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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 04 Dec 2013 03:59:42 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/04/t1386147702vnpumi9ol5g3edr.htm/, Retrieved Thu, 28 Mar 2024 10:22:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230442, Retrieved Thu, 28 Mar 2024 10:22:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Reserve positie I...] [2013-12-04 08:59:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
679
687
638
628
604
713
712
693
697
555
486
470
465
426
384
379
381
380
351
346
339
336
333
324
324
321
304
343
407
389
361
353
361
387
692
704
742
721
843
847
945
946
946
945
1082
1075
820
832
851
1090
1203
1239
1535
1527
1480
1452
1383
1381
1429
1376
1602
1597
2003
1958
1997
1986
2129
2115
2297
2250
2309
2648
2627
2711
2732
2825
2932
2910
2969
2999
2965
2846
2847
2751




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230442&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230442&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230442&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 time9 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1679NANA-41.3958NA
2687NANA-30.5833NA
3638NANA38.1528NA
4628NANA26.8264NA
5604NANA95.5208NA
6713NANA53.4514NA
7712654.278621.2533.027857.7222
8693594.403601.458-7.0555698.5972
9697586.8475806.84722110.153
10555506.924559.042-52.118148.0764
11486470539.375-69.37516
12470462.91516.208-53.29867.09028
13465445.896487.292-41.395819.1042
14426427.208457.792-30.5833-1.20833
15384466.569428.41738.1528-82.5694
16379431.201404.37526.8264-52.2014
17381484.396388.87595.5208-103.396
18380429.868376.41753.4514-49.8681
19351397.486364.45833.0278-46.4861
20346347.153354.208-7.05556-1.15278
21339353.347346.56.84722-14.3472
22336289.549341.667-52.118146.4514
23333271.875341.25-69.37561.125
24324289.41342.708-53.298634.5903
25324302.104343.5-41.395821.8958
26321313.625344.208-30.58337.375
27304383.569345.41738.1528-79.5694
28343375.285348.45826.8264-32.2847
29407461.062365.54295.5208-54.0625
30389449.785396.33353.4514-60.7847
31361462.611429.58333.0278-101.611
32353456.611463.667-7.05556-103.611
33361509.639502.7926.84722-148.639
34387494.132546.25-52.1181-107.132
35692520.292589.667-69.375171.708
36704581.993635.292-53.2986122.007
37742641.479682.875-41.3958100.521
38721701.333731.917-30.583319.6667
39843824.778786.62538.152818.2222
40847872.16845.33326.8264-25.1597
41945974.854879.33395.5208-29.8542
42946943.45189053.45142.54861
43946932.903899.87533.027813.0972
44945912.736919.792-7.0555632.2639
451082957.014950.1676.84722124.986
461075929.382981.5-52.1181145.618
47820953.0421022.42-69.375-133.042
488321017.911071.21-53.2986-185.91
498511076.271117.67-41.3958-225.271
5010901130.461161.04-30.5833-40.4583
5112031232.861194.7138.1528-29.8611
