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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 computationSat, 18 Dec 2010 18:57:16 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/18/t1292698583sumjwp83mn6nh8m.htm/, Retrieved Tue, 30 Apr 2024 04:48:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112160, Retrieved Tue, 30 Apr 2024 04:48:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
-  M D  [Classical Decomposition] [Workshop 8, Class...] [2010-11-28 20:55:54] [d946de7cca328fbcf207448a112523ab]
- R  D    [Classical Decomposition] [Paper Decompositi...] [2010-12-18 18:53:33] [8081b8996d5947580de3eb171e82db4f]
-    D        [Classical Decomposition] [Paper Decompositi...] [2010-12-18 18:57:16] [4d0f7ea43b071af5c75b527ee1ef14c2] [Current]
-    D          [Classical Decomposition] [Paper Decompositi...] [2010-12-18 19:01:17] [8081b8996d5947580de3eb171e82db4f]
-    D            [Classical Decomposition] [Paper Decompositi...] [2010-12-18 19:04:54] [8081b8996d5947580de3eb171e82db4f]
-   P               [Classical Decomposition] [Decomposition - I...] [2010-12-22 08:38:18] [8081b8996d5947580de3eb171e82db4f]
-   P               [Classical Decomposition] [Decomposition - I...] [2010-12-22 08:38:18] [8081b8996d5947580de3eb171e82db4f]
-   P               [Classical Decomposition] [Decomposition - I...] [2010-12-22 08:38:18] [8081b8996d5947580de3eb171e82db4f]
-                   [Classical Decomposition] [Paper Decompositi...] [2010-12-22 08:56:07] [d946de7cca328fbcf207448a112523ab]
-                   [Classical Decomposition] [Paper Decompositi...] [2010-12-22 08:56:07] [d946de7cca328fbcf207448a112523ab]
- R  D              [Classical Decomposition] [] [2011-12-19 20:02:25] [58157dc6b621eed9dc2a8f45e356f037]
-   PD            [Classical Decomposition] [Decomposition - CPI] [2010-12-22 08:29:22] [8081b8996d5947580de3eb171e82db4f]
-   PD            [Classical Decomposition] [Decomposition - CPI] [2010-12-22 08:29:22] [8081b8996d5947580de3eb171e82db4f]
-    D            [Classical Decomposition] [Paper Decompositi...] [2010-12-22 08:52:36] [d946de7cca328fbcf207448a112523ab]
-                 [Classical Decomposition] [Paper Decompositi...] [2010-12-22 15:41:36] [3635fb7041b1998c5a1332cf9de22bce]
-   P           [Classical Decomposition] [Decomposition of ...] [2010-12-22 08:26:29] [8081b8996d5947580de3eb171e82db4f]
-               [Classical Decomposition] [Paper Decompositi...] [2010-12-22 08:48:30] [d946de7cca328fbcf207448a112523ab]
-               [Classical Decomposition] [Paper Decompositi...] [2010-12-22 08:48:30] [d946de7cca328fbcf207448a112523ab]
-               [Classical Decomposition] [Paper Decompositi...] [2010-12-22 15:39:39] [3635fb7041b1998c5a1332cf9de22bce]
- R  D            [Classical Decomposition] [] [2011-12-19 19:41:02] [58157dc6b621eed9dc2a8f45e356f037]
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Dataseries X:
21.454
23.899
24.939
23.580
24.562
24.696
23.785
23.812
21.917
19.713
19.282
18.788
21.453
24.482
27.474
27.264
27.349
30.632
29.429
30.084
26.290
24.379
23.335
21.346
21.106
24.514
28.353
30.805
31.348
34.556
33.855
34.787
32.529
29.998
29.257
28.155
30.466
35.704
39.327
39.351
42.234
43.630
43.722
43.121
37.985
37.135
34.646
33.026
35.087
38.846
42.013
43.908
42.868
44.423
44.167
43.636
44.382
42.142
43.452
36.912
42.413
45.344
44.873
47.510
49.554
47.369
45.998
48.140
48.441
44.928
40.454
38.661
37.246
36.843
36.424
37.594
38.144
38.737
34.560
36.080
33.508
35.462
33.374
32.110




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112160&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112160&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112160&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
121.454NANA-3.95605497685186NA
223.899NANA-1.12240914351852NA
324.939NANA0.833736689814813NA
423.58NANA1.97187557870370NA
