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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationFri, 07 Dec 2012 08:26:19 -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/07/t1354886803nqyu1j8cfiejw4i.htm/, Retrieved Thu, 28 Mar 2024 09:08:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197358, Retrieved Thu, 28 Mar 2024 09:08:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [] [2012-12-07 13:03:08] [74be16979710d4c4e7c6647856088456]
- R PD    [Classical Decomposition] [] [2012-12-07 13:26:19] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
369,82
373,1
374,55
375,01
374,81
375,31
375,31
375,39
375,59
376,26
377,18
377,26
377,26
381,87
387,09
387,14
388,78
389,16
389,16
389,42
389,49
388,97
388,97
389,09
389,09
391,76
390,96
391,76
392,8
393,06
393,06
393,26
393,87
394,47
394,57
394,57
394,57
399,57
406,13
407,03
409,46
409,9
409,9
410,14
410,54
410,69
410,79
410,97
410,97
413,8
423,31
423,85
426,6
426,26
426,26
426,32
427,14
427,55
428,29
428,8
428,8
434,87
435,66
440,75
440,99
441,04
441,04
441,88
441,92
442,48
442,81
442,81




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=197358&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=197358&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197358&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
1369.82NANA0.990168789416101NA
2373.1NANA0.997916123677001NA
3374.55NANA1.00568910596935NA
4375.01NANA1.00644455780546NA
5374.81NANA1.00774720478385NA
6375.31NANA1.00548214421723NA
7375.31376.194788700908375.2758333333331.002448746457810.997648056997377
8375.39376.092150887435375.951251.000374784995220.998133034986828
9375.59376.4111209538376.8391666666670.9988641156473920.997818552885156
10376.26376.695860396311377.8670833333330.9969004367178780.998842938183998
11377.18377.104931658824378.9545833333330.9951190676776111.00019906486199
12377.26377.39400671129380.113750.9928449226351060.999644915634835
13377.26377.519591489032381.2679166666670.9901687894161010.999312376112698
14381.87381.632647379411382.4295833333330.9979161236770011.00062194003113
15387.09385.775636455801383.5933333333331.005689105969351.00340706726914
16387.14387.181318147257384.7020833333331.006444557805460.999893284760084
17388.78388.711191091907385.7229166666671.007747204783851.00017701807838
18389.16388.827067333989386.7070833333331.005482144217231.00085624868735
19389.16388.64227832307387.6929166666671.002448746457811.00133212907037
20389.42388.743557335008388.5979166666671.000374784995221.00174007427835
21389.49388.72919646664389.171250.9988641156473921.00195715562473
22388.97388.317642612531389.5250.9969004367178781.00167995814736
23388.97387.981997701485389.8850.9951190676776111.002546515829
24389.09387.422981486058390.2150.9928449226351061.00430283848301
25389.09386.700519018564390.540.9901687894161011.00617915121371
26391.76390.047990890702390.86250.9979161236770011.00438922683691
27390.96393.430606700738391.2051.005689105969350.993720349513587
28391.76394.140462912583391.6166666666671.006444557805460.99396036911564
29392.8395.116684262314392.0791666666671.007747204783850.994136708586125
30393.06394.692798792816392.5408333333331.005482144217230.99586311481281
31393.06393.959851236051392.99751.002448746457810.997715880861393