5212391246.83122026.8264-7.82639
5315351353.651258.1295.5208181.354
5415271359.621306.1753.4514167.382
5514801393.151360.1233.027886.8472
5614521405.491412.54-7.0555646.5139
5713831473.8514676.84722-90.8472
5813811478.171530.29-52.1181-97.1736
5914291510.121579.5-69.375-81.125
6013761564.581617.87-53.2986-188.576
6116021622.651664.04-41.3958-20.6458
6215971688.121718.71-30.5833-91.125
6320031822.571784.4238.1528180.431
6419581885.531858.7126.826472.4653
6519972027.11931.5895.5208-30.1042
6619862074.72021.2553.4514-88.7014
6721292149.992116.9633.0278-20.9861
6821152199.032206.08-7.05556-84.0278
6922972289.722282.886.847227.27778
7022502297.262349.38-52.1181-47.2569
7123092355.082424.46-69.375-46.0833
7226482448.622501.92-53.2986199.382
7326272534.022575.42-41.395892.9792
7427112616.672647.25-30.583394.3333
7527322750.072711.9238.1528-18.0694
7628252791.412764.5826.826433.5903
7729322907.352811.8395.520824.6458
7829102891.992838.5453.451418.0069
792969NANA33.0278NA
802999NANA-7.05556NA
812965NANA6.84722NA
822846NANA-52.1181NA
832847NANA-69.375NA
842751NANA-53.2986NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 679 & NA & NA & -41.3958 & NA \tabularnewline
2 & 687 & NA & NA & -30.5833 & NA \tabularnewline
3 & 638 & NA & NA & 38.1528 & NA \tabularnewline
4 & 628 & NA & NA & 26.8264 & NA \tabularnewline
5 & 604 & NA & NA & 95.5208 & NA \tabularnewline
6 & 713 & NA & NA & 53.4514 & NA \tabularnewline
7 & 712 & 654.278 & 621.25 & 33.0278 & 57.7222 \tabularnewline
8 & 693 & 594.403 & 601.458 & -7.05556 & 98.5972 \tabularnewline
9 & 697 & 586.847 & 580 & 6.84722 & 110.153 \tabularnewline
10 & 555 & 506.924 & 559.042 & -52.1181 & 48.0764 \tabularnewline
11 & 486 & 470 & 539.375 & -69.375 & 16 \tabularnewline
12 & 470 & 462.91 & 516.208 & -53.2986 & 7.09028 \tabularnewline
13 & 465 & 445.896 & 487.292 & -41.3958 & 19.1042 \tabularnewline
14 & 426 & 427.208 & 457.792 & -30.5833 & -1.20833 \tabularnewline
15 & 384 & 466.569 & 428.417 & 38.1528 & -82.5694 \tabularnewline
16 & 379 & 431.201 & 404.375 & 26.8264 & -52.2014 \tabularnewline
17 & 381 & 484.396 & 388.875 & 95.5208 & -103.396 \tabularnewline
18 & 380 & 429.868 & 376.417 & 53.4514 & -49.8681 \tabularnewline
19 & 351 & 397.486 & 364.458 & 33.0278 & -46.4861 \tabularnewline
20 & 346 & 347.153 & 354.208 & -7.05556 & -1.15278 \tabularnewline
21 & 339 & 353.347 & 346.5 & 6.84722 & -14.3472 \tabularnewline
22 & 336 & 289.549 & 341.667 & -52.1181 & 46.4514 \tabularnewline
23 & 333 & 271.875 & 341.25 & -69.375 & 61.125 \tabularnewline
24 & 324 & 289.41 & 342.708 & -53.2986 & 34.5903 \tabularnewline
25 & 324 & 302.104 & 343.5 & -41.3958 & 21.8958 \tabularnewline
26 & 321 & 313.625 & 344.208 & -30.5833 & 7.375 \tabularnewline
27 & 304 & 383.569 & 345.417 & 38.1528 & -79.5694 \tabularnewline
28 & 343 & 375.285 & 348.458 & 26.8264 & -32.2847 \tabularnewline