524.562NANA2.60881307870370NA
624.696NANA3.72677141203704NA
723.78525.212396412037022.53554166666672.67685474537037-1.42739641203704
823.81225.474424189814822.55979166666672.91463252314815-1.66242418981481
921.91723.428695023148122.68970833333330.738986689814819-1.51169502314815
1019.71321.302576967592622.9488333333333-1.64625636574074-1.58957696759259
1119.28220.069063078703723.2184583333333-3.14939525462963-0.7870630787037
1218.78817.984361689814823.5819166666667-5.597554976851850.803638310185189
1321.45320.108361689814824.0644166666667-3.956054976851861.34463831018519
1424.48223.438507523148124.5609166666667-1.122409143518521.04349247685186
1527.47425.838195023148125.00445833333330.8337366898148131.63580497685185
1627.26427.352958912037025.38108333333331.97187557870370-0.0889589120370324
1727.34928.353188078703725.7443752.60881307870370-1.00418807870370
1830.63229.746604745370426.01983333333333.726771412037040.885395254629632
1929.42928.788813078703726.11195833333332.676854745370370.640186921296298
2030.08429.013465856481526.09883333333332.914632523148151.07053414351852
2126.2926.875778356481526.13679166666670.738986689814819-0.585778356481484
2224.37924.674701967592626.3209583333333-1.64625636574074-0.295701967592592
2323.33523.485729745370426.635125-3.14939525462963-0.150729745370366
2421.34621.367695023148126.96525-5.59755497685185-0.0216950231481476
2521.10623.357111689814827.3131666666667-3.95605497685186-2.25111168981481
2624.51426.571132523148127.6935416666667-1.12240914351852-2.05713252314815
2728.35328.983195023148128.14945833333330.833736689814813-0.630195023148147
2830.80530.615417245370428.64354166666671.971875578703700.189582754629630
2931.34831.733229745370429.12441666666672.60881307870370-0.385229745370374
3034.55633.381646412037029.6548753.726771412037041.17435358796296
3133.85533.005438078703730.32858333333332.676854745370370.849561921296299
3234.78734.099465856481531.18483333333332.914632523148150.68753414351852
3332.52932.847320023148132.10833333333330.738986689814819-0.318320023148143
3429.99831.275410300925932.9216666666667-1.64625636574074-1.27741030092592
3529.25730.581938078703733.7313333333333-3.14939525462963-1.32493807870371
3628.15528.965445023148234.563-5.59755497685185-0.810445023148148
3730.46631.396153356481535.3522083333333-3.95605497685186-0.930153356481483
3835.70434.988174189814836.1105833333333-1.122409143518520.715825810185187
3939.32737.518903356481536.68516666666670.8337366898148131.80809664351852
4039.35139.181750578703737.2098751.971875578703700.169249421296300
4142.23440.340604745370437.73179166666672.608813078703701.89339525462963
4243.6341.886063078703738.15929166666673.726771412037041.74393692129630
4343.72241.23164641203738.55479166666672.676854745370372.49035358796296
4443.12141.792882523148238.878252.914632523148151.32811747685185
4537.98539.860070023148139.12108333333330.738986689814819-1.87507002314814
4637.13537.776618634259339.422875-1.64625636574074-0.64161863425926
4734.64636.489771412037039.6391666666667-3.14939525462963-1.84377141203703
4833.02634.101070023148239.698625-5.59755497685185-1.07507002314815
4935.08735.794153356481539.7502083333333-3.95605497685186-0.707153356481484
5038.84638.667799189814839.7902083333333-1.122409143518520.178200810185182
5142.01340.911945023148140.07820833333330.8337366898148131.10105497685185
5243.90842.525250578703740.5533751.971875578703701.38274942129630
5342.86843.737729745370441.12891666666672.60881307870370-0.869729745370371
5444.42345.384521412037041.657753.72677141203704-0.961521412037037
5544.16744.801771412037042.12491666666672.67685474537037-0.63477141203704
5643.63645.615549189814842.70091666666672.91463252314815-1.97954918981481
5744.38243.829820023148143.09083333333330.7389866898148190.552179976851853
5842.14241.713826967592643.3600833333333-1.646256365740740.428173032407408
