-103.821759259259-517.55324074074
1995219909.435185185197541.1252368.31018518519-388.435185185186
2053636070.553240740747618.625-1548.07175925926-707.553240740741
2160316073.768518518527605.95833333333-1532.18981481482-42.7685185185182
2292458924.456018518527556.8751367.58101851852320.543981481482
2356215746.851851851857552-1805.14814814815-125.851851851852
241180211745.65740740747602.54143.1574074074156.3425925925922
2583647469.990740740747687.45833333333-217.467592592593894.00925925926
2662865678.747685185187777.33333333333-2098.58564814815607.252314814815
2750715662.018518518527811.58333333333-2149.56481481481-591.018518518519
281077311126.4629629637791.416666666673335.0462962963-353.462962962964
2958216046.462962962967805.70833333333-1759.24537037037-225.462962962962
3077947733.344907407417837.16666666667-103.82175925925960.655092592594
311063610176.60185185197808.291666666672368.31018518519459.398148148149
3264056216.053240740747764.125-1548.07175925926188.94675925926
3358116212.560185185187744.75-1532.18981481482-401.560185185184
3489819159.956018518527792.3751367.58101851852-178.956018518517
3562286093.768518518527898.91666666667-1805.14814814815134.231481481482
361195012099.82407407417956.666666666674143.15740740741-149.824074074074
3775237758.990740740747976.45833333333-217.467592592593-235.990740740741
3860675898.664351851857997.25-2098.58564814815168.335648148148
3948255863.060185185198012.625-2149.56481481481-1038.06018518519
401216211353.9629629638018.916666666673335.0462962963808.037037037037
4169896262.087962962968021.33333333333-1759.24537037037726.912037037038
4280127921.928240740748025.75-103.82175925925990.0717592592591
431089310403.72685185198035.416666666672368.31018518519489.273148148148
4466476491.386574074078039.45833333333-1548.07175925926155.613425925925
4559386500.435185185198032.625-1532.18981481482-562.435185185186
4690059320.206018518527952.6251367.58101851852-315.206018518519
4762626055.643518518527860.79166666667-1805.14814814815206.356481481482
481202211955.78240740747812.6254143.1574074074166.2175925925931
4976837497.949074074077715.41666666667-217.467592592593185.050925925927
5060045542.206018518527640.79166666667-2098.58564814815461.793981481483
5147245529.851851851857679.41666666667-2149.56481481481-805.851851851851
521034311118.25462962967783.208333333333335.0462962963-775.25462962963
5366046102.587962962967861.83333333333-1759.24537037037501.412037037036
5472417780.219907407417884.04166666667-103.821759259259-539.219907407408
55933110243.14351851857874.833333333332368.31018518519-912.143518518519
5664186295.344907407417843.41666666667-1548.07175925926122.655092592592
5770946357.226851851857889.41666666667-1532.18981481482736.77314814815
58103409371.081018518528003.51367.58101851852968.918981481483
5968146214.310185185198019.45833333333-1805.14814814815599.689814814816
601200312187.44907407418044.291666666674143.15740740741-184.449074074073
6174817941.365740740748158.83333333333-217.467592592593-460.365740740741
6254526131.414351851858230-2098.58564814815-679.414351851852
6363806099.310185185198248.875-2149.56481481481280.689814814814
641142511570.0879629638235.041666666673335.0462962963-145.087962962964
6559056405.504629629638164.75-1759.24537037037-500.50462962963
6685368027.803240740748131.625-103.821759259259508.19675925926
671078510539.85185185198171.541666666672368.31018518519245.148148148149
6866726640.719907407418188.79166666667-1548.0717592592631.2800925925931
