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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSat, 31 May 2008 07:56:15 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/31/t12122422328u5oz0a47z4yp8m.htm/, Retrieved Wed, 15 May 2024 04:09:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13601, Retrieved Wed, 15 May 2024 04:09:45 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Classical decompo...] [2008-05-31 13:56:15] [3e68c9212ad297cb41373898449ccda3] [Current]
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Dataseries X:
68,4
70,6
83,9
90,1
90,6
87,1
90,8
94,1
99,8
96,8
87
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147
145,8
164,4
149,8
137,7
151,7
156,8
180
180,4
170,4
191,6
199,5
218,2
217,5
205
194
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253
218,2
203,7
205,6
215,6
188,5
202,9
214
230,3
230
241
259,6
247,8
270,3
289,7
322,7
315
320,2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13601&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13601&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13601&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 time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
168.4NANA1.00303776605987NA
270.6NANA0.999525670381087NA
383.9NANA1.01224647878114NA
490.1NANA0.985604024462152NA
590.6NANA0.98701818727222NA
687.1NANA1.00337907906274NA
790.892.95266682962189.57083333333331.037755967768020.976841257996752
894.1100.71923429984493.04166666666671.082517520464060.934280335371314
999.896.069900308539695.8251.002555703715521.03882693413318
1096.896.93079304628196.7251.002127609679820.998650655357595
118791.784906886911796.72916666666670.9488855331836660.947868260161693
1296.390.911778554382297.19583333333330.9353464591697051.05926868367661
13107.198.343673638144698.04583333333331.003037766059871.08903802388016
14115.298.848924110396398.89583333333330.9995256703810871.16541480887888
15106.1100.33471451551999.12083333333331.012246478781141.05746052612319
1689.597.689785557940399.11666666666660.9856040244621520.916165385038307
1791.398.673030696759899.97083333333330.987018187272220.925278157114496
1897.6101.332925493012100.9916666666671.003379079062740.963161771212566
19100.7105.332230728454101.51.037755967768020.956022665651167
20104.6109.776297554393101.4083333333331.082517520464060.952846856109095
2194.7101.909787282682101.651.002555703715520.92925323980234
22101.8103.557361865289103.33751.002127609679820.983030063400273
23102.5100.795365762435106.2250.9488855331836661.01691183145843
24105.3102.019017757022109.0708333333330.9353464591697051.03216049629876
25110.3111.939014692281111.61.003037766059870.985357967489827
26109.8114.662253153884114.7166666666670.9995256703810870.95759499730606
27117.3120.065085464428118.61251.012246478781140.976970112054376
28118.8121.574256417407123.350.9856040244621520.977180560266957
29131.3126.268414182579127.9291666666670.987018187272221.03984833301340
30125.9131.693504126985131.251.003379079062740.956007669737463
31133.1139.396570370439134.3251.037755967768020.95482980425052
32147149.396438803378138.0083333333331.082517520464060.983959197270212
33145.8142.943556772672142.5791666666671.002555703715521.01998301491735
34164.4148.072705393608147.7583333333331.002127609679821.11026538998521