5943.45240.639354745370443.78875-3.149395254629632.81264525462963
6036.91238.592528356481544.1900833333333-5.59755497685185-1.68052835648147
6142.41340.433070023148144.389125-3.956054976851861.97992997685185
6245.34443.530674189814844.6530833333333-1.122409143518521.81332581018518
6344.87345.843611689814845.0098750.833736689814813-0.970611689814817
6447.5147.26695891203745.29508333333331.971875578703700.243041087962965
6549.55447.895063078703745.286252.608813078703701.65893692129631
6647.36948.960979745370445.23420833333333.72677141203704-1.59197974537037
6745.99847.76864641203745.09179166666672.67685474537037-1.77064641203704
6848.1447.436924189814844.52229166666672.914632523148150.703075810185183
6948.44144.555028356481543.81604166666670.7389866898148193.88597164351852
7044.92841.404576967592643.0508333333333-1.646256365740743.52342303240741
7140.45439.012854745370442.16225-3.149395254629631.44114525462963
7238.66135.729611689814841.3271666666667-5.597554976851852.93138831018519
7337.24636.534861689814840.4909166666667-3.956054976851860.711138310185177
7436.84338.389424189814839.5118333333333-1.12240914351852-1.54642418981481
7536.42439.220861689814838.3871250.833736689814813-2.79686168981481
7637.59439.342375578703737.37051.97187557870370-1.74837557870371
7738.14439.28989641203736.68108333333332.60881307870370-1.14589641203705
7838.73739.83989641203736.1131253.72677141203704-1.10289641203704
7934.56NANA2.67685474537037NA
8036.08NANA2.91463252314815NA
8133.508NANA0.738986689814819NA
8235.462NANA-1.64625636574074NA
8333.374NANA-3.14939525462963NA
8432.11NANA-5.59755497685185NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 21.454 & NA & NA & -3.95605497685186 & NA \tabularnewline
2 & 23.899 & NA & NA & -1.12240914351852 & NA \tabularnewline
3 & 24.939 & NA & NA & 0.833736689814813 & NA \tabularnewline
4 & 23.58 & NA & NA & 1.97187557870370 & NA \tabularnewline
5 & 24.562 & NA & NA & 2.60881307870370 & NA \tabularnewline
6 & 24.696 & NA & NA & 3.72677141203704 & NA \tabularnewline
7 & 23.785 & 25.2123964120370 & 22.5355416666667 & 2.67685474537037 & -1.42739641203704 \tabularnewline
8 & 23.812 & 25.4744241898148 & 22.5597916666667 & 2.91463252314815 & -1.66242418981481 \tabularnewline
9 & 21.917 & 23.4286950231481 & 22.6897083333333 & 0.738986689814819 & -1.51169502314815 \tabularnewline
10 & 19.713 & 21.3025769675926 & 22.9488333333333 & -1.64625636574074 & -1.58957696759259 \tabularnewline
11 & 19.282 & 20.0690630787037 & 23.2184583333333 & -3.14939525462963 & -0.7870630787037 \tabularnewline
12 & 18.788 & 17.9843616898148 & 23.5819166666667 & -5.59755497685185 & 0.803638310185189 \tabularnewline
13 & 21.453 & 20.1083616898148 & 24.0644166666667 & -3.95605497685186 & 1.34463831018519 \tabularnewline
14 & 24.482 & 23.4385075231481 & 24.5609166666667 & -1.12240914351852 & 1.04349247685186 \tabularnewline
15 & 27.474 & 25.8381950231481 & 25.0044583333333 & 0.833736689814813 & 1.63580497685185 \tabularnewline
16 & 27.264 & 27.3529589120370 & 25.3810833333333 & 1.97187557870370 & -0.0889589120370324 \tabularnewline
17 & 27.349 & 28.3531880787037 & 25.744375 & 2.60881307870370 & -1.00418807870370 \tabularnewline
18 & 30.632 & 29.7466047453704 & 26.0198333333333 & 3.72677141203704 & 0.885395254629632 \tabularnewline
19 & 29.429 & 28.7888130787037 & 26.1119583333333 & 2.67685474537037 & 0.640186921296298 \tabularnewline
20 & 30.084 & 29.0134658564815 & 26.0988333333333 & 2.91463252314815 & 1.07053414351852 \tabularnewline
21 & 26.29 & 26.8757783564815 & 26.1367916666667 & 0.738986689814819 & -0.585778356481484 \tabularnewline
22 & 24.379 & 24.6747019675926 & 26.3209583333333 & -1.64625636574074 & -0.295701967592592 \tabularnewline
23 & 23.335 & 23.4857297453704 & 26.635125 & -3.14939525462963 & -0.150729745370366 \tabularnewline
24 & 21.346 & 21.3676950231481 & 26.96525 & -5.59755497685185 & -0.0216950231481476 \tabularnewline