29 & 407 & 461.062 & 365.542 & 95.5208 & -54.0625 \tabularnewline
30 & 389 & 449.785 & 396.333 & 53.4514 & -60.7847 \tabularnewline
31 & 361 & 462.611 & 429.583 & 33.0278 & -101.611 \tabularnewline
32 & 353 & 456.611 & 463.667 & -7.05556 & -103.611 \tabularnewline
33 & 361 & 509.639 & 502.792 & 6.84722 & -148.639 \tabularnewline
34 & 387 & 494.132 & 546.25 & -52.1181 & -107.132 \tabularnewline
35 & 692 & 520.292 & 589.667 & -69.375 & 171.708 \tabularnewline
36 & 704 & 581.993 & 635.292 & -53.2986 & 122.007 \tabularnewline
37 & 742 & 641.479 & 682.875 & -41.3958 & 100.521 \tabularnewline
38 & 721 & 701.333 & 731.917 & -30.5833 & 19.6667 \tabularnewline
39 & 843 & 824.778 & 786.625 & 38.1528 & 18.2222 \tabularnewline
40 & 847 & 872.16 & 845.333 & 26.8264 & -25.1597 \tabularnewline
41 & 945 & 974.854 & 879.333 & 95.5208 & -29.8542 \tabularnewline
42 & 946 & 943.451 & 890 & 53.4514 & 2.54861 \tabularnewline
43 & 946 & 932.903 & 899.875 & 33.0278 & 13.0972 \tabularnewline
44 & 945 & 912.736 & 919.792 & -7.05556 & 32.2639 \tabularnewline
45 & 1082 & 957.014 & 950.167 & 6.84722 & 124.986 \tabularnewline
46 & 1075 & 929.382 & 981.5 & -52.1181 & 145.618 \tabularnewline
47 & 820 & 953.042 & 1022.42 & -69.375 & -133.042 \tabularnewline
48 & 832 & 1017.91 & 1071.21 & -53.2986 & -185.91 \tabularnewline
49 & 851 & 1076.27 & 1117.67 & -41.3958 & -225.271 \tabularnewline
50 & 1090 & 1130.46 & 1161.04 & -30.5833 & -40.4583 \tabularnewline
51 & 1203 & 1232.86 & 1194.71 & 38.1528 & -29.8611 \tabularnewline
52 & 1239 & 1246.83 & 1220 & 26.8264 & -7.82639 \tabularnewline
53 & 1535 & 1353.65 & 1258.12 & 95.5208 & 181.354 \tabularnewline
54 & 1527 & 1359.62 & 1306.17 & 53.4514 & 167.382 \tabularnewline
55 & 1480 & 1393.15 & 1360.12 & 33.0278 & 86.8472 \tabularnewline
56 & 1452 & 1405.49 & 1412.54 & -7.05556 & 46.5139 \tabularnewline
57 & 1383 & 1473.85 & 1467 & 6.84722 & -90.8472 \tabularnewline
58 & 1381 & 1478.17 & 1530.29 & -52.1181 & -97.1736 \tabularnewline
59 & 1429 & 1510.12 & 1579.5 & -69.375 & -81.125 \tabularnewline
60 & 1376 & 1564.58 & 1617.87 & -53.2986 & -188.576 \tabularnewline
61 & 1602 & 1622.65 & 1664.04 & -41.3958 & -20.6458 \tabularnewline
62 & 1597 & 1688.12 & 1718.71 & -30.5833 & -91.125 \tabularnewline
63 & 2003 & 1822.57 & 1784.42 & 38.1528 & 180.431 \tabularnewline
64 & 1958 & 1885.53 & 1858.71 & 26.8264 & 72.4653 \tabularnewline
65 & 1997 & 2027.1 & 1931.58 & 95.5208 & -30.1042 \tabularnewline
66 & 1986 & 2074.7 & 2021.25 & 53.4514 & -88.7014 \tabularnewline
67 & 2129 & 2149.99 & 2116.96 & 33.0278 & -20.9861 \tabularnewline
68 & 2115 & 2199.03 & 2206.08 & -7.05556 & -84.0278 \tabularnewline
69 & 2297 & 2289.72 & 2282.88 & 6.84722 & 7.27778 \tabularnewline
70 & 2250 & 2297.26 & 2349.38 & -52.1181 & -47.2569 \tabularnewline
71 & 2309 & 2355.08 & 2424.46 & -69.375 & -46.0833 \tabularnewline