35149.8144.187110456980151.9541666666670.9488855331836661.03892781764772
36137.7146.214137952791156.3208333333330.9353464591697050.941769393356886
37151.7162.316586492638161.8251.003037766059870.934593335640906
38156.8167.478855452938167.5583333333330.9995256703810870.936237589968852
39180175.637417149512173.51251.012246478781141.02483857324533
40180.4175.626423792285178.1916666666670.9856040244621521.02718028474668
41170.4179.365880082044181.7250.987018187272220.950013458089448
42191.6186.762292582879186.1333333333331.003379079062741.02590302009157
43199.5198.747563760371191.5166666666671.037755967768021.00378588912182
44218.2212.818434033566196.5958333333331.082517520464061.02528712322723
45217.5200.836971346811200.3251.002555703715521.08296793434718
46205204.71796853076204.2833333333331.002127609679821.00137765859667
47194199.044555344160209.7666666666670.9488855331836660.974656150049228
48199.3200.916316706566214.8041666666670.9353464591697050.991955274051104
49219.3219.844981700196219.1791666666671.003037766059870.997521063724167
50211.1222.85257759205222.9583333333330.9995256703810870.94726299458127
51215.2227.186069081441224.43751.012246478781140.947241179312167
52240.2221.181863139613224.41250.9856040244621521.08598416068311
53242.2221.922814256598224.8416666666670.987018187272221.09137044251772
54240.7226.767852614343226.0041666666671.003379079062741.06143792969346
55255.4233.910195134911225.41.037755967768021.09187203171155
56253242.240358141846223.7751.082517520464061.04441721412851
57218.2223.954234948318223.3833333333331.002555703715520.974306201668183
58203.7223.395121856168222.9208333333331.002127609679820.911837278752897
59205.6210.6525883667742220.9488855331836660.976014591579683
60215.6207.183137983003221.5041666666670.9353464591697051.04062522702831
61188.5222.365114087422221.6916666666671.003037766059870.8477049143864
62202.9221.544864839968221.650.9995256703810870.915841584261337
63214226.342530349124223.6041666666671.012246478781140.945469681150574
64230.3226.056496377265229.3583333333330.9856040244621521.01877187203527
65230234.733487812235237.8208333333330.987018187272220.97983462923696
66241247.675764174313246.8416666666671.003379079062740.973046356810211
67259.6266.154137850103256.4708333333331.037755967768020.975374653563364
68247.8NANA1.08251752046406NA
69270.3NANA1.00255570371552NA
70289.7NANA1.00212760967982NA
71322.7NANA0.948885533183666NA
72315NANA0.935346459169705NA
73320.2NANANANA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 68.4 & NA & NA & 1.00303776605987 & NA \tabularnewline
2 & 70.6 & NA & NA & 0.999525670381087 & NA \tabularnewline
3 & 83.9 & NA & NA & 1.01224647878114 & NA \tabularnewline
4 & 90.1 & NA & NA & 0.985604024462152 & NA \tabularnewline
5 & 90.6 & NA & NA & 0.98701818727222 & NA \tabularnewline
6 & 87.1 & NA & NA & 1.00337907906274 & NA \tabularnewline
7 & 90.8 & 92.952666829621 & 89.5708333333333 & 1.03775596776802 & 0.976841257996752 \tabularnewline
8 & 94.1 & 100.719234299844 & 93.0416666666667 & 1.08251752046406 & 0.934280335371314 \tabularnewline
9 & 99.8 & 96.0699003085396 & 95.825 & 1.00255570371552 & 1.03882693413318 \tabularnewline
10 & 96.8 & 96.930793046281 & 96.725 & 1.00212760967982 & 0.998650655357595 \tabularnewline