25 & 21.106 & 23.3571116898148 & 27.3131666666667 & -3.95605497685186 & -2.25111168981481 \tabularnewline
26 & 24.514 & 26.5711325231481 & 27.6935416666667 & -1.12240914351852 & -2.05713252314815 \tabularnewline
27 & 28.353 & 28.9831950231481 & 28.1494583333333 & 0.833736689814813 & -0.630195023148147 \tabularnewline
28 & 30.805 & 30.6154172453704 & 28.6435416666667 & 1.97187557870370 & 0.189582754629630 \tabularnewline
29 & 31.348 & 31.7332297453704 & 29.1244166666667 & 2.60881307870370 & -0.385229745370374 \tabularnewline
30 & 34.556 & 33.3816464120370 & 29.654875 & 3.72677141203704 & 1.17435358796296 \tabularnewline
31 & 33.855 & 33.0054380787037 & 30.3285833333333 & 2.67685474537037 & 0.849561921296299 \tabularnewline
32 & 34.787 & 34.0994658564815 & 31.1848333333333 & 2.91463252314815 & 0.68753414351852 \tabularnewline
33 & 32.529 & 32.8473200231481 & 32.1083333333333 & 0.738986689814819 & -0.318320023148143 \tabularnewline
34 & 29.998 & 31.2754103009259 & 32.9216666666667 & -1.64625636574074 & -1.27741030092592 \tabularnewline
35 & 29.257 & 30.5819380787037 & 33.7313333333333 & -3.14939525462963 & -1.32493807870371 \tabularnewline
36 & 28.155 & 28.9654450231482 & 34.563 & -5.59755497685185 & -0.810445023148148 \tabularnewline
37 & 30.466 & 31.3961533564815 & 35.3522083333333 & -3.95605497685186 & -0.930153356481483 \tabularnewline
38 & 35.704 & 34.9881741898148 & 36.1105833333333 & -1.12240914351852 & 0.715825810185187 \tabularnewline
39 & 39.327 & 37.5189033564815 & 36.6851666666667 & 0.833736689814813 & 1.80809664351852 \tabularnewline
40 & 39.351 & 39.1817505787037 & 37.209875 & 1.97187557870370 & 0.169249421296300 \tabularnewline
41 & 42.234 & 40.3406047453704 & 37.7317916666667 & 2.60881307870370 & 1.89339525462963 \tabularnewline
42 & 43.63 & 41.8860630787037 & 38.1592916666667 & 3.72677141203704 & 1.74393692129630 \tabularnewline
43 & 43.722 & 41.231646412037 & 38.5547916666667 & 2.67685474537037 & 2.49035358796296 \tabularnewline
44 & 43.121 & 41.7928825231482 & 38.87825 & 2.91463252314815 & 1.32811747685185 \tabularnewline
45 & 37.985 & 39.8600700231481 & 39.1210833333333 & 0.738986689814819 & -1.87507002314814 \tabularnewline
46 & 37.135 & 37.7766186342593 & 39.422875 & -1.64625636574074 & -0.64161863425926 \tabularnewline
47 & 34.646 & 36.4897714120370 & 39.6391666666667 & -3.14939525462963 & -1.84377141203703 \tabularnewline
48 & 33.026 & 34.1010700231482 & 39.698625 & -5.59755497685185 & -1.07507002314815 \tabularnewline
49 & 35.087 & 35.7941533564815 & 39.7502083333333 & -3.95605497685186 & -0.707153356481484 \tabularnewline
50 & 38.846 & 38.6677991898148 & 39.7902083333333 & -1.12240914351852 & 0.178200810185182 \tabularnewline
51 & 42.013 & 40.9119450231481 & 40.0782083333333 & 0.833736689814813 & 1.10105497685185 \tabularnewline
52 & 43.908 & 42.5252505787037 & 40.553375 & 1.97187557870370 & 1.38274942129630 \tabularnewline
53 & 42.868 & 43.7377297453704 & 41.1289166666667 & 2.60881307870370 & -0.869729745370371 \tabularnewline
54 & 44.423 & 45.3845214120370 & 41.65775 & 3.72677141203704 & -0.961521412037037 \tabularnewline
55 & 44.167 & 44.8017714120370 & 42.1249166666667 & 2.67685474537037 & -0.63477141203704 \tabularnewline
56 & 43.636 & 45.6155491898148 & 42.7009166666667 & 2.91463252314815 & -1.97954918981481 \tabularnewline
57 & 44.382 & 43.8298200231481 & 43.0908333333333 & 0.738986689814819 & 0.552179976851853 \tabularnewline
58 & 42.142 & 41.7138269675926 & 43.3600833333333 & -1.64625636574074 & 0.428173032407408 \tabularnewline
59 & 43.452 & 40.6393547453704 & 43.78875 & -3.14939525462963 & 2.81264525462963 \tabularnewline
60 & 36.912 & 38.5925283564815 & 44.1900833333333 & -5.59755497685185 & -1.68052835648147 \tabularnewline
61 & 42.413 & 40.4330700231481 & 44.389125 & -3.95605497685186 & 1.97992997685185 \tabularnewline