32393.26393.698747103351393.551251.000374784995220.998885576582147
33393.87394.060633683908394.508750.9988641156473920.999516232610891
34394.47394.550347217928395.7770833333330.9969004367178780.999796357502929
35394.57395.169245167787397.10750.9951190676776110.998483573367324
36394.57395.652011153165398.5033333333330.9928449226351060.997265245410957
37394.57395.975100012762399.9066666666670.9901687894161010.996451544522077
38399.57400.475382786356401.3116666666670.9979161236770010.997739229862127
39406.13405.000640827788402.7095833333331.005689105969351.00278853675368
40407.03406.684116918032404.081.006444557805461.00085049567362
41409.46408.57262881419405.4316666666671.007747204783851.00217188113747
42409.9409.020919347912406.7908333333331.005482144217231.00214923151972
43409.9409.156974232352408.15751.002448746457811.00181599194061
44410.14409.587199626038409.433751.000374784995221.00134965246587
45410.54410.275944021299410.74250.9988641156473921.00064360580373
46410.69410.881653247277412.1591666666670.9969004367178780.999533556084187
47410.79411.555539148878413.5741666666670.9951190676776110.998139888602978
48410.97412.00085754589414.970.9928449226351060.997497923785813
49410.97412.240272660237416.3333333333330.9901687894161010.996918610954627
50413.8416.818754101877417.6891666666670.9979161236770010.992757633690497
51423.31421.439048301984419.0551.005689105969351.00443943603602
52423.85423.158775625509420.4491666666671.006444557805461.0016334870368
53426.6425.149230543547421.8808333333331.007747204783851.00341237700136
54426.26425.673798410616423.3529166666671.005482144217231.00137711456888
55426.26425.879072384201424.838751.002448746457811.00089445018668
56426.32426.619413986236426.4595833333331.000374784995220.999298170743244
57427.14427.366092846644427.8520833333330.9988641156473920.999470962131932
58427.55427.740901132904429.0708333333330.9969004367178780.999553699137964
59428.29428.273954118807430.3745833333330.9951190676776111.00003746639514
60428.8428.501940160085431.590.9928449226351061.00069558574181
61428.8428.566505716392432.8216666666670.9901687894161011.00054482625332
62434.87433.1812521431434.0858333333330.9979161236770011.00389847863578
63435.66437.826752283755435.351.005689105969350.995051119484014
64440.75439.401532732792436.5879166666671.006444557805461.00306887247029
65440.99441.206842462441437.8151.007747204783850.999508524253091
66441.04441.410431869403439.003751.005482144217230.999160799467666
67441.04NANA1.00244874645781NA
68441.88NANA1.00037478499522NA
69441.92NANA0.998864115647392NA
70442.48NANA0.996900436717878NA
71442.81NANA0.995119067677611NA
72442.81NANA0.992844922635106NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 369.82 & NA & NA & 0.990168789416101 & NA \tabularnewline
2 & 373.1 & NA & NA & 0.997916123677001 & NA \tabularnewline
3 & 374.55 & NA & NA & 1.00568910596935 & NA \tabularnewline
4 & 375.01 & NA & NA & 1.00644455780546 & NA \tabularnewline
5 & 374.81 & NA & NA & 1.00774720478385 & NA \tabularnewline
6 & 375.31 & NA & NA & 1.00548214421723 & NA \tabularnewline
7 & 375.31 & 376.194788700908 & 375.275833333333 & 1.00244874645781 & 0.997648056997377 \tabularnewline
8 & 375.39 & 376.092150887435 & 375.95125 & 1.00037478499522 & 0.998133034986828 \tabularnewline