6972936707.601851851858239.79166666667-1532.18981481482585.39814814815
7098099678.664351851858311.083333333331367.58101851852130.33564814815
7156586532.393518518528337.54166666667-1805.14814814815-874.393518518517
721236412496.157407407483534143.15740740741-132.157407407407
7380788155.157407407418372.625-217.467592592593-77.1574074074069
7452696297.914351851858396.5-2098.58564814815-1028.91435185185
7577876199.768518518528349.33333333333-2149.564814814811587.23148148148
761172911612.2129629638277.166666666673335.0462962963116.787037037036
7762366490.754629629638250-1759.24537037037-254.75462962963
7885768144.511574074078248.33333333333-103.821759259259431.488425925925
7911216NANA2368.31018518519NA
806814NANA-1548.07175925926NA
816019NANA-1532.18981481482NA
829351NANA1367.58101851852NA
835464NANA-1805.14814814815NA
8412518NANA4143.15740740741NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 6848 & NA & NA & -217.467592592593 & NA \tabularnewline
2 & 5772 & NA & NA & -2098.58564814815 & NA \tabularnewline
3 & 5251 & NA & NA & -2149.56481481481 & NA \tabularnewline
4 & 11232 & NA & NA & 3335.0462962963 & NA \tabularnewline
5 & 5908 & NA & NA & -1759.24537037037 & NA \tabularnewline
6 & 6812 & NA & NA & -103.821759259259 & NA \tabularnewline
7 & 9962 & 9821.60185185185 & 7453.29166666667 & 2368.31018518519 & 140.398148148148 \tabularnewline
8 & 6155 & 5912.30324074074 & 7460.375 & -1548.07175925926 & 242.69675925926 \tabularnewline
9 & 5673 & 5954.76851851852 & 7486.95833333333 & -1532.18981481482 & -281.768518518519 \tabularnewline
10 & 7985 & 8876.99768518519 & 7509.41666666667 & 1367.58101851852 & -891.997685185185 \tabularnewline
11 & 5780 & 5686.39351851852 & 7491.54166666667 & -1805.14814814815 & 93.6064814814808 \tabularnewline
12 & 11999 & 11621.4907407407 & 7478.33333333333 & 4143.15740740741 & 377.509259259259 \tabularnewline
13 & 6973 & 7244.90740740741 & 7462.375 & -217.467592592593 & -271.907407407408 \tabularnewline
14 & 5817 & 5312.41435185185 & 7411 & -2098.58564814815 & 504.585648148148 \tabularnewline
15 & 5844 & 5243.35185185185 & 7392.91666666667 & -2149.56481481481 & 600.648148148148 \tabularnewline
16 & 11178 & 10795.3796296296 & 7460.33333333333 & 3335.0462962963 & 382.62037037037 \tabularnewline
17 & 5533 & 5746.96296296296 & 7506.20833333333 & -1759.24537037037 & -213.962962962963 \tabularnewline
18 & 6870 & 7387.55324074074 & 7491.375 & -103.821759259259 & -517.55324074074 \tabularnewline
19 & 9521 & 9909.43518518519 & 7541.125 & 2368.31018518519 & -388.435185185186 \tabularnewline
20 & 5363 & 6070.55324074074 & 7618.625 & -1548.07175925926 & -707.553240740741 \tabularnewline
21 & 6031 & 6073.76851851852 & 7605.95833333333 & -1532.18981481482 & -42.7685185185182 \tabularnewline
22 & 9245 & 8924.45601851852 & 7556.875 & 1367.58101851852 & 320.543981481482 \tabularnewline
23 & 5621 & 5746.85185185185 & 7552 & -1805.14814814815 & -125.851851851852 \tabularnewline
24 & 11802 & 11745.6574074074 & 7602.5 & 4143.15740740741 & 56.3425925925922 \tabularnewline
25 & 8364 & 7469.99074074074 & 7687.45833333333 & -217.467592592593 & 894.00925925926 \tabularnewline
26 & 6286 & 5678.74768518518 & 7777.33333333333 & -2098.58564814815 & 607.252314814815 \tabularnewline
27 & 5071 & 5662.01851851852 & 7811.58333333333 & -2149.56481481481 & -591.018518518519 \tabularnewline
28 & 10773 & 11126.462962963 & 7791.41666666667 & 3335.0462962963 & -353.462962962964 \tabularnewline