11 & 87 & 91.7849068869117 & 96.7291666666667 & 0.948885533183666 & 0.947868260161693 \tabularnewline
12 & 96.3 & 90.9117785543822 & 97.1958333333333 & 0.935346459169705 & 1.05926868367661 \tabularnewline
13 & 107.1 & 98.3436736381446 & 98.0458333333333 & 1.00303776605987 & 1.08903802388016 \tabularnewline
14 & 115.2 & 98.8489241103963 & 98.8958333333333 & 0.999525670381087 & 1.16541480887888 \tabularnewline
15 & 106.1 & 100.334714515519 & 99.1208333333333 & 1.01224647878114 & 1.05746052612319 \tabularnewline
16 & 89.5 & 97.6897855579403 & 99.1166666666666 & 0.985604024462152 & 0.916165385038307 \tabularnewline
17 & 91.3 & 98.6730306967598 & 99.9708333333333 & 0.98701818727222 & 0.925278157114496 \tabularnewline
18 & 97.6 & 101.332925493012 & 100.991666666667 & 1.00337907906274 & 0.963161771212566 \tabularnewline
19 & 100.7 & 105.332230728454 & 101.5 & 1.03775596776802 & 0.956022665651167 \tabularnewline
20 & 104.6 & 109.776297554393 & 101.408333333333 & 1.08251752046406 & 0.952846856109095 \tabularnewline
21 & 94.7 & 101.909787282682 & 101.65 & 1.00255570371552 & 0.92925323980234 \tabularnewline
22 & 101.8 & 103.557361865289 & 103.3375 & 1.00212760967982 & 0.983030063400273 \tabularnewline
23 & 102.5 & 100.795365762435 & 106.225 & 0.948885533183666 & 1.01691183145843 \tabularnewline
24 & 105.3 & 102.019017757022 & 109.070833333333 & 0.935346459169705 & 1.03216049629876 \tabularnewline
25 & 110.3 & 111.939014692281 & 111.6 & 1.00303776605987 & 0.985357967489827 \tabularnewline
26 & 109.8 & 114.662253153884 & 114.716666666667 & 0.999525670381087 & 0.95759499730606 \tabularnewline
27 & 117.3 & 120.065085464428 & 118.6125 & 1.01224647878114 & 0.976970112054376 \tabularnewline
28 & 118.8 & 121.574256417407 & 123.35 & 0.985604024462152 & 0.977180560266957 \tabularnewline
29 & 131.3 & 126.268414182579 & 127.929166666667 & 0.98701818727222 & 1.03984833301340 \tabularnewline
30 & 125.9 & 131.693504126985 & 131.25 & 1.00337907906274 & 0.956007669737463 \tabularnewline
31 & 133.1 & 139.396570370439 & 134.325 & 1.03775596776802 & 0.95482980425052 \tabularnewline
32 & 147 & 149.396438803378 & 138.008333333333 & 1.08251752046406 & 0.983959197270212 \tabularnewline
33 & 145.8 & 142.943556772672 & 142.579166666667 & 1.00255570371552 & 1.01998301491735 \tabularnewline
34 & 164.4 & 148.072705393608 & 147.758333333333 & 1.00212760967982 & 1.11026538998521 \tabularnewline
35 & 149.8 & 144.187110456980 & 151.954166666667 & 0.948885533183666 & 1.03892781764772 \tabularnewline
36 & 137.7 & 146.214137952791 & 156.320833333333 & 0.935346459169705 & 0.941769393356886 \tabularnewline
37 & 151.7 & 162.316586492638 & 161.825 & 1.00303776605987 & 0.934593335640906 \tabularnewline
38 & 156.8 & 167.478855452938 & 167.558333333333 & 0.999525670381087 & 0.936237589968852 \tabularnewline
39 & 180 & 175.637417149512 & 173.5125 & 1.01224647878114 & 1.02483857324533 \tabularnewline
40 & 180.4 & 175.626423792285 & 178.191666666667 & 0.985604024462152 & 1.02718028474668 \tabularnewline
41 & 170.4 & 179.365880082044 & 181.725 & 0.98701818727222 & 0.950013458089448 \tabularnewline
42 & 191.6 & 186.762292582879 & 186.133333333333 & 1.00337907906274 & 1.02590302009157 \tabularnewline