9 & 375.59 & 376.4111209538 & 376.839166666667 & 0.998864115647392 & 0.997818552885156 \tabularnewline
10 & 376.26 & 376.695860396311 & 377.867083333333 & 0.996900436717878 & 0.998842938183998 \tabularnewline
11 & 377.18 & 377.104931658824 & 378.954583333333 & 0.995119067677611 & 1.00019906486199 \tabularnewline
12 & 377.26 & 377.39400671129 & 380.11375 & 0.992844922635106 & 0.999644915634835 \tabularnewline
13 & 377.26 & 377.519591489032 & 381.267916666667 & 0.990168789416101 & 0.999312376112698 \tabularnewline
14 & 381.87 & 381.632647379411 & 382.429583333333 & 0.997916123677001 & 1.00062194003113 \tabularnewline
15 & 387.09 & 385.775636455801 & 383.593333333333 & 1.00568910596935 & 1.00340706726914 \tabularnewline
16 & 387.14 & 387.181318147257 & 384.702083333333 & 1.00644455780546 & 0.999893284760084 \tabularnewline
17 & 388.78 & 388.711191091907 & 385.722916666667 & 1.00774720478385 & 1.00017701807838 \tabularnewline
18 & 389.16 & 388.827067333989 & 386.707083333333 & 1.00548214421723 & 1.00085624868735 \tabularnewline
19 & 389.16 & 388.64227832307 & 387.692916666667 & 1.00244874645781 & 1.00133212907037 \tabularnewline
20 & 389.42 & 388.743557335008 & 388.597916666667 & 1.00037478499522 & 1.00174007427835 \tabularnewline
21 & 389.49 & 388.72919646664 & 389.17125 & 0.998864115647392 & 1.00195715562473 \tabularnewline
22 & 388.97 & 388.317642612531 & 389.525 & 0.996900436717878 & 1.00167995814736 \tabularnewline
23 & 388.97 & 387.981997701485 & 389.885 & 0.995119067677611 & 1.002546515829 \tabularnewline
24 & 389.09 & 387.422981486058 & 390.215 & 0.992844922635106 & 1.00430283848301 \tabularnewline
25 & 389.09 & 386.700519018564 & 390.54 & 0.990168789416101 & 1.00617915121371 \tabularnewline
26 & 391.76 & 390.047990890702 & 390.8625 & 0.997916123677001 & 1.00438922683691 \tabularnewline
27 & 390.96 & 393.430606700738 & 391.205 & 1.00568910596935 & 0.993720349513587 \tabularnewline
28 & 391.76 & 394.140462912583 & 391.616666666667 & 1.00644455780546 & 0.99396036911564 \tabularnewline
29 & 392.8 & 395.116684262314 & 392.079166666667 & 1.00774720478385 & 0.994136708586125 \tabularnewline
30 & 393.06 & 394.692798792816 & 392.540833333333 & 1.00548214421723 & 0.99586311481281 \tabularnewline
31 & 393.06 & 393.959851236051 & 392.9975 & 1.00244874645781 & 0.997715880861393 \tabularnewline
32 & 393.26 & 393.698747103351 & 393.55125 & 1.00037478499522 & 0.998885576582147 \tabularnewline
33 & 393.87 & 394.060633683908 & 394.50875 & 0.998864115647392 & 0.999516232610891 \tabularnewline
34 & 394.47 & 394.550347217928 & 395.777083333333 & 0.996900436717878 & 0.999796357502929 \tabularnewline
35 & 394.57 & 395.169245167787 & 397.1075 & 0.995119067677611 & 0.998483573367324 \tabularnewline
36 & 394.57 & 395.652011153165 & 398.503333333333 & 0.992844922635106 & 0.997265245410957 \tabularnewline
37 & 394.57 & 395.975100012762 & 399.906666666667 & 0.990168789416101 & 0.996451544522077 \tabularnewline
38 & 399.57 & 400.475382786356 & 401.311666666667 & 0.997916123677001 & 0.997739229862127 \tabularnewline
39 & 406.13 & 405.000640827788 & 402.709583333333 & 1.00568910596935 & 1.00278853675368 \tabularnewline
40 & 407.03 & 406.684116918032 & 404.08 & 1.00644455780546 & 1.00085049567362 \tabularnewline
41 & 409.46 & 408.57262881419 & 405.431666666667 & 1.00774720478385 & 1.00217188113747 \tabularnewline