29 & 5821 & 6046.46296296296 & 7805.70833333333 & -1759.24537037037 & -225.462962962962 \tabularnewline
30 & 7794 & 7733.34490740741 & 7837.16666666667 & -103.821759259259 & 60.655092592594 \tabularnewline
31 & 10636 & 10176.6018518519 & 7808.29166666667 & 2368.31018518519 & 459.398148148149 \tabularnewline
32 & 6405 & 6216.05324074074 & 7764.125 & -1548.07175925926 & 188.94675925926 \tabularnewline
33 & 5811 & 6212.56018518518 & 7744.75 & -1532.18981481482 & -401.560185185184 \tabularnewline
34 & 8981 & 9159.95601851852 & 7792.375 & 1367.58101851852 & -178.956018518517 \tabularnewline
35 & 6228 & 6093.76851851852 & 7898.91666666667 & -1805.14814814815 & 134.231481481482 \tabularnewline
36 & 11950 & 12099.8240740741 & 7956.66666666667 & 4143.15740740741 & -149.824074074074 \tabularnewline
37 & 7523 & 7758.99074074074 & 7976.45833333333 & -217.467592592593 & -235.990740740741 \tabularnewline
38 & 6067 & 5898.66435185185 & 7997.25 & -2098.58564814815 & 168.335648148148 \tabularnewline
39 & 4825 & 5863.06018518519 & 8012.625 & -2149.56481481481 & -1038.06018518519 \tabularnewline
40 & 12162 & 11353.962962963 & 8018.91666666667 & 3335.0462962963 & 808.037037037037 \tabularnewline
41 & 6989 & 6262.08796296296 & 8021.33333333333 & -1759.24537037037 & 726.912037037038 \tabularnewline
42 & 8012 & 7921.92824074074 & 8025.75 & -103.821759259259 & 90.0717592592591 \tabularnewline
43 & 10893 & 10403.7268518519 & 8035.41666666667 & 2368.31018518519 & 489.273148148148 \tabularnewline
44 & 6647 & 6491.38657407407 & 8039.45833333333 & -1548.07175925926 & 155.613425925925 \tabularnewline
45 & 5938 & 6500.43518518519 & 8032.625 & -1532.18981481482 & -562.435185185186 \tabularnewline
46 & 9005 & 9320.20601851852 & 7952.625 & 1367.58101851852 & -315.206018518519 \tabularnewline
47 & 6262 & 6055.64351851852 & 7860.79166666667 & -1805.14814814815 & 206.356481481482 \tabularnewline
48 & 12022 & 11955.7824074074 & 7812.625 & 4143.15740740741 & 66.2175925925931 \tabularnewline
49 & 7683 & 7497.94907407407 & 7715.41666666667 & -217.467592592593 & 185.050925925927 \tabularnewline
50 & 6004 & 5542.20601851852 & 7640.79166666667 & -2098.58564814815 & 461.793981481483 \tabularnewline
51 & 4724 & 5529.85185185185 & 7679.41666666667 & -2149.56481481481 & -805.851851851851 \tabularnewline
52 & 10343 & 11118.2546296296 & 7783.20833333333 & 3335.0462962963 & -775.25462962963 \tabularnewline
53 & 6604 & 6102.58796296296 & 7861.83333333333 & -1759.24537037037 & 501.412037037036 \tabularnewline
54 & 7241 & 7780.21990740741 & 7884.04166666667 & -103.821759259259 & -539.219907407408 \tabularnewline
55 & 9331 & 10243.1435185185 & 7874.83333333333 & 2368.31018518519 & -912.143518518519 \tabularnewline
56 & 6418 & 6295.34490740741 & 7843.41666666667 & -1548.07175925926 & 122.655092592592 \tabularnewline
57 & 7094 & 6357.22685185185 & 7889.41666666667 & -1532.18981481482 & 736.77314814815 \tabularnewline
58 & 10340 & 9371.08101851852 & 8003.5 & 1367.58101851852 & 968.918981481483 \tabularnewline
59 & 6814 & 6214.31018518519 & 8019.45833333333 & -1805.14814814815 & 599.689814814816 \tabularnewline
60 & 12003 & 12187.4490740741 & 8044.29166666667 & 4143.15740740741 & -184.449074074073 \tabularnewline
61 & 7481 & 7941.36574074074 & 8158.83333333333 & -217.467592592593 & -460.365740740741 \tabularnewline
62 & 5452 & 6131.41435185185 & 8230 & -2098.58564814815 & -679.414351851852 \tabularnewline
63 & 6380 & 6099.31018518519 & 8248.875 & -2149.56481481481 & 280.689814814814 \tabularnewline