72 & 2648 & 2448.62 & 2501.92 & -53.2986 & 199.382 \tabularnewline
73 & 2627 & 2534.02 & 2575.42 & -41.3958 & 92.9792 \tabularnewline
74 & 2711 & 2616.67 & 2647.25 & -30.5833 & 94.3333 \tabularnewline
75 & 2732 & 2750.07 & 2711.92 & 38.1528 & -18.0694 \tabularnewline
76 & 2825 & 2791.41 & 2764.58 & 26.8264 & 33.5903 \tabularnewline
77 & 2932 & 2907.35 & 2811.83 & 95.5208 & 24.6458 \tabularnewline
78 & 2910 & 2891.99 & 2838.54 & 53.4514 & 18.0069 \tabularnewline
79 & 2969 & NA & NA & 33.0278 & NA \tabularnewline
80 & 2999 & NA & NA & -7.05556 & NA \tabularnewline
81 & 2965 & NA & NA & 6.84722 & NA \tabularnewline
82 & 2846 & NA & NA & -52.1181 & NA \tabularnewline
83 & 2847 & NA & NA & -69.375 & NA \tabularnewline
84 & 2751 & NA & NA & -53.2986 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230442&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]679[/C][C]NA[/C][C]NA[/C][C]-41.3958[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]687[/C][C]NA[/C][C]NA[/C][C]-30.5833[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]638[/C][C]NA[/C][C]NA[/C][C]38.1528[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]628[/C][C]NA[/C][C]NA[/C][C]26.8264[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]604[/C][C]NA[/C][C]NA[/C][C]95.5208[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]713[/C][C]NA[/C][C]NA[/C][C]53.4514[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]712[/C][C]654.278[/C][C]621.25[/C][C]33.0278[/C][C]57.7222[/C][/ROW]
[ROW][C]8[/C][C]693[/C][C]594.403[/C][C]601.458[/C][C]-7.05556[/C][C]98.5972[/C][/ROW]
[ROW][C]9[/C][C]697[/C][C]586.847[/C][C]580[/C][C]6.84722[/C][C]110.153[/C][/ROW]
[ROW][C]10[/C][C]555[/C][C]506.924[/C][C]559.042[/C][C]-52.1181[/C][C]48.0764[/C][/ROW]
[ROW][C]11[/C][C]486[/C][C]470[/C][C]539.375[/C][C]-69.375[/C][C]16[/C][/ROW]
[ROW][C]12[/C][C]470[/C][C]462.91[/C][C]516.208[/C][C]-53.2986[/C][C]7.09028[/C][/ROW]
[ROW][C]13[/C][C]465[/C][C]445.896[/C][C]487.292[/C][C]-41.3958[/C][C]19.1042[/C][/ROW]
[ROW][C]14[/C][C]426[/C][C]427.208[/C][C]457.792[/C][C]-30.5833[/C][C]-1.20833[/C][/ROW]
[ROW][C]15[/C][C]384[/C][C]466.569[/C][C]428.417[/C][C]38.1528[/C][C]-82.5694[/C][/ROW]
[ROW][C]16[/C][C]379[/C][C]431.201[/C][C]404.375[/C][C]26.8264[/C][C]-52.2014[/C][/ROW]
[ROW][C]17[/C][C]381[/C][C]484.396[/C][C]388.875[/C][C]95.5208[/C][C]-103.396[/C][/ROW]
[ROW][C]18[/C][C]380[/C][C]429.868[/C][C]376.417[/C][C]53.4514[/C][C]-49.8681[/C][/ROW]
[ROW][C]19[/C][C]351[/C][C]397.486[/C][C]364.458[/C][C]33.0278[/C][C]-46.4861[/C][/ROW]
[ROW][C]20[/C][C]346[/C][C]347.153[/C][C]354.208[/C][C]-7.05556[/C][C]-1.15278[/C][/ROW]
[ROW][C]21[/C][C]339[/C][C]353.347[/C][C]346.5[/C][C]6.84722[/C][C]-14.3472[/C][/ROW]
[ROW][C]22[/C][C]336[/C][C]289.549[/C][C]341.667[/C][C]-52.1181[/C][C]46.4514[/C][/ROW]
