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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSat, 05 May 2012 08:15:07 -0400
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/May/05/t13362201447wsvu3kiioesmgu.htm/, Retrieved Wed, 01 May 2024 08:24:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166224, Retrieved Wed, 01 May 2024 08:24:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact172
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2012-05-05 12:15:07] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
105,32
106,93
107,99
109,41
111,79
112,7
113,41
115,14
115,6
116,21
116,9
117,31
117,62
118,66
120
120,41
120,8
120,93
121,54
122,04
122,5
123,01
123,79
123,99
124,58
125,77
127,6
130,97
131,79
132,29
132,29
132,65
133,88
134,79
135,9
136,33
136,33
137,91
138,92
140,12
141,92
142,57
143,69
144,61
145,02
146,07
146,77
147,55
148,14
148,62
151,16
152,56
154,55
156,17
158,8
159,39
162,44
166,48
168,3
170,32
170,64
172,85
174,38
177,2
178,96
179,62
180,27
183,38
190,81
193,72
196,86
197,73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166224&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]2 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=166224&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166224&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 time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1105.32NANA0.993715745772321NA
2106.93NANA0.995162094768801NA
3107.99NANA0.998817266424619NA
4109.41NANA1.00301926065846NA
5111.79NANA1.00336451311754NA
6112.7NANA0.999333467999233NA
7113.41113.179828302283112.9051.002434155283491.00203368127669
8115.14114.007899272006113.906251.000892394157531.00993002007074
9115.6114.972123033234114.8954166666671.000667619029491.00546112353326
10116.21116.116417101675115.8541666666671.002263625405581.00080594028528
11116.9116.865489755735116.6879166666671.001521777868191.00029529884602
12117.31117.266311085529117.406250.9988080795147511.00037256151461
13117.62117.345822177116118.0879166666670.9937157457723211.00233649411455
14118.66118.139838778733118.7141666666670.9951620947688011.00440292814553
15120119.148079364071119.2891666666670.9988172664246191.00715009961114
16120.41120.221888582523119.861.003019260658461.00156470189992
17120.8120.835606383292120.4304166666671.003364513117540.999705332026232
18120.93120.915185738457120.9958333333330.9993334679992331.00012251779173
19121.54121.860072725242121.5641666666671.002434155283490.997373440552893
20122.04122.25942298484122.1504166666671.000892394157530.998205267295697
21122.5122.84529247079122.7633333333331.000667619029490.997189208769462
22123.01123.799603010097123.521.002263625405580.993621926154059
23123.79124.607253098656124.4179166666671.001521777868190.993441368152067
24123.99125.199760427108125.3491666666670.9988080795147510.990337358290617
25124.58125.476901266898126.2704166666670.9937157457723210.992852060755066
26125.77126.545226621674127.1604166666670.9951620947688010.993873916524792
27127.6127.925186092777128.0766666666670.9988172664246190.997457997891507
28130.97129.431277094136129.0416666666671.003019260658461.01188833905073
29131.79130.474594805974130.0370833333331.003364513117541.01008169594994
30132.29130.968480426529131.0558333333330.9993334679992331.01009036349179
31132.29132.38103686584132.0595833333331.002434155283490.999312311883974
32132.65133.17373750463133.0551.000892394157530.996067261350143
33133.88134.12198264757134.03251.000667619029490.998195801741126