62 & 45.344 & 43.5306741898148 & 44.6530833333333 & -1.12240914351852 & 1.81332581018518 \tabularnewline
63 & 44.873 & 45.8436116898148 & 45.009875 & 0.833736689814813 & -0.970611689814817 \tabularnewline
64 & 47.51 & 47.266958912037 & 45.2950833333333 & 1.97187557870370 & 0.243041087962965 \tabularnewline
65 & 49.554 & 47.8950630787037 & 45.28625 & 2.60881307870370 & 1.65893692129631 \tabularnewline
66 & 47.369 & 48.9609797453704 & 45.2342083333333 & 3.72677141203704 & -1.59197974537037 \tabularnewline
67 & 45.998 & 47.768646412037 & 45.0917916666667 & 2.67685474537037 & -1.77064641203704 \tabularnewline
68 & 48.14 & 47.4369241898148 & 44.5222916666667 & 2.91463252314815 & 0.703075810185183 \tabularnewline
69 & 48.441 & 44.5550283564815 & 43.8160416666667 & 0.738986689814819 & 3.88597164351852 \tabularnewline
70 & 44.928 & 41.4045769675926 & 43.0508333333333 & -1.64625636574074 & 3.52342303240741 \tabularnewline
71 & 40.454 & 39.0128547453704 & 42.16225 & -3.14939525462963 & 1.44114525462963 \tabularnewline
72 & 38.661 & 35.7296116898148 & 41.3271666666667 & -5.59755497685185 & 2.93138831018519 \tabularnewline
73 & 37.246 & 36.5348616898148 & 40.4909166666667 & -3.95605497685186 & 0.711138310185177 \tabularnewline
74 & 36.843 & 38.3894241898148 & 39.5118333333333 & -1.12240914351852 & -1.54642418981481 \tabularnewline
75 & 36.424 & 39.2208616898148 & 38.387125 & 0.833736689814813 & -2.79686168981481 \tabularnewline
76 & 37.594 & 39.3423755787037 & 37.3705 & 1.97187557870370 & -1.74837557870371 \tabularnewline
77 & 38.144 & 39.289896412037 & 36.6810833333333 & 2.60881307870370 & -1.14589641203705 \tabularnewline
78 & 38.737 & 39.839896412037 & 36.113125 & 3.72677141203704 & -1.10289641203704 \tabularnewline
79 & 34.56 & NA & NA & 2.67685474537037 & NA \tabularnewline
80 & 36.08 & NA & NA & 2.91463252314815 & NA \tabularnewline
81 & 33.508 & NA & NA & 0.738986689814819 & NA \tabularnewline
82 & 35.462 & NA & NA & -1.64625636574074 & NA \tabularnewline
83 & 33.374 & NA & NA & -3.14939525462963 & NA \tabularnewline
84 & 32.11 & NA & NA & -5.59755497685185 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112160&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]21.454[/C][C]NA[/C][C]NA[/C][C]-3.95605497685186[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]23.899[/C][C]NA[/C][C]NA[/C][C]-1.12240914351852[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]24.939[/C][C]NA[/C][C]NA[/C][C]0.833736689814813[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]23.58[/C][C]NA[/C][C]NA[/C][C]1.97187557870370[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]24.562[/C][C]NA[/C][C]NA[/C][C]2.60881307870370[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]24.696[/C][C]NA[/C][C]NA[/C][C]3.72677141203704[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]23.785[/C][C]25.2123964120370[/C][C]22.5355416666667[/C][C]2.67685474537037[/C][C]-1.42739641203704[/C][/ROW]
[ROW][C]8[/C][C]23.812[/C][C]25.4744241898148[/C][C]22.5597916666667[/C][C]2.91463252314815[/C][C]-1.66242418981481[/C][/ROW]
[ROW][C]9[/C][C]21.917[/C][C]23.4286950231481[/C][C]22.6897083333333[/C][C]0.738986689814819[/C][C]-1.51169502314815[/C][/ROW]
[ROW][C]10[/C][C]19.713[/C][C]21.3025769675926[/C][C]22.9488333333333[/C][C]-1.64625636574074[/C][C]-1.58957696759259[/C][/ROW]
[ROW][C]11[/C][C]19.282[/C][C]20.0690630787037[/C][C]23.2184583333333[/C][C]-3.14939525462963[/C][C]-0.7870630787037[/C][/ROW]
[ROW][C]12[/C][C]18.788[/C][C]17.9843616898148[/C][C]23.5819166666667[/C][C]-5.59755497685185[/C][C]0.803638310185189[/C][/ROW]
[ROW][C]13[/C][C]21.453[/C][C]20.1083616898148[/C][C]24.0644166666667[/C][C]-3.95605497685186[/C][C]1.34463831018519[/C][/ROW]
[ROW][C]14[/C][C]24.482[/C][C]23.4385075231481[/C][C]24.5609166666667[/C][C]-1.12240914351852[/C][C]1.04349247685186[/C][/ROW]