42 & 409.9 & 409.020919347912 & 406.790833333333 & 1.00548214421723 & 1.00214923151972 \tabularnewline
43 & 409.9 & 409.156974232352 & 408.1575 & 1.00244874645781 & 1.00181599194061 \tabularnewline
44 & 410.14 & 409.587199626038 & 409.43375 & 1.00037478499522 & 1.00134965246587 \tabularnewline
45 & 410.54 & 410.275944021299 & 410.7425 & 0.998864115647392 & 1.00064360580373 \tabularnewline
46 & 410.69 & 410.881653247277 & 412.159166666667 & 0.996900436717878 & 0.999533556084187 \tabularnewline
47 & 410.79 & 411.555539148878 & 413.574166666667 & 0.995119067677611 & 0.998139888602978 \tabularnewline
48 & 410.97 & 412.00085754589 & 414.97 & 0.992844922635106 & 0.997497923785813 \tabularnewline
49 & 410.97 & 412.240272660237 & 416.333333333333 & 0.990168789416101 & 0.996918610954627 \tabularnewline
50 & 413.8 & 416.818754101877 & 417.689166666667 & 0.997916123677001 & 0.992757633690497 \tabularnewline
51 & 423.31 & 421.439048301984 & 419.055 & 1.00568910596935 & 1.00443943603602 \tabularnewline
52 & 423.85 & 423.158775625509 & 420.449166666667 & 1.00644455780546 & 1.0016334870368 \tabularnewline
53 & 426.6 & 425.149230543547 & 421.880833333333 & 1.00774720478385 & 1.00341237700136 \tabularnewline
54 & 426.26 & 425.673798410616 & 423.352916666667 & 1.00548214421723 & 1.00137711456888 \tabularnewline
55 & 426.26 & 425.879072384201 & 424.83875 & 1.00244874645781 & 1.00089445018668 \tabularnewline
56 & 426.32 & 426.619413986236 & 426.459583333333 & 1.00037478499522 & 0.999298170743244 \tabularnewline
57 & 427.14 & 427.366092846644 & 427.852083333333 & 0.998864115647392 & 0.999470962131932 \tabularnewline
58 & 427.55 & 427.740901132904 & 429.070833333333 & 0.996900436717878 & 0.999553699137964 \tabularnewline
59 & 428.29 & 428.273954118807 & 430.374583333333 & 0.995119067677611 & 1.00003746639514 \tabularnewline
60 & 428.8 & 428.501940160085 & 431.59 & 0.992844922635106 & 1.00069558574181 \tabularnewline
61 & 428.8 & 428.566505716392 & 432.821666666667 & 0.990168789416101 & 1.00054482625332 \tabularnewline
62 & 434.87 & 433.1812521431 & 434.085833333333 & 0.997916123677001 & 1.00389847863578 \tabularnewline
63 & 435.66 & 437.826752283755 & 435.35 & 1.00568910596935 & 0.995051119484014 \tabularnewline
64 & 440.75 & 439.401532732792 & 436.587916666667 & 1.00644455780546 & 1.00306887247029 \tabularnewline
65 & 440.99 & 441.206842462441 & 437.815 & 1.00774720478385 & 0.999508524253091 \tabularnewline
66 & 441.04 & 441.410431869403 & 439.00375 & 1.00548214421723 & 0.999160799467666 \tabularnewline
67 & 441.04 & NA & NA & 1.00244874645781 & NA \tabularnewline
68 & 441.88 & NA & NA & 1.00037478499522 & NA \tabularnewline
69 & 441.92 & NA & NA & 0.998864115647392 & NA \tabularnewline
70 & 442.48 & NA & NA & 0.996900436717878 & NA \tabularnewline
71 & 442.81 & NA & NA & 0.995119067677611 & NA \tabularnewline