34134.79135.190746722675134.8854166666671.002263625405580.997035694140391
35135.9135.895238136712135.688751.001521777868191.00003504069276
36136.33136.376422836878136.5391666666670.9988080795147510.999659597781551
37136.33136.578776388312137.44250.9937157457723210.998178513566376
38137.91137.746190649169138.4158333333330.9951620947688011.00118921147698
39138.92139.213485898819139.3783333333330.9988172664246190.997891828532814
40140.12140.736140011141140.31251.003019260658460.995622019965221
41141.92141.710605078702141.2354166666671.003364513117541.0014776235073
42142.57142.061081921321142.1558333333330.9993334679992331.00358238915117
43143.69143.463781814295143.1154166666671.002434155283491.00157683132875
44144.61144.182302724871144.053751.000892394157531.00296636457489
45145.02145.106811435466145.011.000667619029490.99940174114084
46146.07146.368909414854146.0383333333331.002263625405580.997957835335048
47146.77147.306744194039147.0829166666671.001521777868190.996356282280384
48147.55147.999219522165148.1758333333330.9988080795147510.996964716951786
49148.14148.433391187149149.3720833333330.9937157457723210.998023415184399
50148.62149.88882680884150.61750.9951620947688010.99153488064552
51151.16151.779439458163151.9591666666670.9988172664246190.995918818382948
52152.56153.998980109889153.5354166666671.003019260658460.990655911429658
53154.55155.805368076721155.2829166666671.003364513117540.991942716145038
54156.17157.024018659885157.128750.9993334679992330.994561222753225
55158.8159.402067202404159.0151.002434155283490.996222964902708
56159.39161.105724956084160.9620833333331.000892394157530.98935031665354
57162.44163.047947954982162.9391666666671.000667619029490.99627135476032
58166.48165.306680616893164.9333333333331.002263625405581.00709783403023
59168.3167.231185363245166.9770833333331.001521777868191.00639123997377
60170.32168.769849705707168.971250.9988080795147511.00918499540644
61170.64169.769296345335170.8429166666670.9937157457723211.00512874632462
62172.85171.901397694253172.7370833333330.9951620947688011.00551829315218
63174.38174.711867721411174.918750.9988172664246190.998100485526601
64177.2177.770954512187177.2358333333331.003019260658460.996788257599486
65178.96180.164968112479179.5608333333331.003364513117540.993311862316503
66179.62181.771679216995181.8929166666670.9993334679992330.9881627367571
67180.27NANA1.00243415528349NA
68183.38NANA1.00089239415753NA
69190.81NANA1.00066761902949NA
70193.72NANA1.00226362540558NA
71196.86NANA1.00152177786819NA
72197.73NANA0.998808079514751NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 105.32 & NA & NA & 0.993715745772321 & NA \tabularnewline
2 & 106.93 & NA & NA & 0.995162094768801 & NA \tabularnewline
3 & 107.99 & NA & NA & 0.998817266424619 & NA \tabularnewline
4 & 109.41 & NA & NA & 1.00301926065846 & NA \tabularnewline
5 & 111.79 & NA & NA & 1.00336451311754 & NA \tabularnewline
6 & 112.7 & NA & NA & 0.999333467999233 & NA \tabularnewline
7 & 113.41 & 113.179828302283 & 112.905 & 1.00243415528349 & 1.00203368127669 \tabularnewline
8 & 115.14 & 114.007899272006 & 113.90625 & 1.00089239415753 & 1.00993002007074 \tabularnewline
9 & 115.6 & 114.972123033234 & 114.895416666667 & 1.00066761902949 & 1.00546112353326 \tabularnewline
10 & 116.21 & 116.116417101675 & 115.854166666667 & 1.00226362540558 & 1.00080594028528 \tabularnewline
11 & 116.9 & 116.865489755735 & 116.687916666667 & 1.00152177786819 & 1.00029529884602 \tabularnewline