[ROW][C]15[/C][C]27.474[/C][C]25.8381950231481[/C][C]25.0044583333333[/C][C]0.833736689814813[/C][C]1.63580497685185[/C][/ROW]
[ROW][C]16[/C][C]27.264[/C][C]27.3529589120370[/C][C]25.3810833333333[/C][C]1.97187557870370[/C][C]-0.0889589120370324[/C][/ROW]
[ROW][C]17[/C][C]27.349[/C][C]28.3531880787037[/C][C]25.744375[/C][C]2.60881307870370[/C][C]-1.00418807870370[/C][/ROW]
[ROW][C]18[/C][C]30.632[/C][C]29.7466047453704[/C][C]26.0198333333333[/C][C]3.72677141203704[/C][C]0.885395254629632[/C][/ROW]
[ROW][C]19[/C][C]29.429[/C][C]28.7888130787037[/C][C]26.1119583333333[/C][C]2.67685474537037[/C][C]0.640186921296298[/C][/ROW]
[ROW][C]20[/C][C]30.084[/C][C]29.0134658564815[/C][C]26.0988333333333[/C][C]2.91463252314815[/C][C]1.07053414351852[/C][/ROW]
[ROW][C]21[/C][C]26.29[/C][C]26.8757783564815[/C][C]26.1367916666667[/C][C]0.738986689814819[/C][C]-0.585778356481484[/C][/ROW]
[ROW][C]22[/C][C]24.379[/C][C]24.6747019675926[/C][C]26.3209583333333[/C][C]-1.64625636574074[/C][C]-0.295701967592592[/C][/ROW]
[ROW][C]23[/C][C]23.335[/C][C]23.4857297453704[/C][C]26.635125[/C][C]-3.14939525462963[/C][C]-0.150729745370366[/C][/ROW]
[ROW][C]24[/C][C]21.346[/C][C]21.3676950231481[/C][C]26.96525[/C][C]-5.59755497685185[/C][C]-0.0216950231481476[/C][/ROW]
[ROW][C]25[/C][C]21.106[/C][C]23.3571116898148[/C][C]27.3131666666667[/C][C]-3.95605497685186[/C][C]-2.25111168981481[/C][/ROW]
[ROW][C]26[/C][C]24.514[/C][C]26.5711325231481[/C][C]27.6935416666667[/C][C]-1.12240914351852[/C][C]-2.05713252314815[/C][/ROW]
[ROW][C]27[/C][C]28.353[/C][C]28.9831950231481[/C][C]28.1494583333333[/C][C]0.833736689814813[/C][C]-0.630195023148147[/C][/ROW]
[ROW][C]28[/C][C]30.805[/C][C]30.6154172453704[/C][C]28.6435416666667[/C][C]1.97187557870370[/C][C]0.189582754629630[/C][/ROW]
[ROW][C]29[/C][C]31.348[/C][C]31.7332297453704[/C][C]29.1244166666667[/C][C]2.60881307870370[/C][C]-0.385229745370374[/C][/ROW]
[ROW][C]30[/C][C]34.556[/C][C]33.3816464120370[/C][C]29.654875[/C][C]3.72677141203704[/C][C]1.17435358796296[/C][/ROW]
[ROW][C]31[/C][C]33.855[/C][C]33.0054380787037[/C][C]30.3285833333333[/C][C]2.67685474537037[/C][C]0.849561921296299[/C][/ROW]
[ROW][C]32[/C][C]34.787[/C][C]34.0994658564815[/C][C]31.1848333333333[/C][C]2.91463252314815[/C][C]0.68753414351852[/C][/ROW]
[ROW][C]33[/C][C]32.529[/C][C]32.8473200231481[/C][C]32.1083333333333[/C][C]0.738986689814819[/C][C]-0.318320023148143[/C][/ROW]
[ROW][C]34[/C][C]29.998[/C][C]31.2754103009259[/C][C]32.9216666666667[/C][C]-1.64625636574074[/C][C]-1.27741030092592[/C][/ROW]
[ROW][C]35[/C][C]29.257[/C][C]30.5819380787037[/C][C]33.7313333333333[/C][C]-3.14939525462963[/C][C]-1.32493807870371[/C][/ROW]
[ROW][C]36[/C][C]28.155[/C][C]28.9654450231482[/C][C]34.563[/C][C]-5.59755497685185[/C][C]-0.810445023148148[/C][/ROW]
[ROW][C]37[/C][C]30.466[/C][C]31.3961533564815[/C][C]35.3522083333333[/C][C]-3.95605497685186[/C][C]-0.930153356481483[/C][/ROW]
[ROW][C]38[/C][C]35.704[/C][C]34.9881741898148[/C][C]36.1105833333333[/C][C]-1.12240914351852[/C][C]0.715825810185187[/C][/ROW]
[ROW][C]39[/C][C]39.327[/C][C]37.5189033564815[/C][C]36.6851666666667[/C][C]0.833736689814813[/C][C]1.80809664351852[/C][/ROW]
[ROW][C]40[/C][C]39.351[/C][C]39.1817505787037[/C][C]37.209875[/C][C]1.97187557870370[/C][C]0.169249421296300[/C][/ROW]
[ROW][C]41[/C][C]42.234[/C][C]40.3406047453704[/C][C]37.7317916666667[/C][C]2.60881307870370[/C][C]1.89339525462963[/C][/ROW]
[ROW][C]42[/C][C]43.63[/C][C]41.8860630787037[/C][C]38.1592916666667[/C][C]3.72677141203704[/C][C]1.74393692129630[/C][/ROW]
[ROW][C]43[/C][C]43.722[/C][C]41.231646412037[/C][C]38.5547916666667[/C][C]2.67685474537037[/C][C]2.49035358796296[/C][/ROW]
[ROW][C]44[/C][C]43.121[/C][C]41.7928825231482[/C][C]38.87825[/C][C]2.91463252314815[/C][C]1.32811747685185[/C][/ROW]
[ROW][C]45[/C][C]37.985[/C][C]39.8600700231481[/C][C]39.1210833333333[/C][C]0.738986689814819[/C][C]-1.87507002314814[/C][/ROW]