43 & 199.5 & 198.747563760371 & 191.516666666667 & 1.03775596776802 & 1.00378588912182 \tabularnewline
44 & 218.2 & 212.818434033566 & 196.595833333333 & 1.08251752046406 & 1.02528712322723 \tabularnewline
45 & 217.5 & 200.836971346811 & 200.325 & 1.00255570371552 & 1.08296793434718 \tabularnewline
46 & 205 & 204.71796853076 & 204.283333333333 & 1.00212760967982 & 1.00137765859667 \tabularnewline
47 & 194 & 199.044555344160 & 209.766666666667 & 0.948885533183666 & 0.974656150049228 \tabularnewline
48 & 199.3 & 200.916316706566 & 214.804166666667 & 0.935346459169705 & 0.991955274051104 \tabularnewline
49 & 219.3 & 219.844981700196 & 219.179166666667 & 1.00303776605987 & 0.997521063724167 \tabularnewline
50 & 211.1 & 222.85257759205 & 222.958333333333 & 0.999525670381087 & 0.94726299458127 \tabularnewline
51 & 215.2 & 227.186069081441 & 224.4375 & 1.01224647878114 & 0.947241179312167 \tabularnewline
52 & 240.2 & 221.181863139613 & 224.4125 & 0.985604024462152 & 1.08598416068311 \tabularnewline
53 & 242.2 & 221.922814256598 & 224.841666666667 & 0.98701818727222 & 1.09137044251772 \tabularnewline
54 & 240.7 & 226.767852614343 & 226.004166666667 & 1.00337907906274 & 1.06143792969346 \tabularnewline
55 & 255.4 & 233.910195134911 & 225.4 & 1.03775596776802 & 1.09187203171155 \tabularnewline
56 & 253 & 242.240358141846 & 223.775 & 1.08251752046406 & 1.04441721412851 \tabularnewline
57 & 218.2 & 223.954234948318 & 223.383333333333 & 1.00255570371552 & 0.974306201668183 \tabularnewline
58 & 203.7 & 223.395121856168 & 222.920833333333 & 1.00212760967982 & 0.911837278752897 \tabularnewline
59 & 205.6 & 210.652588366774 & 222 & 0.948885533183666 & 0.976014591579683 \tabularnewline
60 & 215.6 & 207.183137983003 & 221.504166666667 & 0.935346459169705 & 1.04062522702831 \tabularnewline
61 & 188.5 & 222.365114087422 & 221.691666666667 & 1.00303776605987 & 0.8477049143864 \tabularnewline
62 & 202.9 & 221.544864839968 & 221.65 & 0.999525670381087 & 0.915841584261337 \tabularnewline
63 & 214 & 226.342530349124 & 223.604166666667 & 1.01224647878114 & 0.945469681150574 \tabularnewline
64 & 230.3 & 226.056496377265 & 229.358333333333 & 0.985604024462152 & 1.01877187203527 \tabularnewline
65 & 230 & 234.733487812235 & 237.820833333333 & 0.98701818727222 & 0.97983462923696 \tabularnewline
66 & 241 & 247.675764174313 & 246.841666666667 & 1.00337907906274 & 0.973046356810211 \tabularnewline
67 & 259.6 & 266.154137850103 & 256.470833333333 & 1.03775596776802 & 0.975374653563364 \tabularnewline
68 & 247.8 & NA & NA & 1.08251752046406 & NA \tabularnewline
69 & 270.3 & NA & NA & 1.00255570371552 & NA \tabularnewline
70 & 289.7 & NA & NA & 1.00212760967982 & NA \tabularnewline
71 & 322.7 & NA & NA & 0.948885533183666 & NA \tabularnewline
72 & 315 & NA & NA & 0.935346459169705 & NA \tabularnewline
73 & 320.2 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13601&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]68.4[/C][C]NA[/C][C]NA[/C][C]1.00303776605987[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]70.6[/C][C]NA[/C][C]NA[/C][C]0.999525670381087[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]83.9[/C][C]NA[/C][C]NA[/C][C]1.01224647878114[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]90.1[/C][C]NA[/C][C]NA[/C][C]0.985604024462152[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]90.6[/C][C]NA[/C][C]NA[/C][C]0.98701818727222[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]87.1[/C][C]NA[/C][C]NA[/C][C]1.00337907906274[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]90.8[/C][C]92.952666829621[/C][C]89.5708333333333[/C][C]1.03775596776802[/C][C]0.976841257996752[/C][/ROW]