72 & 442.81 & NA & NA & 0.992844922635106 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197358&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]369.82[/C][C]NA[/C][C]NA[/C][C]0.990168789416101[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]373.1[/C][C]NA[/C][C]NA[/C][C]0.997916123677001[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]374.55[/C][C]NA[/C][C]NA[/C][C]1.00568910596935[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]375.01[/C][C]NA[/C][C]NA[/C][C]1.00644455780546[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]374.81[/C][C]NA[/C][C]NA[/C][C]1.00774720478385[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]375.31[/C][C]NA[/C][C]NA[/C][C]1.00548214421723[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]375.31[/C][C]376.194788700908[/C][C]375.275833333333[/C][C]1.00244874645781[/C][C]0.997648056997377[/C][/ROW]
[ROW][C]8[/C][C]375.39[/C][C]376.092150887435[/C][C]375.95125[/C][C]1.00037478499522[/C][C]0.998133034986828[/C][/ROW]
[ROW][C]9[/C][C]375.59[/C][C]376.4111209538[/C][C]376.839166666667[/C][C]0.998864115647392[/C][C]0.997818552885156[/C][/ROW]
[ROW][C]10[/C][C]376.26[/C][C]376.695860396311[/C][C]377.867083333333[/C][C]0.996900436717878[/C][C]0.998842938183998[/C][/ROW]
[ROW][C]11[/C][C]377.18[/C][C]377.104931658824[/C][C]378.954583333333[/C][C]0.995119067677611[/C][C]1.00019906486199[/C][/ROW]
[ROW][C]12[/C][C]377.26[/C][C]377.39400671129[/C][C]380.11375[/C][C]0.992844922635106[/C][C]0.999644915634835[/C][/ROW]
[ROW][C]13[/C][C]377.26[/C][C]377.519591489032[/C][C]381.267916666667[/C][C]0.990168789416101[/C][C]0.999312376112698[/C][/ROW]
[ROW][C]14[/C][C]381.87[/C][C]381.632647379411[/C][C]382.429583333333[/C][C]0.997916123677001[/C][C]1.00062194003113[/C][/ROW]
[ROW][C]15[/C][C]387.09[/C][C]385.775636455801[/C][C]383.593333333333[/C][C]1.00568910596935[/C][C]1.00340706726914[/C][/ROW]
[ROW][C]16[/C][C]387.14[/C][C]387.181318147257[/C][C]384.702083333333[/C][C]1.00644455780546[/C][C]0.999893284760084[/C][/ROW]
[ROW][C]17[/C][C]388.78[/C][C]388.711191091907[/C][C]385.722916666667[/C][C]1.00774720478385[/C][C]1.00017701807838[/C][/ROW]
[ROW][C]18[/C][C]389.16[/C][C]388.827067333989[/C][C]386.707083333333[/C][C]1.00548214421723[/C][C]1.00085624868735[/C][/ROW]
[ROW][C]19[/C][C]389.16[/C][C]388.64227832307[/C][C]387.692916666667[/C][C]1.00244874645781[/C][C]1.00133212907037[/C][/ROW]
[ROW][C]20[/C][C]389.42[/C][C]388.743557335008[/C][C]388.597916666667[/C][C]1.00037478499522[/C][C]1.00174007427835[/C][/ROW]
[ROW][C]21[/C][C]389.49[/C][C]388.72919646664[/C][C]389.17125[/C][C]0.998864115647392[/C][C]1.00195715562473[/C][/ROW]
[ROW][C]22[/C][C]388.97[/C][C]388.317642612531[/C][C]389.525[/C][C]0.996900436717878[/C][C]1.00167995814736[/C][/ROW]
[ROW][C]23[/C][C]388.97[/C][C]387.981997701485[/C][C]389.885[/C][C]0.995119067677611[/C][C]1.002546515829[/C][/ROW]
[ROW][C]24[/C][C]389.09[/C][C]387.422981486058[/C][C]390.215[/C][C]0.992844922635106[/C][C]1.00430283848301[/C][/ROW]
[ROW][C]25[/C][C]389.09[/C][C]386.700519018564[/C][C]390.54[/C][C]0.990168789416101[/C][C]1.00617915121371[/C][/ROW]
[ROW][C]26[/C][C]391.76[/C][C]390.047990890702[/C][C]390.8625[/C][C]0.997916123677001[/C][C]1.00438922683691[/C][/ROW]
[ROW][C]27[/C][C]390.96[/C][C]393.430606700738[/C][C]391.205[/C][C]1.00568910596935[/C][C]0.993720349513587[/C][/ROW]
[ROW][C]28[/C][C]391.76[/C][C]394.140462912583[/C][C]391.616666666667[/C][C]1.00644455780546[/C][C]0.99396036911564[/C][/ROW]
[ROW][C]29[/C][C]392.8[/C][C]395.116684262314[/C][C]392.079166666667[/C][C]1.00774720478385[/C][C]0.994136708586125[/C][/ROW]
[ROW][C]30[/C][C]393.06[/C][C]394.692798792816[/C][C]392.540833333333[/C][C]1.00548214421723[/C][C]0.99586311481281[/C][/ROW]