[ROW][C]46[/C][C]37.135[/C][C]37.7766186342593[/C][C]39.422875[/C][C]-1.64625636574074[/C][C]-0.64161863425926[/C][/ROW]
[ROW][C]47[/C][C]34.646[/C][C]36.4897714120370[/C][C]39.6391666666667[/C][C]-3.14939525462963[/C][C]-1.84377141203703[/C][/ROW]
[ROW][C]48[/C][C]33.026[/C][C]34.1010700231482[/C][C]39.698625[/C][C]-5.59755497685185[/C][C]-1.07507002314815[/C][/ROW]
[ROW][C]49[/C][C]35.087[/C][C]35.7941533564815[/C][C]39.7502083333333[/C][C]-3.95605497685186[/C][C]-0.707153356481484[/C][/ROW]
[ROW][C]50[/C][C]38.846[/C][C]38.6677991898148[/C][C]39.7902083333333[/C][C]-1.12240914351852[/C][C]0.178200810185182[/C][/ROW]
[ROW][C]51[/C][C]42.013[/C][C]40.9119450231481[/C][C]40.0782083333333[/C][C]0.833736689814813[/C][C]1.10105497685185[/C][/ROW]
[ROW][C]52[/C][C]43.908[/C][C]42.5252505787037[/C][C]40.553375[/C][C]1.97187557870370[/C][C]1.38274942129630[/C][/ROW]
[ROW][C]53[/C][C]42.868[/C][C]43.7377297453704[/C][C]41.1289166666667[/C][C]2.60881307870370[/C][C]-0.869729745370371[/C][/ROW]
[ROW][C]54[/C][C]44.423[/C][C]45.3845214120370[/C][C]41.65775[/C][C]3.72677141203704[/C][C]-0.961521412037037[/C][/ROW]
[ROW][C]55[/C][C]44.167[/C][C]44.8017714120370[/C][C]42.1249166666667[/C][C]2.67685474537037[/C][C]-0.63477141203704[/C][/ROW]
[ROW][C]56[/C][C]43.636[/C][C]45.6155491898148[/C][C]42.7009166666667[/C][C]2.91463252314815[/C][C]-1.97954918981481[/C][/ROW]
[ROW][C]57[/C][C]44.382[/C][C]43.8298200231481[/C][C]43.0908333333333[/C][C]0.738986689814819[/C][C]0.552179976851853[/C][/ROW]
[ROW][C]58[/C][C]42.142[/C][C]41.7138269675926[/C][C]43.3600833333333[/C][C]-1.64625636574074[/C][C]0.428173032407408[/C][/ROW]
[ROW][C]59[/C][C]43.452[/C][C]40.6393547453704[/C][C]43.78875[/C][C]-3.14939525462963[/C][C]2.81264525462963[/C][/ROW]
[ROW][C]60[/C][C]36.912[/C][C]38.5925283564815[/C][C]44.1900833333333[/C][C]-5.59755497685185[/C][C]-1.68052835648147[/C][/ROW]
[ROW][C]61[/C][C]42.413[/C][C]40.4330700231481[/C][C]44.389125[/C][C]-3.95605497685186[/C][C]1.97992997685185[/C][/ROW]
[ROW][C]62[/C][C]45.344[/C][C]43.5306741898148[/C][C]44.6530833333333[/C][C]-1.12240914351852[/C][C]1.81332581018518[/C][/ROW]
[ROW][C]63[/C][C]44.873[/C][C]45.8436116898148[/C][C]45.009875[/C][C]0.833736689814813[/C][C]-0.970611689814817[/C][/ROW]
[ROW][C]64[/C][C]47.51[/C][C]47.266958912037[/C][C]45.2950833333333[/C][C]1.97187557870370[/C][C]0.243041087962965[/C][/ROW]
[ROW][C]65[/C][C]49.554[/C][C]47.8950630787037[/C][C]45.28625[/C][C]2.60881307870370[/C][C]1.65893692129631[/C][/ROW]
[ROW][C]66[/C][C]47.369[/C][C]48.9609797453704[/C][C]45.2342083333333[/C][C]3.72677141203704[/C][C]-1.59197974537037[/C][/ROW]
[ROW][C]67[/C][C]45.998[/C][C]47.768646412037[/C][C]45.0917916666667[/C][C]2.67685474537037[/C][C]-1.77064641203704[/C][/ROW]
[ROW][C]68[/C][C]48.14[/C][C]47.4369241898148[/C][C]44.5222916666667[/C][C]2.91463252314815[/C][C]0.703075810185183[/C][/ROW]
[ROW][C]69[/C][C]48.441[/C][C]44.5550283564815[/C][C]43.8160416666667[/C][C]0.738986689814819[/C][C]3.88597164351852[/C][/ROW]
[ROW][C]70[/C][C]44.928[/C][C]41.4045769675926[/C][C]43.0508333333333[/C][C]-1.64625636574074[/C][C]3.52342303240741[/C][/ROW]
[ROW][C]71[/C][C]40.454[/C][C]39.0128547453704[/C][C]42.16225[/C][C]-3.14939525462963[/C][C]1.44114525462963[/C][/ROW]
[ROW][C]72[/C][C]38.661[/C][C]35.7296116898148[/C][C]41.3271666666667[/C][C]-5.59755497685185[/C][C]2.93138831018519[/C][/ROW]
[ROW][C]73[/C][C]37.246[/C][C]36.5348616898148[/C][C]40.4909166666667[/C][C]-3.95605497685186[/C][C]0.711138310185177[/C][/ROW]
[ROW][C]74[/C][C]36.843[/C][C]38.3894241898148[/C][C]39.5118333333333[/C][C]-1.12240914351852[/C][C]-1.54642418981481[/C][/ROW]
[ROW][C]75[/C][C]36.424[/C][C]39.2208616898148[/C][C]38.387125[/C][C]0.833736689814813[/C][C]-2.79686168981481[/C][/ROW]
[ROW][C]76[/C][C]37.594[/C][C]39.3423755787037[/C][C]37.3705[/C][C]1.97187557870370[/C][C]-1.74837557870371[/C][/ROW]