[ROW][C]8[/C][C]94.1[/C][C]100.719234299844[/C][C]93.0416666666667[/C][C]1.08251752046406[/C][C]0.934280335371314[/C][/ROW]
[ROW][C]9[/C][C]99.8[/C][C]96.0699003085396[/C][C]95.825[/C][C]1.00255570371552[/C][C]1.03882693413318[/C][/ROW]
[ROW][C]10[/C][C]96.8[/C][C]96.930793046281[/C][C]96.725[/C][C]1.00212760967982[/C][C]0.998650655357595[/C][/ROW]
[ROW][C]11[/C][C]87[/C][C]91.7849068869117[/C][C]96.7291666666667[/C][C]0.948885533183666[/C][C]0.947868260161693[/C][/ROW]
[ROW][C]12[/C][C]96.3[/C][C]90.9117785543822[/C][C]97.1958333333333[/C][C]0.935346459169705[/C][C]1.05926868367661[/C][/ROW]
[ROW][C]13[/C][C]107.1[/C][C]98.3436736381446[/C][C]98.0458333333333[/C][C]1.00303776605987[/C][C]1.08903802388016[/C][/ROW]
[ROW][C]14[/C][C]115.2[/C][C]98.8489241103963[/C][C]98.8958333333333[/C][C]0.999525670381087[/C][C]1.16541480887888[/C][/ROW]
[ROW][C]15[/C][C]106.1[/C][C]100.334714515519[/C][C]99.1208333333333[/C][C]1.01224647878114[/C][C]1.05746052612319[/C][/ROW]
[ROW][C]16[/C][C]89.5[/C][C]97.6897855579403[/C][C]99.1166666666666[/C][C]0.985604024462152[/C][C]0.916165385038307[/C][/ROW]
[ROW][C]17[/C][C]91.3[/C][C]98.6730306967598[/C][C]99.9708333333333[/C][C]0.98701818727222[/C][C]0.925278157114496[/C][/ROW]
[ROW][C]18[/C][C]97.6[/C][C]101.332925493012[/C][C]100.991666666667[/C][C]1.00337907906274[/C][C]0.963161771212566[/C][/ROW]
[ROW][C]19[/C][C]100.7[/C][C]105.332230728454[/C][C]101.5[/C][C]1.03775596776802[/C][C]0.956022665651167[/C][/ROW]
[ROW][C]20[/C][C]104.6[/C][C]109.776297554393[/C][C]101.408333333333[/C][C]1.08251752046406[/C][C]0.952846856109095[/C][/ROW]
[ROW][C]21[/C][C]94.7[/C][C]101.909787282682[/C][C]101.65[/C][C]1.00255570371552[/C][C]0.92925323980234[/C][/ROW]
[ROW][C]22[/C][C]101.8[/C][C]103.557361865289[/C][C]103.3375[/C][C]1.00212760967982[/C][C]0.983030063400273[/C][/ROW]
[ROW][C]23[/C][C]102.5[/C][C]100.795365762435[/C][C]106.225[/C][C]0.948885533183666[/C][C]1.01691183145843[/C][/ROW]
[ROW][C]24[/C][C]105.3[/C][C]102.019017757022[/C][C]109.070833333333[/C][C]0.935346459169705[/C][C]1.03216049629876[/C][/ROW]
[ROW][C]25[/C][C]110.3[/C][C]111.939014692281[/C][C]111.6[/C][C]1.00303776605987[/C][C]0.985357967489827[/C][/ROW]
[ROW][C]26[/C][C]109.8[/C][C]114.662253153884[/C][C]114.716666666667[/C][C]0.999525670381087[/C][C]0.95759499730606[/C][/ROW]
[ROW][C]27[/C][C]117.3[/C][C]120.065085464428[/C][C]118.6125[/C][C]1.01224647878114[/C][C]0.976970112054376[/C][/ROW]
[ROW][C]28[/C][C]118.8[/C][C]121.574256417407[/C][C]123.35[/C][C]0.985604024462152[/C][C]0.977180560266957[/C][/ROW]
[ROW][C]29[/C][C]131.3[/C][C]126.268414182579[/C][C]127.929166666667[/C][C]0.98701818727222[/C][C]1.03984833301340[/C][/ROW]
[ROW][C]30[/C][C]125.9[/C][C]131.693504126985[/C][C]131.25[/C][C]1.00337907906274[/C][C]0.956007669737463[/C][/ROW]
[ROW][C]31[/C][C]133.1[/C][C]139.396570370439[/C][C]134.325[/C][C]1.03775596776802[/C][C]0.95482980425052[/C][/ROW]