[ROW][C]31[/C][C]393.06[/C][C]393.959851236051[/C][C]392.9975[/C][C]1.00244874645781[/C][C]0.997715880861393[/C][/ROW]
[ROW][C]32[/C][C]393.26[/C][C]393.698747103351[/C][C]393.55125[/C][C]1.00037478499522[/C][C]0.998885576582147[/C][/ROW]
[ROW][C]33[/C][C]393.87[/C][C]394.060633683908[/C][C]394.50875[/C][C]0.998864115647392[/C][C]0.999516232610891[/C][/ROW]
[ROW][C]34[/C][C]394.47[/C][C]394.550347217928[/C][C]395.777083333333[/C][C]0.996900436717878[/C][C]0.999796357502929[/C][/ROW]
[ROW][C]35[/C][C]394.57[/C][C]395.169245167787[/C][C]397.1075[/C][C]0.995119067677611[/C][C]0.998483573367324[/C][/ROW]
[ROW][C]36[/C][C]394.57[/C][C]395.652011153165[/C][C]398.503333333333[/C][C]0.992844922635106[/C][C]0.997265245410957[/C][/ROW]
[ROW][C]37[/C][C]394.57[/C][C]395.975100012762[/C][C]399.906666666667[/C][C]0.990168789416101[/C][C]0.996451544522077[/C][/ROW]
[ROW][C]38[/C][C]399.57[/C][C]400.475382786356[/C][C]401.311666666667[/C][C]0.997916123677001[/C][C]0.997739229862127[/C][/ROW]
[ROW][C]39[/C][C]406.13[/C][C]405.000640827788[/C][C]402.709583333333[/C][C]1.00568910596935[/C][C]1.00278853675368[/C][/ROW]
[ROW][C]40[/C][C]407.03[/C][C]406.684116918032[/C][C]404.08[/C][C]1.00644455780546[/C][C]1.00085049567362[/C][/ROW]
[ROW][C]41[/C][C]409.46[/C][C]408.57262881419[/C][C]405.431666666667[/C][C]1.00774720478385[/C][C]1.00217188113747[/C][/ROW]
[ROW][C]42[/C][C]409.9[/C][C]409.020919347912[/C][C]406.790833333333[/C][C]1.00548214421723[/C][C]1.00214923151972[/C][/ROW]
[ROW][C]43[/C][C]409.9[/C][C]409.156974232352[/C][C]408.1575[/C][C]1.00244874645781[/C][C]1.00181599194061[/C][/ROW]
[ROW][C]44[/C][C]410.14[/C][C]409.587199626038[/C][C]409.43375[/C][C]1.00037478499522[/C][C]1.00134965246587[/C][/ROW]
[ROW][C]45[/C][C]410.54[/C][C]410.275944021299[/C][C]410.7425[/C][C]0.998864115647392[/C][C]1.00064360580373[/C][/ROW]
[ROW][C]46[/C][C]410.69[/C][C]410.881653247277[/C][C]412.159166666667[/C][C]0.996900436717878[/C][C]0.999533556084187[/C][/ROW]
[ROW][C]47[/C][C]410.79[/C][C]411.555539148878[/C][C]413.574166666667[/C][C]0.995119067677611[/C][C]0.998139888602978[/C][/ROW]
[ROW][C]48[/C][C]410.97[/C][C]412.00085754589[/C][C]414.97[/C][C]0.992844922635106[/C][C]0.997497923785813[/C][/ROW]
[ROW][C]49[/C][C]410.97[/C][C]412.240272660237[/C][C]416.333333333333[/C][C]0.990168789416101[/C][C]0.996918610954627[/C][/ROW]
[ROW][C]50[/C][C]413.8[/C][C]416.818754101877[/C][C]417.689166666667[/C][C]0.997916123677001[/C][C]0.992757633690497[/C][/ROW]
[ROW][C]51[/C][C]423.31[/C][C]421.439048301984[/C][C]419.055[/C][C]1.00568910596935[/C][C]1.00443943603602[/C][/ROW]
[ROW][C]52[/C][C]423.85[/C][C]423.158775625509[/C][C]420.449166666667[/C][C]1.00644455780546[/C][C]1.0016334870368[/C][/ROW]
[ROW][C]53[/C][C]426.6[/C][C]425.149230543547[/C][C]421.880833333333[/C][C]1.00774720478385[/C][C]1.00341237700136[/C][/ROW]
[ROW][C]54[/C][C]426.26[/C][C]425.673798410616[/C][C]423.352916666667[/C][C]1.00548214421723[/C][C]1.00137711456888[/C][/ROW]
[ROW][C]55[/C][C]426.26[/C][C]425.879072384201[/C][C]424.83875[/C][C]1.00244874645781[/C][C]1.00089445018668[/C][/ROW]
[ROW][C]56[/C][C]426.32[/C][C]426.619413986236[/C][C]426.459583333333[/C][C]1.00037478499522[/C][C]0.999298170743244[/C][/ROW]