64 & 11425 & 11570.087962963 & 8235.04166666667 & 3335.0462962963 & -145.087962962964 \tabularnewline
65 & 5905 & 6405.50462962963 & 8164.75 & -1759.24537037037 & -500.50462962963 \tabularnewline
66 & 8536 & 8027.80324074074 & 8131.625 & -103.821759259259 & 508.19675925926 \tabularnewline
67 & 10785 & 10539.8518518519 & 8171.54166666667 & 2368.31018518519 & 245.148148148149 \tabularnewline
68 & 6672 & 6640.71990740741 & 8188.79166666667 & -1548.07175925926 & 31.2800925925931 \tabularnewline
69 & 7293 & 6707.60185185185 & 8239.79166666667 & -1532.18981481482 & 585.39814814815 \tabularnewline
70 & 9809 & 9678.66435185185 & 8311.08333333333 & 1367.58101851852 & 130.33564814815 \tabularnewline
71 & 5658 & 6532.39351851852 & 8337.54166666667 & -1805.14814814815 & -874.393518518517 \tabularnewline
72 & 12364 & 12496.1574074074 & 8353 & 4143.15740740741 & -132.157407407407 \tabularnewline
73 & 8078 & 8155.15740740741 & 8372.625 & -217.467592592593 & -77.1574074074069 \tabularnewline
74 & 5269 & 6297.91435185185 & 8396.5 & -2098.58564814815 & -1028.91435185185 \tabularnewline
75 & 7787 & 6199.76851851852 & 8349.33333333333 & -2149.56481481481 & 1587.23148148148 \tabularnewline
76 & 11729 & 11612.212962963 & 8277.16666666667 & 3335.0462962963 & 116.787037037036 \tabularnewline
77 & 6236 & 6490.75462962963 & 8250 & -1759.24537037037 & -254.75462962963 \tabularnewline
78 & 8576 & 8144.51157407407 & 8248.33333333333 & -103.821759259259 & 431.488425925925 \tabularnewline
79 & 11216 & NA & NA & 2368.31018518519 & NA \tabularnewline
80 & 6814 & NA & NA & -1548.07175925926 & NA \tabularnewline
81 & 6019 & NA & NA & -1532.18981481482 & NA \tabularnewline
82 & 9351 & NA & NA & 1367.58101851852 & NA \tabularnewline
83 & 5464 & NA & NA & -1805.14814814815 & NA \tabularnewline
84 & 12518 & NA & NA & 4143.15740740741 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197209&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]6848[/C][C]NA[/C][C]NA[/C][C]-217.467592592593[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]5772[/C][C]NA[/C][C]NA[/C][C]-2098.58564814815[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]5251[/C][C]NA[/C][C]NA[/C][C]-2149.56481481481[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]11232[/C][C]NA[/C][C]NA[/C][C]3335.0462962963[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]5908[/C][C]NA[/C][C]NA[/C][C]-1759.24537037037[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]6812[/C][C]NA[/C][C]NA[/C][C]-103.821759259259[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9962[/C][C]9821.60185185185[/C][C]7453.29166666667[/C][C]2368.31018518519[/C][C]140.398148148148[/C][/ROW]
[ROW][C]8[/C][C]6155[/C][C]5912.30324074074[/C][C]7460.375[/C][C]-1548.07175925926[/C][C]242.69675925926[/C][/ROW]
[ROW][C]9[/C][C]5673[/C][C]5954.76851851852[/C][C]7486.95833333333[/C][C]-1532.18981481482[/C][C]-281.768518518519[/C][/ROW]
[ROW][C]10[/C][C]7985[/C][C]8876.99768518519[/C][C]7509.41666666667[/C][C]1367.58101851852[/C][C]-891.997685185185[/C][/ROW]
[ROW][C]11[/C][C]5780[/C][C]5686.39351851852[/C][C]7491.54166666667[/C][C]-1805.14814814815[/C][C]93.6064814814808[/C][/ROW]
[ROW][C]12[/C][C]11999[/C][C]11621.4907407407[/C][C]7478.33333333333[/C][C]4143.15740740741[/C][C]377.509259259259[/C][/ROW]
[ROW][C]13[/C][C]6973[/C][C]7244.90740740741[/C][C]7462.375[/C][C]-217.467592592593[/C][C]-271.907407407408[/C][/ROW]
[ROW][C]14[/C][C]5817[/C][C]5312.41435185185[/C][C]7411[/C][C]-2098.58564814815[/C][C]504.585648148148[/C][/ROW]