[ROW][C]32[/C][C]147[/C][C]149.396438803378[/C][C]138.008333333333[/C][C]1.08251752046406[/C][C]0.983959197270212[/C][/ROW]
[ROW][C]33[/C][C]145.8[/C][C]142.943556772672[/C][C]142.579166666667[/C][C]1.00255570371552[/C][C]1.01998301491735[/C][/ROW]
[ROW][C]34[/C][C]164.4[/C][C]148.072705393608[/C][C]147.758333333333[/C][C]1.00212760967982[/C][C]1.11026538998521[/C][/ROW]
[ROW][C]35[/C][C]149.8[/C][C]144.187110456980[/C][C]151.954166666667[/C][C]0.948885533183666[/C][C]1.03892781764772[/C][/ROW]
[ROW][C]36[/C][C]137.7[/C][C]146.214137952791[/C][C]156.320833333333[/C][C]0.935346459169705[/C][C]0.941769393356886[/C][/ROW]
[ROW][C]37[/C][C]151.7[/C][C]162.316586492638[/C][C]161.825[/C][C]1.00303776605987[/C][C]0.934593335640906[/C][/ROW]
[ROW][C]38[/C][C]156.8[/C][C]167.478855452938[/C][C]167.558333333333[/C][C]0.999525670381087[/C][C]0.936237589968852[/C][/ROW]
[ROW][C]39[/C][C]180[/C][C]175.637417149512[/C][C]173.5125[/C][C]1.01224647878114[/C][C]1.02483857324533[/C][/ROW]
[ROW][C]40[/C][C]180.4[/C][C]175.626423792285[/C][C]178.191666666667[/C][C]0.985604024462152[/C][C]1.02718028474668[/C][/ROW]
[ROW][C]41[/C][C]170.4[/C][C]179.365880082044[/C][C]181.725[/C][C]0.98701818727222[/C][C]0.950013458089448[/C][/ROW]
[ROW][C]42[/C][C]191.6[/C][C]186.762292582879[/C][C]186.133333333333[/C][C]1.00337907906274[/C][C]1.02590302009157[/C][/ROW]
[ROW][C]43[/C][C]199.5[/C][C]198.747563760371[/C][C]191.516666666667[/C][C]1.03775596776802[/C][C]1.00378588912182[/C][/ROW]
[ROW][C]44[/C][C]218.2[/C][C]212.818434033566[/C][C]196.595833333333[/C][C]1.08251752046406[/C][C]1.02528712322723[/C][/ROW]
[ROW][C]45[/C][C]217.5[/C][C]200.836971346811[/C][C]200.325[/C][C]1.00255570371552[/C][C]1.08296793434718[/C][/ROW]
[ROW][C]46[/C][C]205[/C][C]204.71796853076[/C][C]204.283333333333[/C][C]1.00212760967982[/C][C]1.00137765859667[/C][/ROW]
[ROW][C]47[/C][C]194[/C][C]199.044555344160[/C][C]209.766666666667[/C][C]0.948885533183666[/C][C]0.974656150049228[/C][/ROW]
[ROW][C]48[/C][C]199.3[/C][C]200.916316706566[/C][C]214.804166666667[/C][C]0.935346459169705[/C][C]0.991955274051104[/C][/ROW]
[ROW][C]49[/C][C]219.3[/C][C]219.844981700196[/C][C]219.179166666667[/C][C]1.00303776605987[/C][C]0.997521063724167[/C][/ROW]
[ROW][C]50[/C][C]211.1[/C][C]222.85257759205[/C][C]222.958333333333[/C][C]0.999525670381087[/C][C]0.94726299458127[/C][/ROW]
[ROW][C]51[/C][C]215.2[/C][C]227.186069081441[/C][C]224.4375[/C][C]1.01224647878114[/C][C]0.947241179312167[/C][/ROW]
[ROW][C]52[/C][C]240.2[/C][C]221.181863139613[/C][C]224.4125[/C][C]0.985604024462152[/C][C]1.08598416068311[/C][/ROW]
[ROW][C]53[/C][C]242.2[/C][C]221.922814256598[/C][C]224.841666666667[/C][C]0.98701818727222[/C][C]1.09137044251772[/C][/ROW]
[ROW][C]54[/C][C]240.7[/C][C]226.767852614343[/C][C]226.004166666667[/C][C]1.00337907906274[/C][C]1.06143792969346[/C][/ROW]
[ROW][C]55[/C][C]255.4[/C][C]233.910195134911[/C][C]225.4[/C][C]1.03775596776802[/C][C]1.09187203171155[/C][/ROW]
[ROW][C]56[/C][C]253[/C][C]242.240358141846[/C][C]223.775[/C][C]1.08251752046406[/C][C]1.04441721412851[/C][/ROW]
[ROW][C]57[/C][C]218.2[/C][C]223.954234948318[/C][C]223.383333333333[/C][C]1.00255570371552[/C][C]0.974306201668183[/C][/ROW]