[ROW][C]23[/C][C]333[/C][C]271.875[/C][C]341.25[/C][C]-69.375[/C][C]61.125[/C][/ROW]
[ROW][C]24[/C][C]324[/C][C]289.41[/C][C]342.708[/C][C]-53.2986[/C][C]34.5903[/C][/ROW]
[ROW][C]25[/C][C]324[/C][C]302.104[/C][C]343.5[/C][C]-41.3958[/C][C]21.8958[/C][/ROW]
[ROW][C]26[/C][C]321[/C][C]313.625[/C][C]344.208[/C][C]-30.5833[/C][C]7.375[/C][/ROW]
[ROW][C]27[/C][C]304[/C][C]383.569[/C][C]345.417[/C][C]38.1528[/C][C]-79.5694[/C][/ROW]
[ROW][C]28[/C][C]343[/C][C]375.285[/C][C]348.458[/C][C]26.8264[/C][C]-32.2847[/C][/ROW]
[ROW][C]29[/C][C]407[/C][C]461.062[/C][C]365.542[/C][C]95.5208[/C][C]-54.0625[/C][/ROW]
[ROW][C]30[/C][C]389[/C][C]449.785[/C][C]396.333[/C][C]53.4514[/C][C]-60.7847[/C][/ROW]
[ROW][C]31[/C][C]361[/C][C]462.611[/C][C]429.583[/C][C]33.0278[/C][C]-101.611[/C][/ROW]
[ROW][C]32[/C][C]353[/C][C]456.611[/C][C]463.667[/C][C]-7.05556[/C][C]-103.611[/C][/ROW]
[ROW][C]33[/C][C]361[/C][C]509.639[/C][C]502.792[/C][C]6.84722[/C][C]-148.639[/C][/ROW]
[ROW][C]34[/C][C]387[/C][C]494.132[/C][C]546.25[/C][C]-52.1181[/C][C]-107.132[/C][/ROW]
[ROW][C]35[/C][C]692[/C][C]520.292[/C][C]589.667[/C][C]-69.375[/C][C]171.708[/C][/ROW]
[ROW][C]36[/C][C]704[/C][C]581.993[/C][C]635.292[/C][C]-53.2986[/C][C]122.007[/C][/ROW]
[ROW][C]37[/C][C]742[/C][C]641.479[/C][C]682.875[/C][C]-41.3958[/C][C]100.521[/C][/ROW]
[ROW][C]38[/C][C]721[/C][C]701.333[/C][C]731.917[/C][C]-30.5833[/C][C]19.6667[/C][/ROW]
[ROW][C]39[/C][C]843[/C][C]824.778[/C][C]786.625[/C][C]38.1528[/C][C]18.2222[/C][/ROW]
[ROW][C]40[/C][C]847[/C][C]872.16[/C][C]845.333[/C][C]26.8264[/C][C]-25.1597[/C][/ROW]
[ROW][C]41[/C][C]945[/C][C]974.854[/C][C]879.333[/C][C]95.5208[/C][C]-29.8542[/C][/ROW]
[ROW][C]42[/C][C]946[/C][C]943.451[/C][C]890[/C][C]53.4514[/C][C]2.54861[/C][/ROW]
[ROW][C]43[/C][C]946[/C][C]932.903[/C][C]899.875[/C][C]33.0278[/C][C]13.0972[/C][/ROW]
[ROW][C]44[/C][C]945[/C][C]912.736[/C][C]919.792[/C][C]-7.05556[/C][C]32.2639[/C][/ROW]
[ROW][C]45[/C][C]1082[/C][C]957.014[/C][C]950.167[/C][C]6.84722[/C][C]124.986[/C][/ROW]
[ROW][C]46[/C][C]1075[/C][C]929.382[/C][C]981.5[/C][C]-52.1181[/C][C]145.618[/C][/ROW]
[ROW][C]47[/C][C]820[/C][C]953.042[/C][C]1022.42[/C][C]-69.375[/C][C]-133.042[/C][/ROW]
[ROW][C]48[/C][C]832[/C][C]1017.91[/C][C]1071.21[/C][C]-53.2986[/C][C]-185.91[/C][/ROW]
[ROW][C]49[/C][C]851[/C][C]1076.27[/C][C]1117.67[/C][C]-41.3958[/C][C]-225.271[/C][/ROW]
[ROW][C]50[/C][C]1090[/C][C]1130.46[/C][C]1161.04[/C][C]-30.5833[/C][C]-40.4583[/C][/ROW]
[ROW][C]51[/C][C]1203[/C][C]1232.86[/C][C]1194.71[/C][C]38.1528[/C][C]-29.8611[/C][/ROW]
[ROW][C]52[/C][C]1239[/C][C]1246.83[/C][C]1220[/C][C]26.8264[/C][C]-7.82639[/C][/ROW]
[ROW][C]53[/C][C]1535[/C][C]1353.65[/C][C]1258.12[/C][C]95.5208[/C][C]181.354[/C][/ROW]
[ROW][C]54[/C][C]1527[/C][C]1359.62[/C][C]1306.17[/C][C]53.4514[/C][C]167.382[/C][/ROW]