[ROW][C]15[/C][C]5844[/C][C]5243.35185185185[/C][C]7392.91666666667[/C][C]-2149.56481481481[/C][C]600.648148148148[/C][/ROW]
[ROW][C]16[/C][C]11178[/C][C]10795.3796296296[/C][C]7460.33333333333[/C][C]3335.0462962963[/C][C]382.62037037037[/C][/ROW]
[ROW][C]17[/C][C]5533[/C][C]5746.96296296296[/C][C]7506.20833333333[/C][C]-1759.24537037037[/C][C]-213.962962962963[/C][/ROW]
[ROW][C]18[/C][C]6870[/C][C]7387.55324074074[/C][C]7491.375[/C][C]-103.821759259259[/C][C]-517.55324074074[/C][/ROW]
[ROW][C]19[/C][C]9521[/C][C]9909.43518518519[/C][C]7541.125[/C][C]2368.31018518519[/C][C]-388.435185185186[/C][/ROW]
[ROW][C]20[/C][C]5363[/C][C]6070.55324074074[/C][C]7618.625[/C][C]-1548.07175925926[/C][C]-707.553240740741[/C][/ROW]
[ROW][C]21[/C][C]6031[/C][C]6073.76851851852[/C][C]7605.95833333333[/C][C]-1532.18981481482[/C][C]-42.7685185185182[/C][/ROW]
[ROW][C]22[/C][C]9245[/C][C]8924.45601851852[/C][C]7556.875[/C][C]1367.58101851852[/C][C]320.543981481482[/C][/ROW]
[ROW][C]23[/C][C]5621[/C][C]5746.85185185185[/C][C]7552[/C][C]-1805.14814814815[/C][C]-125.851851851852[/C][/ROW]
[ROW][C]24[/C][C]11802[/C][C]11745.6574074074[/C][C]7602.5[/C][C]4143.15740740741[/C][C]56.3425925925922[/C][/ROW]
[ROW][C]25[/C][C]8364[/C][C]7469.99074074074[/C][C]7687.45833333333[/C][C]-217.467592592593[/C][C]894.00925925926[/C][/ROW]
[ROW][C]26[/C][C]6286[/C][C]5678.74768518518[/C][C]7777.33333333333[/C][C]-2098.58564814815[/C][C]607.252314814815[/C][/ROW]
[ROW][C]27[/C][C]5071[/C][C]5662.01851851852[/C][C]7811.58333333333[/C][C]-2149.56481481481[/C][C]-591.018518518519[/C][/ROW]
[ROW][C]28[/C][C]10773[/C][C]11126.462962963[/C][C]7791.41666666667[/C][C]3335.0462962963[/C][C]-353.462962962964[/C][/ROW]
[ROW][C]29[/C][C]5821[/C][C]6046.46296296296[/C][C]7805.70833333333[/C][C]-1759.24537037037[/C][C]-225.462962962962[/C][/ROW]
[ROW][C]30[/C][C]7794[/C][C]7733.34490740741[/C][C]7837.16666666667[/C][C]-103.821759259259[/C][C]60.655092592594[/C][/ROW]
[ROW][C]31[/C][C]10636[/C][C]10176.6018518519[/C][C]7808.29166666667[/C][C]2368.31018518519[/C][C]459.398148148149[/C][/ROW]
[ROW][C]32[/C][C]6405[/C][C]6216.05324074074[/C][C]7764.125[/C][C]-1548.07175925926[/C][C]188.94675925926[/C][/ROW]
[ROW][C]33[/C][C]5811[/C][C]6212.56018518518[/C][C]7744.75[/C][C]-1532.18981481482[/C][C]-401.560185185184[/C][/ROW]
[ROW][C]34[/C][C]8981[/C][C]9159.95601851852[/C][C]7792.375[/C][C]1367.58101851852[/C][C]-178.956018518517[/C][/ROW]
[ROW][C]35[/C][C]6228[/C][C]6093.76851851852[/C][C]7898.91666666667[/C][C]-1805.14814814815[/C][C]134.231481481482[/C][/ROW]
[ROW][C]36[/C][C]11950[/C][C]12099.8240740741[/C][C]7956.66666666667[/C][C]4143.15740740741[/C][C]-149.824074074074[/C][/ROW]
[ROW][C]37[/C][C]7523[/C][C]7758.99074074074[/C][C]7976.45833333333[/C][C]-217.467592592593[/C][C]-235.990740740741[/C][/ROW]
[ROW][C]38[/C][C]6067[/C][C]5898.66435185185[/C][C]7997.25[/C][C]-2098.58564814815[/C][C]168.335648148148[/C][/ROW]
[ROW][C]39[/C][C]4825[/C][C]5863.06018518519[/C][C]8012.625[/C][C]-2149.56481481481[/C][C]-1038.06018518519[/C][/ROW]
[ROW][C]40[/C][C]12162[/C][C]11353.962962963[/C][C]8018.91666666667[/C][C]3335.0462962963[/C][C]808.037037037037[/C][/ROW]
[ROW][C]41[/C][C]6989[/C][C]6262.08796296296[/C][C]8021.33333333333[/C][C]-1759.24537037037[/C][C]726.912037037038[/C][/ROW]
[ROW][C]42[/C][C]8012[/C][C]7921.92824074074[/C][C]8025.75[/C][C]-103.821759259259[/C][C]90.0717592592591[/C][/ROW]