[ROW][C]58[/C][C]203.7[/C][C]223.395121856168[/C][C]222.920833333333[/C][C]1.00212760967982[/C][C]0.911837278752897[/C][/ROW]
[ROW][C]59[/C][C]205.6[/C][C]210.652588366774[/C][C]222[/C][C]0.948885533183666[/C][C]0.976014591579683[/C][/ROW]
[ROW][C]60[/C][C]215.6[/C][C]207.183137983003[/C][C]221.504166666667[/C][C]0.935346459169705[/C][C]1.04062522702831[/C][/ROW]
[ROW][C]61[/C][C]188.5[/C][C]222.365114087422[/C][C]221.691666666667[/C][C]1.00303776605987[/C][C]0.8477049143864[/C][/ROW]
[ROW][C]62[/C][C]202.9[/C][C]221.544864839968[/C][C]221.65[/C][C]0.999525670381087[/C][C]0.915841584261337[/C][/ROW]
[ROW][C]63[/C][C]214[/C][C]226.342530349124[/C][C]223.604166666667[/C][C]1.01224647878114[/C][C]0.945469681150574[/C][/ROW]
[ROW][C]64[/C][C]230.3[/C][C]226.056496377265[/C][C]229.358333333333[/C][C]0.985604024462152[/C][C]1.01877187203527[/C][/ROW]
[ROW][C]65[/C][C]230[/C][C]234.733487812235[/C][C]237.820833333333[/C][C]0.98701818727222[/C][C]0.97983462923696[/C][/ROW]
[ROW][C]66[/C][C]241[/C][C]247.675764174313[/C][C]246.841666666667[/C][C]1.00337907906274[/C][C]0.973046356810211[/C][/ROW]
[ROW][C]67[/C][C]259.6[/C][C]266.154137850103[/C][C]256.470833333333[/C][C]1.03775596776802[/C][C]0.975374653563364[/C][/ROW]
[ROW][C]68[/C][C]247.8[/C][C]NA[/C][C]NA[/C][C]1.08251752046406[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]270.3[/C][C]NA[/C][C]NA[/C][C]1.00255570371552[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]289.7[/C][C]NA[/C][C]NA[/C][C]1.00212760967982[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]322.7[/C][C]NA[/C][C]NA[/C][C]0.948885533183666[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]315[/C][C]NA[/C][C]NA[/C][C]0.935346459169705[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]320.2[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13601&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13601&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
168.4NANA1.00303776605987NA
270.6NANA0.999525670381087NA
383.9NANA1.01224647878114NA
490.1NANA0.985604024462152NA
590.6NANA0.98701818727222NA
687.1NANA1.00337907906274NA
790.892.95266682962189.57083333333331.037755967768020.976841257996752
894.1100.71923429984493.04166666666671.082517520464060.934280335371314
999.896.069900308539695.8251.002555703715521.03882693413318
1096.896.93079304628196.7251.002127609679820.998650655357595
118791.784906886911796.72916666666670.9488855331836660.947868260161693
1296.390.911778554382297.19583333333330.9353464591697051.05926868367661
13107.198.343673638144698.04583333333331.003037766059871.08903802388016
14115.298.848924110396398.89583333333330.9995256703810871.16541480887888
15106.1100.33471451551999.12083333333331.012246478781141.05746052612319
1689.597.689785557940399.11666666666660.9856040244621520.916165385038307
1791.398.673030696759899.97083333333330.987018187272220.925278157114496
1897.6101.332925493012100.9916666666671.003379079062740.963161771212566
19100.7105.332230728454101.51.037755967768020.956022665651167
20104.6109.776297554393101.4083333333331.082517520464060.952846856109095
2194.7101.909787282682101.651.002555703715520.92925323980234
22101.8103.557361865289103.33751.002127609679820.983030063400273
23102.5100.795365762435106.2250.9488855331836661.01691183145843