[ROW][C]57[/C][C]427.14[/C][C]427.366092846644[/C][C]427.852083333333[/C][C]0.998864115647392[/C][C]0.999470962131932[/C][/ROW]
[ROW][C]58[/C][C]427.55[/C][C]427.740901132904[/C][C]429.070833333333[/C][C]0.996900436717878[/C][C]0.999553699137964[/C][/ROW]
[ROW][C]59[/C][C]428.29[/C][C]428.273954118807[/C][C]430.374583333333[/C][C]0.995119067677611[/C][C]1.00003746639514[/C][/ROW]
[ROW][C]60[/C][C]428.8[/C][C]428.501940160085[/C][C]431.59[/C][C]0.992844922635106[/C][C]1.00069558574181[/C][/ROW]
[ROW][C]61[/C][C]428.8[/C][C]428.566505716392[/C][C]432.821666666667[/C][C]0.990168789416101[/C][C]1.00054482625332[/C][/ROW]
[ROW][C]62[/C][C]434.87[/C][C]433.1812521431[/C][C]434.085833333333[/C][C]0.997916123677001[/C][C]1.00389847863578[/C][/ROW]
[ROW][C]63[/C][C]435.66[/C][C]437.826752283755[/C][C]435.35[/C][C]1.00568910596935[/C][C]0.995051119484014[/C][/ROW]
[ROW][C]64[/C][C]440.75[/C][C]439.401532732792[/C][C]436.587916666667[/C][C]1.00644455780546[/C][C]1.00306887247029[/C][/ROW]
[ROW][C]65[/C][C]440.99[/C][C]441.206842462441[/C][C]437.815[/C][C]1.00774720478385[/C][C]0.999508524253091[/C][/ROW]
[ROW][C]66[/C][C]441.04[/C][C]441.410431869403[/C][C]439.00375[/C][C]1.00548214421723[/C][C]0.999160799467666[/C][/ROW]
[ROW][C]67[/C][C]441.04[/C][C]NA[/C][C]NA[/C][C]1.00244874645781[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]441.88[/C][C]NA[/C][C]NA[/C][C]1.00037478499522[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]441.92[/C][C]NA[/C][C]NA[/C][C]0.998864115647392[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]442.48[/C][C]NA[/C][C]NA[/C][C]0.996900436717878[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]442.81[/C][C]NA[/C][C]NA[/C][C]0.995119067677611[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]442.81[/C][C]NA[/C][C]NA[/C][C]0.992844922635106[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197358&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197358&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
1369.82NANA0.990168789416101NA
2373.1NANA0.997916123677001NA
3374.55NANA1.00568910596935NA
4375.01NANA1.00644455780546NA
5374.81NANA1.00774720478385NA
6375.31NANA1.00548214421723NA
7375.31376.194788700908375.2758333333331.002448746457810.997648056997377
8375.39376.092150887435375.951251.000374784995220.998133034986828
9375.59376.4111209538376.8391666666670.9988641156473920.997818552885156
10376.26376.695860396311377.8670833333330.9969004367178780.998842938183998
11377.18377.104931658824378.9545833333330.9951190676776111.00019906486199
12377.26377.39400671129380.113750.9928449226351060.999644915634835
13377.26377.519591489032381.2679166666670.9901687894161010.999312376112698
14381.87381.632647379411382.4295833333330.9979161236770011.00062194003113
15387.09385.775636455801383.5933333333331.005689105969351.00340706726914
16387.14387.181318147257384.7020833333331.006444557805460.999893284760084
17388.78388.711191091907385.7229166666671.007747204783851.00017701807838
18389.16388.827067333989386.7070833333331.005482144217231.00085624868735
19389.16388.64227832307387.6929166666671.002448746457811.00133212907037
20389.42388.743557335008388.5979166666671.000374784995221.00174007427835
21389.49388.72919646664389.171250.9988641156473921.00195715562473
22388.97388.317642612531389.5250.9969004367178781.00167995814736
23388.97387.981997701485389.8850.9951190676776111.002546515829