[ROW][C]43[/C][C]10893[/C][C]10403.7268518519[/C][C]8035.41666666667[/C][C]2368.31018518519[/C][C]489.273148148148[/C][/ROW]
[ROW][C]44[/C][C]6647[/C][C]6491.38657407407[/C][C]8039.45833333333[/C][C]-1548.07175925926[/C][C]155.613425925925[/C][/ROW]
[ROW][C]45[/C][C]5938[/C][C]6500.43518518519[/C][C]8032.625[/C][C]-1532.18981481482[/C][C]-562.435185185186[/C][/ROW]
[ROW][C]46[/C][C]9005[/C][C]9320.20601851852[/C][C]7952.625[/C][C]1367.58101851852[/C][C]-315.206018518519[/C][/ROW]
[ROW][C]47[/C][C]6262[/C][C]6055.64351851852[/C][C]7860.79166666667[/C][C]-1805.14814814815[/C][C]206.356481481482[/C][/ROW]
[ROW][C]48[/C][C]12022[/C][C]11955.7824074074[/C][C]7812.625[/C][C]4143.15740740741[/C][C]66.2175925925931[/C][/ROW]
[ROW][C]49[/C][C]7683[/C][C]7497.94907407407[/C][C]7715.41666666667[/C][C]-217.467592592593[/C][C]185.050925925927[/C][/ROW]
[ROW][C]50[/C][C]6004[/C][C]5542.20601851852[/C][C]7640.79166666667[/C][C]-2098.58564814815[/C][C]461.793981481483[/C][/ROW]
[ROW][C]51[/C][C]4724[/C][C]5529.85185185185[/C][C]7679.41666666667[/C][C]-2149.56481481481[/C][C]-805.851851851851[/C][/ROW]
[ROW][C]52[/C][C]10343[/C][C]11118.2546296296[/C][C]7783.20833333333[/C][C]3335.0462962963[/C][C]-775.25462962963[/C][/ROW]
[ROW][C]53[/C][C]6604[/C][C]6102.58796296296[/C][C]7861.83333333333[/C][C]-1759.24537037037[/C][C]501.412037037036[/C][/ROW]
[ROW][C]54[/C][C]7241[/C][C]7780.21990740741[/C][C]7884.04166666667[/C][C]-103.821759259259[/C][C]-539.219907407408[/C][/ROW]
[ROW][C]55[/C][C]9331[/C][C]10243.1435185185[/C][C]7874.83333333333[/C][C]2368.31018518519[/C][C]-912.143518518519[/C][/ROW]
[ROW][C]56[/C][C]6418[/C][C]6295.34490740741[/C][C]7843.41666666667[/C][C]-1548.07175925926[/C][C]122.655092592592[/C][/ROW]
[ROW][C]57[/C][C]7094[/C][C]6357.22685185185[/C][C]7889.41666666667[/C][C]-1532.18981481482[/C][C]736.77314814815[/C][/ROW]
[ROW][C]58[/C][C]10340[/C][C]9371.08101851852[/C][C]8003.5[/C][C]1367.58101851852[/C][C]968.918981481483[/C][/ROW]
[ROW][C]59[/C][C]6814[/C][C]6214.31018518519[/C][C]8019.45833333333[/C][C]-1805.14814814815[/C][C]599.689814814816[/C][/ROW]
[ROW][C]60[/C][C]12003[/C][C]12187.4490740741[/C][C]8044.29166666667[/C][C]4143.15740740741[/C][C]-184.449074074073[/C][/ROW]
[ROW][C]61[/C][C]7481[/C][C]7941.36574074074[/C][C]8158.83333333333[/C][C]-217.467592592593[/C][C]-460.365740740741[/C][/ROW]
[ROW][C]62[/C][C]5452[/C][C]6131.41435185185[/C][C]8230[/C][C]-2098.58564814815[/C][C]-679.414351851852[/C][/ROW]
[ROW][C]63[/C][C]6380[/C][C]6099.31018518519[/C][C]8248.875[/C][C]-2149.56481481481[/C][C]280.689814814814[/C][/ROW]
[ROW][C]64[/C][C]11425[/C][C]11570.087962963[/C][C]8235.04166666667[/C][C]3335.0462962963[/C][C]-145.087962962964[/C][/ROW]
[ROW][C]65[/C][C]5905[/C][C]6405.50462962963[/C][C]8164.75[/C][C]-1759.24537037037[/C][C]-500.50462962963[/C][/ROW]
[ROW][C]66[/C][C]8536[/C][C]8027.80324074074[/C][C]8131.625[/C][C]-103.821759259259[/C][C]508.19675925926[/C][/ROW]
[ROW][C]67[/C][C]10785[/C][C]10539.8518518519[/C][C]8171.54166666667[/C][C]2368.31018518519[/C][C]245.148148148149[/C][/ROW]
[ROW][C]68[/C][C]6672[/C][C]6640.71990740741[/C][C]8188.79166666667[/C][C]-1548.07175925926[/C][C]31.2800925925931[/C][/ROW]
[ROW][C]69[/C][C]7293[/C][C]6707.60185185185[/C][C]8239.79166666667[/C][C]-1532.18981481482[/C][C]585.39814814815[/C][/ROW]
[ROW][C]70[/C][C]9809[/C][C]9678.66435185185[/C][C]8311.08333333333[/C][C]1367.58101851852[/C][C]130.33564814815[/C][/ROW]
[ROW][C]71[/C][C]5658[/C][C]6532.39351851852[/C][C]8337.54166666667[/C][C]-1805.14814814815[/C][C]-874.393518518517[/C][/ROW]