[ROW][C]55[/C][C]1480[/C][C]1393.15[/C][C]1360.12[/C][C]33.0278[/C][C]86.8472[/C][/ROW]
[ROW][C]56[/C][C]1452[/C][C]1405.49[/C][C]1412.54[/C][C]-7.05556[/C][C]46.5139[/C][/ROW]
[ROW][C]57[/C][C]1383[/C][C]1473.85[/C][C]1467[/C][C]6.84722[/C][C]-90.8472[/C][/ROW]
[ROW][C]58[/C][C]1381[/C][C]1478.17[/C][C]1530.29[/C][C]-52.1181[/C][C]-97.1736[/C][/ROW]
[ROW][C]59[/C][C]1429[/C][C]1510.12[/C][C]1579.5[/C][C]-69.375[/C][C]-81.125[/C][/ROW]
[ROW][C]60[/C][C]1376[/C][C]1564.58[/C][C]1617.87[/C][C]-53.2986[/C][C]-188.576[/C][/ROW]
[ROW][C]61[/C][C]1602[/C][C]1622.65[/C][C]1664.04[/C][C]-41.3958[/C][C]-20.6458[/C][/ROW]
[ROW][C]62[/C][C]1597[/C][C]1688.12[/C][C]1718.71[/C][C]-30.5833[/C][C]-91.125[/C][/ROW]
[ROW][C]63[/C][C]2003[/C][C]1822.57[/C][C]1784.42[/C][C]38.1528[/C][C]180.431[/C][/ROW]
[ROW][C]64[/C][C]1958[/C][C]1885.53[/C][C]1858.71[/C][C]26.8264[/C][C]72.4653[/C][/ROW]
[ROW][C]65[/C][C]1997[/C][C]2027.1[/C][C]1931.58[/C][C]95.5208[/C][C]-30.1042[/C][/ROW]
[ROW][C]66[/C][C]1986[/C][C]2074.7[/C][C]2021.25[/C][C]53.4514[/C][C]-88.7014[/C][/ROW]
[ROW][C]67[/C][C]2129[/C][C]2149.99[/C][C]2116.96[/C][C]33.0278[/C][C]-20.9861[/C][/ROW]
[ROW][C]68[/C][C]2115[/C][C]2199.03[/C][C]2206.08[/C][C]-7.05556[/C][C]-84.0278[/C][/ROW]
[ROW][C]69[/C][C]2297[/C][C]2289.72[/C][C]2282.88[/C][C]6.84722[/C][C]7.27778[/C][/ROW]
[ROW][C]70[/C][C]2250[/C][C]2297.26[/C][C]2349.38[/C][C]-52.1181[/C][C]-47.2569[/C][/ROW]
[ROW][C]71[/C][C]2309[/C][C]2355.08[/C][C]2424.46[/C][C]-69.375[/C][C]-46.0833[/C][/ROW]
[ROW][C]72[/C][C]2648[/C][C]2448.62[/C][C]2501.92[/C][C]-53.2986[/C][C]199.382[/C][/ROW]
[ROW][C]73[/C][C]2627[/C][C]2534.02[/C][C]2575.42[/C][C]-41.3958[/C][C]92.9792[/C][/ROW]
[ROW][C]74[/C][C]2711[/C][C]2616.67[/C][C]2647.25[/C][C]-30.5833[/C][C]94.3333[/C][/ROW]
[ROW][C]75[/C][C]2732[/C][C]2750.07[/C][C]2711.92[/C][C]38.1528[/C][C]-18.0694[/C][/ROW]
[ROW][C]76[/C][C]2825[/C][C]2791.41[/C][C]2764.58[/C][C]26.8264[/C][C]33.5903[/C][/ROW]
[ROW][C]77[/C][C]2932[/C][C]2907.35[/C][C]2811.83[/C][C]95.5208[/C][C]24.6458[/C][/ROW]
[ROW][C]78[/C][C]2910[/C][C]2891.99[/C][C]2838.54[/C][C]53.4514[/C][C]18.0069[/C][/ROW]
[ROW][C]79[/C][C]2969[/C][C]NA[/C][C]NA[/C][C]33.0278[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]2999[/C][C]NA[/C][C]NA[/C][C]-7.05556[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]2965[/C][C]NA[/C][C]NA[/C][C]6.84722[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]2846[/C][C]NA[/C][C]NA[/C][C]-52.1181[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]2847[/C][C]NA[/C][C]NA[/C][C]-69.375[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]2751[/C][C]NA[/C][C]NA[/C][C]-53.2986[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230442&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230442&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
1679NANA-41.3958NA
2687NANA-30.5833NA