24389.09387.422981486058390.2150.9928449226351061.00430283848301
25389.09386.700519018564390.540.9901687894161011.00617915121371
26391.76390.047990890702390.86250.9979161236770011.00438922683691
27390.96393.430606700738391.2051.005689105969350.993720349513587
28391.76394.140462912583391.6166666666671.006444557805460.99396036911564
29392.8395.116684262314392.0791666666671.007747204783850.994136708586125
30393.06394.692798792816392.5408333333331.005482144217230.99586311481281
31393.06393.959851236051392.99751.002448746457810.997715880861393
32393.26393.698747103351393.551251.000374784995220.998885576582147
33393.87394.060633683908394.508750.9988641156473920.999516232610891
34394.47394.550347217928395.7770833333330.9969004367178780.999796357502929
35394.57395.169245167787397.10750.9951190676776110.998483573367324
36394.57395.652011153165398.5033333333330.9928449226351060.997265245410957
37394.57395.975100012762399.9066666666670.9901687894161010.996451544522077
38399.57400.475382786356401.3116666666670.9979161236770010.997739229862127
39406.13405.000640827788402.7095833333331.005689105969351.00278853675368
40407.03406.684116918032404.081.006444557805461.00085049567362
41409.46408.57262881419405.4316666666671.007747204783851.00217188113747
42409.9409.020919347912406.7908333333331.005482144217231.00214923151972
43409.9409.156974232352408.15751.002448746457811.00181599194061
44410.14409.587199626038409.433751.000374784995221.00134965246587
45410.54410.275944021299410.74250.9988641156473921.00064360580373
46410.69410.881653247277412.1591666666670.9969004367178780.999533556084187
47410.79411.555539148878413.5741666666670.9951190676776110.998139888602978
48410.97412.00085754589414.970.9928449226351060.997497923785813
49410.97412.240272660237416.3333333333330.9901687894161010.996918610954627
50413.8416.818754101877417.6891666666670.9979161236770010.992757633690497
51423.31421.439048301984419.0551.005689105969351.00443943603602
52423.85423.158775625509420.4491666666671.006444557805461.0016334870368
53426.6425.149230543547421.8808333333331.007747204783851.00341237700136
54426.26425.673798410616423.3529166666671.005482144217231.00137711456888
55426.26425.879072384201424.838751.002448746457811.00089445018668
56426.32426.619413986236426.4595833333331.000374784995220.999298170743244
57427.14427.366092846644427.8520833333330.9988641156473920.999470962131932
58427.55427.740901132904429.0708333333330.9969004367178780.999553699137964
59428.29428.273954118807430.3745833333330.9951190676776111.00003746639514
60428.8428.501940160085431.590.9928449226351061.00069558574181
61428.8428.566505716392432.8216666666670.9901687894161011.00054482625332
62434.87433.1812521431434.0858333333330.9979161236770011.00389847863578
63435.66437.826752283755435.351.005689105969350.995051119484014
64440.75439.401532732792436.5879166666671.006444557805461.00306887247029
65440.99441.206842462441437.8151.007747204783850.999508524253091
66441.04441.410431869403439.003751.005482144217230.999160799467666
67441.04NANA1.00244874645781NA
68441.88NANA1.00037478499522NA
69441.92NANA0.998864115647392NA
70442.48NANA0.996900436717878NA
71442.81NANA0.995119067677611NA
72442.81NANA0.992844922635106NA



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