[ROW][C]72[/C][C]12364[/C][C]12496.1574074074[/C][C]8353[/C][C]4143.15740740741[/C][C]-132.157407407407[/C][/ROW]
[ROW][C]73[/C][C]8078[/C][C]8155.15740740741[/C][C]8372.625[/C][C]-217.467592592593[/C][C]-77.1574074074069[/C][/ROW]
[ROW][C]74[/C][C]5269[/C][C]6297.91435185185[/C][C]8396.5[/C][C]-2098.58564814815[/C][C]-1028.91435185185[/C][/ROW]
[ROW][C]75[/C][C]7787[/C][C]6199.76851851852[/C][C]8349.33333333333[/C][C]-2149.56481481481[/C][C]1587.23148148148[/C][/ROW]
[ROW][C]76[/C][C]11729[/C][C]11612.212962963[/C][C]8277.16666666667[/C][C]3335.0462962963[/C][C]116.787037037036[/C][/ROW]
[ROW][C]77[/C][C]6236[/C][C]6490.75462962963[/C][C]8250[/C][C]-1759.24537037037[/C][C]-254.75462962963[/C][/ROW]
[ROW][C]78[/C][C]8576[/C][C]8144.51157407407[/C][C]8248.33333333333[/C][C]-103.821759259259[/C][C]431.488425925925[/C][/ROW]
[ROW][C]79[/C][C]11216[/C][C]NA[/C][C]NA[/C][C]2368.31018518519[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]6814[/C][C]NA[/C][C]NA[/C][C]-1548.07175925926[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]6019[/C][C]NA[/C][C]NA[/C][C]-1532.18981481482[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]9351[/C][C]NA[/C][C]NA[/C][C]1367.58101851852[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]5464[/C][C]NA[/C][C]NA[/C][C]-1805.14814814815[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]12518[/C][C]NA[/C][C]NA[/C][C]4143.15740740741[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197209&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197209&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
16848NANA-217.467592592593NA
25772NANA-2098.58564814815NA
35251NANA-2149.56481481481NA
411232NANA3335.0462962963NA
55908NANA-1759.24537037037NA
66812NANA-103.821759259259NA
799629821.601851851857453.291666666672368.31018518519140.398148148148
861555912.303240740747460.375-1548.07175925926242.69675925926
956735954.768518518527486.95833333333-1532.18981481482-281.768518518519
1079858876.997685185197509.416666666671367.58101851852-891.997685185185
1157805686.393518518527491.54166666667-1805.1481481481593.6064814814808
121199911621.49074074077478.333333333334143.15740740741377.509259259259
1369737244.907407407417462.375-217.467592592593-271.907407407408
1458175312.414351851857411-2098.58564814815504.585648148148
1558445243.351851851857392.91666666667-2149.56481481481600.648148148148
161117810795.37962962967460.333333333333335.0462962963382.62037037037
1755335746.962962962967506.20833333333-1759.24537037037-213.962962962963
1868707387.553240740747491.375-103.821759259259-517.55324074074
1995219909.435185185197541.1252368.31018518519-388.435185185186
2053636070.553240740747618.625-1548.07175925926-707.553240740741
2160316073.768518518527605.95833333333-1532.18981481482-42.7685185185182
2292458924.456018518527556.8751367.58101851852320.543981481482
2356215746.851851851857552-1805.14814814815-125.851851851852
241180211745.65740740747602.54143.1574074074156.3425925925922
2583647469.990740740747687.45833333333-217.467592592593894.00925925926
2662865678.747685185187777.33333333333-2098.58564814815607.252314814815
2750715662.018518518527811.58333333333-2149.56481481481-591.018518518519
281077311126.4629629637791.416666666673335.0462962963-353.462962962964
2958216046.462962962967805.70833333333-1759.24537037037-225.462962962962
3077947733.344907407417837.16666666667-103.82175925925960.655092592594
311063610176.60185185197808.291666666672368.31018518519459.398148148149