3638NANA38.1528NA
4628NANA26.8264NA
5604NANA95.5208NA
6713NANA53.4514NA
7712654.278621.2533.027857.7222
8693594.403601.458-7.0555698.5972
9697586.8475806.84722110.153
10555506.924559.042-52.118148.0764
11486470539.375-69.37516
12470462.91516.208-53.29867.09028
13465445.896487.292-41.395819.1042
14426427.208457.792-30.5833-1.20833
15384466.569428.41738.1528-82.5694
16379431.201404.37526.8264-52.2014
17381484.396388.87595.5208-103.396
18380429.868376.41753.4514-49.8681
19351397.486364.45833.0278-46.4861
20346347.153354.208-7.05556-1.15278
21339353.347346.56.84722-14.3472
22336289.549341.667-52.118146.4514
23333271.875341.25-69.37561.125
24324289.41342.708-53.298634.5903
25324302.104343.5-41.395821.8958
26321313.625344.208-30.58337.375
27304383.569345.41738.1528-79.5694
28343375.285348.45826.8264-32.2847
29407461.062365.54295.5208-54.0625
30389449.785396.33353.4514-60.7847
31361462.611429.58333.0278-101.611
32353456.611463.667-7.05556-103.611
33361509.639502.7926.84722-148.639
34387494.132546.25-52.1181-107.132
35692520.292589.667-69.375171.708
36704581.993635.292-53.2986122.007
37742641.479682.875-41.3958100.521
38721701.333731.917-30.583319.6667
39843824.778786.62538.152818.2222
40847872.16845.33326.8264-25.1597
41945974.854879.33395.5208-29.8542
42946943.45189053.45142.54861
43946932.903899.87533.027813.0972
44945912.736919.792-7.0555632.2639
451082957.014950.1676.84722124.986
461075929.382981.5-52.1181145.618
47820953.0421022.42-69.375-133.042
488321017.911071.21-53.2986-185.91
498511076.271117.67-41.3958-225.271
5010901130.461161.04-30.5833-40.4583
5112031232.861194.7138.1528-29.8611
5212391246.83122026.8264-7.82639
5315351353.651258.1295.5208181.354
5415271359.621306.1753.4514167.382
5514801393.151360.1233.027886.8472
5614521405.491412.54-7.0555646.5139
5713831473.8514676.84722-90.8472
5813811478.171530.29-52.1181-97.1736
5914291510.121579.5-69.375-81.125
6013761564.581617.87-53.2986-188.576
6116021622.651664.04-41.3958-20.6458
6215971688.121718.71-30.5833-91.125
6320031822.571784.4238.1528180.431
6419581885.531858.7126.826472.4653
6519972027.11931.5895.5208-30.1042
6619862074.72021.2553.4514-88.7014
6721292149.992116.9633.0278-20.9861
6821152199.032206.08-7.05556-84.0278
6922972289.722282.886.847227.27778
7022502297.262349.38-52.1181-47.2569
7123092355.082424.46-69.375-46.0833
7226482448.622501.92-53.2986199.382
7326272534.022575.42-41.395892.9792
7427112616.672647.25-30.583394.3333
7527322750.072711.9238.1528-18.0694
7628252791.412764.5826.826433.5903
7729322907.352811.8395.520824.6458
7829102891.992838.5453.451418.0069
792969NANA33.0278NA
802999NANA-7.05556NA
812965NANA6.84722NA
822846NANA-52.1181NA
832847NANA-69.375NA
842751NANA-53.2986NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- '12'
par1 <- 'multiplicative'
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')