24105.3102.019017757022109.0708333333330.9353464591697051.03216049629876
25110.3111.939014692281111.61.003037766059870.985357967489827
26109.8114.662253153884114.7166666666670.9995256703810870.95759499730606
27117.3120.065085464428118.61251.012246478781140.976970112054376
28118.8121.574256417407123.350.9856040244621520.977180560266957
29131.3126.268414182579127.9291666666670.987018187272221.03984833301340
30125.9131.693504126985131.251.003379079062740.956007669737463
31133.1139.396570370439134.3251.037755967768020.95482980425052
32147149.396438803378138.0083333333331.082517520464060.983959197270212
33145.8142.943556772672142.5791666666671.002555703715521.01998301491735
34164.4148.072705393608147.7583333333331.002127609679821.11026538998521
35149.8144.187110456980151.9541666666670.9488855331836661.03892781764772
36137.7146.214137952791156.3208333333330.9353464591697050.941769393356886
37151.7162.316586492638161.8251.003037766059870.934593335640906
38156.8167.478855452938167.5583333333330.9995256703810870.936237589968852
39180175.637417149512173.51251.012246478781141.02483857324533
40180.4175.626423792285178.1916666666670.9856040244621521.02718028474668
41170.4179.365880082044181.7250.987018187272220.950013458089448
42191.6186.762292582879186.1333333333331.003379079062741.02590302009157
43199.5198.747563760371191.5166666666671.037755967768021.00378588912182
44218.2212.818434033566196.5958333333331.082517520464061.02528712322723
45217.5200.836971346811200.3251.002555703715521.08296793434718
46205204.71796853076204.2833333333331.002127609679821.00137765859667
47194199.044555344160209.7666666666670.9488855331836660.974656150049228
48199.3200.916316706566214.8041666666670.9353464591697050.991955274051104
49219.3219.844981700196219.1791666666671.003037766059870.997521063724167
50211.1222.85257759205222.9583333333330.9995256703810870.94726299458127
51215.2227.186069081441224.43751.012246478781140.947241179312167
52240.2221.181863139613224.41250.9856040244621521.08598416068311
53242.2221.922814256598224.8416666666670.987018187272221.09137044251772
54240.7226.767852614343226.0041666666671.003379079062741.06143792969346
55255.4233.910195134911225.41.037755967768021.09187203171155
56253242.240358141846223.7751.082517520464061.04441721412851
57218.2223.954234948318223.3833333333331.002555703715520.974306201668183
58203.7223.395121856168222.9208333333331.002127609679820.911837278752897
59205.6210.6525883667742220.9488855331836660.976014591579683
60215.6207.183137983003221.5041666666670.9353464591697051.04062522702831
61188.5222.365114087422221.6916666666671.003037766059870.8477049143864
62202.9221.544864839968221.650.9995256703810870.915841584261337
63214226.342530349124223.6041666666671.012246478781140.945469681150574
64230.3226.056496377265229.3583333333330.9856040244621521.01877187203527
65230234.733487812235237.8208333333330.987018187272220.97983462923696
66241247.675764174313246.8416666666671.003379079062740.973046356810211
67259.6266.154137850103256.4708333333331.037755967768020.975374653563364
68247.8NANA1.08251752046406NA
69270.3NANA1.00255570371552NA
70289.7NANA1.00212760967982NA
71322.7NANA0.948885533183666NA
72315NANA0.935346459169705NA
73320.2NANANANA



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')