3264056216.053240740747764.125-1548.07175925926188.94675925926
3358116212.560185185187744.75-1532.18981481482-401.560185185184
3489819159.956018518527792.3751367.58101851852-178.956018518517
3562286093.768518518527898.91666666667-1805.14814814815134.231481481482
361195012099.82407407417956.666666666674143.15740740741-149.824074074074
3775237758.990740740747976.45833333333-217.467592592593-235.990740740741
3860675898.664351851857997.25-2098.58564814815168.335648148148
3948255863.060185185198012.625-2149.56481481481-1038.06018518519
401216211353.9629629638018.916666666673335.0462962963808.037037037037
4169896262.087962962968021.33333333333-1759.24537037037726.912037037038
4280127921.928240740748025.75-103.82175925925990.0717592592591
431089310403.72685185198035.416666666672368.31018518519489.273148148148
4466476491.386574074078039.45833333333-1548.07175925926155.613425925925
4559386500.435185185198032.625-1532.18981481482-562.435185185186
4690059320.206018518527952.6251367.58101851852-315.206018518519
4762626055.643518518527860.79166666667-1805.14814814815206.356481481482
481202211955.78240740747812.6254143.1574074074166.2175925925931
4976837497.949074074077715.41666666667-217.467592592593185.050925925927
5060045542.206018518527640.79166666667-2098.58564814815461.793981481483
5147245529.851851851857679.41666666667-2149.56481481481-805.851851851851
521034311118.25462962967783.208333333333335.0462962963-775.25462962963
5366046102.587962962967861.83333333333-1759.24537037037501.412037037036
5472417780.219907407417884.04166666667-103.821759259259-539.219907407408
55933110243.14351851857874.833333333332368.31018518519-912.143518518519
5664186295.344907407417843.41666666667-1548.07175925926122.655092592592
5770946357.226851851857889.41666666667-1532.18981481482736.77314814815
58103409371.081018518528003.51367.58101851852968.918981481483
5968146214.310185185198019.45833333333-1805.14814814815599.689814814816
601200312187.44907407418044.291666666674143.15740740741-184.449074074073
6174817941.365740740748158.83333333333-217.467592592593-460.365740740741
6254526131.414351851858230-2098.58564814815-679.414351851852
6363806099.310185185198248.875-2149.56481481481280.689814814814
641142511570.0879629638235.041666666673335.0462962963-145.087962962964
6559056405.504629629638164.75-1759.24537037037-500.50462962963
6685368027.803240740748131.625-103.821759259259508.19675925926
671078510539.85185185198171.541666666672368.31018518519245.148148148149
6866726640.719907407418188.79166666667-1548.0717592592631.2800925925931
6972936707.601851851858239.79166666667-1532.18981481482585.39814814815
7098099678.664351851858311.083333333331367.58101851852130.33564814815
7156586532.393518518528337.54166666667-1805.14814814815-874.393518518517
721236412496.157407407483534143.15740740741-132.157407407407
7380788155.157407407418372.625-217.467592592593-77.1574074074069
7452696297.914351851858396.5-2098.58564814815-1028.91435185185
7577876199.768518518528349.33333333333-2149.564814814811587.23148148148
761172911612.2129629638277.166666666673335.0462962963116.787037037036
7762366490.754629629638250-1759.24537037037-254.75462962963
7885768144.511574074078248.33333333333-103.821759259259431.488425925925
7911216NANA2368.31018518519NA
806814NANA-1548.07175925926NA
816019NANA-1532.18981481482NA
829351NANA1367.58101851852NA
835464NANA-1805.14814814815NA
8412518NANA4143.15740740741NA



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')