12 & 117.31 & 117.266311085529 & 117.40625 & 0.998808079514751 & 1.00037256151461 \tabularnewline
13 & 117.62 & 117.345822177116 & 118.087916666667 & 0.993715745772321 & 1.00233649411455 \tabularnewline
14 & 118.66 & 118.139838778733 & 118.714166666667 & 0.995162094768801 & 1.00440292814553 \tabularnewline
15 & 120 & 119.148079364071 & 119.289166666667 & 0.998817266424619 & 1.00715009961114 \tabularnewline
16 & 120.41 & 120.221888582523 & 119.86 & 1.00301926065846 & 1.00156470189992 \tabularnewline
17 & 120.8 & 120.835606383292 & 120.430416666667 & 1.00336451311754 & 0.999705332026232 \tabularnewline
18 & 120.93 & 120.915185738457 & 120.995833333333 & 0.999333467999233 & 1.00012251779173 \tabularnewline
19 & 121.54 & 121.860072725242 & 121.564166666667 & 1.00243415528349 & 0.997373440552893 \tabularnewline
20 & 122.04 & 122.25942298484 & 122.150416666667 & 1.00089239415753 & 0.998205267295697 \tabularnewline
21 & 122.5 & 122.84529247079 & 122.763333333333 & 1.00066761902949 & 0.997189208769462 \tabularnewline
22 & 123.01 & 123.799603010097 & 123.52 & 1.00226362540558 & 0.993621926154059 \tabularnewline
23 & 123.79 & 124.607253098656 & 124.417916666667 & 1.00152177786819 & 0.993441368152067 \tabularnewline
24 & 123.99 & 125.199760427108 & 125.349166666667 & 0.998808079514751 & 0.990337358290617 \tabularnewline
25 & 124.58 & 125.476901266898 & 126.270416666667 & 0.993715745772321 & 0.992852060755066 \tabularnewline
26 & 125.77 & 126.545226621674 & 127.160416666667 & 0.995162094768801 & 0.993873916524792 \tabularnewline
27 & 127.6 & 127.925186092777 & 128.076666666667 & 0.998817266424619 & 0.997457997891507 \tabularnewline
28 & 130.97 & 129.431277094136 & 129.041666666667 & 1.00301926065846 & 1.01188833905073 \tabularnewline
29 & 131.79 & 130.474594805974 & 130.037083333333 & 1.00336451311754 & 1.01008169594994 \tabularnewline
30 & 132.29 & 130.968480426529 & 131.055833333333 & 0.999333467999233 & 1.01009036349179 \tabularnewline
31 & 132.29 & 132.38103686584 & 132.059583333333 & 1.00243415528349 & 0.999312311883974 \tabularnewline
32 & 132.65 & 133.17373750463 & 133.055 & 1.00089239415753 & 0.996067261350143 \tabularnewline
33 & 133.88 & 134.12198264757 & 134.0325 & 1.00066761902949 & 0.998195801741126 \tabularnewline
34 & 134.79 & 135.190746722675 & 134.885416666667 & 1.00226362540558 & 0.997035694140391 \tabularnewline
35 & 135.9 & 135.895238136712 & 135.68875 & 1.00152177786819 & 1.00003504069276 \tabularnewline
36 & 136.33 & 136.376422836878 & 136.539166666667 & 0.998808079514751 & 0.999659597781551 \tabularnewline
37 & 136.33 & 136.578776388312 & 137.4425 & 0.993715745772321 & 0.998178513566376 \tabularnewline
38 & 137.91 & 137.746190649169 & 138.415833333333 & 0.995162094768801 & 1.00118921147698 \tabularnewline
39 & 138.92 & 139.213485898819 & 139.378333333333 & 0.998817266424619 & 0.997891828532814 \tabularnewline
40 & 140.12 & 140.736140011141 & 140.3125 & 1.00301926065846 & 0.995622019965221 \tabularnewline
41 & 141.92 & 141.710605078702 & 141.235416666667 & 1.00336451311754 & 1.0014776235073 \tabularnewline
42 & 142.57 & 142.061081921321 & 142.155833333333 & 0.999333467999233 & 1.00358238915117 \tabularnewline
43 & 143.69 & 143.463781814295 & 143.115416666667 & 1.00243415528349 & 1.00157683132875 \tabularnewline
44 & 144.61 & 144.182302724871 & 144.05375 & 1.00089239415753 & 1.00296636457489 \tabularnewline
45 & 145.02 & 145.106811435466 & 145.01 & 1.00066761902949 & 0.99940174114084 \tabularnewline