[ROW][C]77[/C][C]38.144[/C][C]39.289896412037[/C][C]36.6810833333333[/C][C]2.60881307870370[/C][C]-1.14589641203705[/C][/ROW]
[ROW][C]78[/C][C]38.737[/C][C]39.839896412037[/C][C]36.113125[/C][C]3.72677141203704[/C][C]-1.10289641203704[/C][/ROW]
[ROW][C]79[/C][C]34.56[/C][C]NA[/C][C]NA[/C][C]2.67685474537037[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]36.08[/C][C]NA[/C][C]NA[/C][C]2.91463252314815[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]33.508[/C][C]NA[/C][C]NA[/C][C]0.738986689814819[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]35.462[/C][C]NA[/C][C]NA[/C][C]-1.64625636574074[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]33.374[/C][C]NA[/C][C]NA[/C][C]-3.14939525462963[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]32.11[/C][C]NA[/C][C]NA[/C][C]-5.59755497685185[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112160&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112160&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
121.454NANA-3.95605497685186NA
223.899NANA-1.12240914351852NA
324.939NANA0.833736689814813NA
423.58NANA1.97187557870370NA
524.562NANA2.60881307870370NA
624.696NANA3.72677141203704NA
723.78525.212396412037022.53554166666672.67685474537037-1.42739641203704
823.81225.474424189814822.55979166666672.91463252314815-1.66242418981481
921.91723.428695023148122.68970833333330.738986689814819-1.51169502314815
1019.71321.302576967592622.9488333333333-1.64625636574074-1.58957696759259
1119.28220.069063078703723.2184583333333-3.14939525462963-0.7870630787037
1218.78817.984361689814823.5819166666667-5.597554976851850.803638310185189
1321.45320.108361689814824.0644166666667-3.956054976851861.34463831018519
1424.48223.438507523148124.5609166666667-1.122409143518521.04349247685186
1527.47425.838195023148125.00445833333330.8337366898148131.63580497685185
1627.26427.352958912037025.38108333333331.97187557870370-0.0889589120370324
1727.34928.353188078703725.7443752.60881307870370-1.00418807870370
1830.63229.746604745370426.01983333333333.726771412037040.885395254629632
1929.42928.788813078703726.11195833333332.676854745370370.640186921296298
2030.08429.013465856481526.09883333333332.914632523148151.07053414351852
2126.2926.875778356481526.13679166666670.738986689814819-0.585778356481484
2224.37924.674701967592626.3209583333333-1.64625636574074-0.295701967592592
2323.33523.485729745370426.635125-3.14939525462963-0.150729745370366
2421.34621.367695023148126.96525-5.59755497685185-0.0216950231481476
2521.10623.357111689814827.3131666666667-3.95605497685186-2.25111168981481
2624.51426.571132523148127.6935416666667-1.12240914351852-2.05713252314815
2728.35328.983195023148128.14945833333330.833736689814813-0.630195023148147
2830.80530.615417245370428.64354166666671.971875578703700.189582754629630
2931.34831.733229745370429.12441666666672.60881307870370-0.385229745370374
3034.55633.381646412037029.6548753.726771412037041.17435358796296
3133.85533.005438078703730.32858333333332.676854745370370.849561921296299
3234.78734.099465856481531.18483333333332.914632523148150.68753414351852
3332.52932.847320023148132.10833333333330.738986689814819-0.318320023148143
3429.99831.275410300925932.9216666666667-1.64625636574074-1.27741030092592
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3730.46631.396153356481535.3522083333333-3.95605497685186-0.930153356481483
3835.70434.988174189814836.1105833333333-1.122409143518520.715825810185187
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7838.73739.83989641203736.1131253.72677141203704-1.10289641203704
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8036.08NANA2.91463252314815NA
8133.508NANA0.738986689814819NA
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8333.374NANA-3.14939525462963NA
8432.11NANA-5.59755497685185NA



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')