46 & 146.07 & 146.368909414854 & 146.038333333333 & 1.00226362540558 & 0.997957835335048 \tabularnewline
47 & 146.77 & 147.306744194039 & 147.082916666667 & 1.00152177786819 & 0.996356282280384 \tabularnewline
48 & 147.55 & 147.999219522165 & 148.175833333333 & 0.998808079514751 & 0.996964716951786 \tabularnewline
49 & 148.14 & 148.433391187149 & 149.372083333333 & 0.993715745772321 & 0.998023415184399 \tabularnewline
50 & 148.62 & 149.88882680884 & 150.6175 & 0.995162094768801 & 0.99153488064552 \tabularnewline
51 & 151.16 & 151.779439458163 & 151.959166666667 & 0.998817266424619 & 0.995918818382948 \tabularnewline
52 & 152.56 & 153.998980109889 & 153.535416666667 & 1.00301926065846 & 0.990655911429658 \tabularnewline
53 & 154.55 & 155.805368076721 & 155.282916666667 & 1.00336451311754 & 0.991942716145038 \tabularnewline
54 & 156.17 & 157.024018659885 & 157.12875 & 0.999333467999233 & 0.994561222753225 \tabularnewline
55 & 158.8 & 159.402067202404 & 159.015 & 1.00243415528349 & 0.996222964902708 \tabularnewline
56 & 159.39 & 161.105724956084 & 160.962083333333 & 1.00089239415753 & 0.98935031665354 \tabularnewline
57 & 162.44 & 163.047947954982 & 162.939166666667 & 1.00066761902949 & 0.99627135476032 \tabularnewline
58 & 166.48 & 165.306680616893 & 164.933333333333 & 1.00226362540558 & 1.00709783403023 \tabularnewline
59 & 168.3 & 167.231185363245 & 166.977083333333 & 1.00152177786819 & 1.00639123997377 \tabularnewline
60 & 170.32 & 168.769849705707 & 168.97125 & 0.998808079514751 & 1.00918499540644 \tabularnewline
61 & 170.64 & 169.769296345335 & 170.842916666667 & 0.993715745772321 & 1.00512874632462 \tabularnewline
62 & 172.85 & 171.901397694253 & 172.737083333333 & 0.995162094768801 & 1.00551829315218 \tabularnewline
63 & 174.38 & 174.711867721411 & 174.91875 & 0.998817266424619 & 0.998100485526601 \tabularnewline
64 & 177.2 & 177.770954512187 & 177.235833333333 & 1.00301926065846 & 0.996788257599486 \tabularnewline
65 & 178.96 & 180.164968112479 & 179.560833333333 & 1.00336451311754 & 0.993311862316503 \tabularnewline
66 & 179.62 & 181.771679216995 & 181.892916666667 & 0.999333467999233 & 0.9881627367571 \tabularnewline
67 & 180.27 & NA & NA & 1.00243415528349 & NA \tabularnewline
68 & 183.38 & NA & NA & 1.00089239415753 & NA \tabularnewline
69 & 190.81 & NA & NA & 1.00066761902949 & NA \tabularnewline
70 & 193.72 & NA & NA & 1.00226362540558 & NA \tabularnewline
71 & 196.86 & NA & NA & 1.00152177786819 & NA \tabularnewline
72 & 197.73 & NA & NA & 0.998808079514751 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166224&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]105.32[/C][C]NA[/C][C]NA[/C][C]0.993715745772321[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]106.93[/C][C]NA[/C][C]NA[/C][C]0.995162094768801[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]107.99[/C][C]NA[/C][C]NA[/C][C]0.998817266424619[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]109.41[/C][C]NA[/C][C]NA[/C][C]1.00301926065846[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]111.79[/C][C]NA[/C][C]NA[/C][C]1.00336451311754[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]112.7[/C][C]NA[/C][C]NA[/C][C]0.999333467999233[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]113.41[/C][C]113.179828302283[/C][C]112.905[/C][C]1.00243415528349[/C][C]1.00203368127669[/C][/ROW]
[ROW][C]8[/C][C]115.14[/C][C]114.007899272006[/C][C]113.90625[/C][C]1.00089239415753[/C][C]1.00993002007074[/C][/ROW]
[ROW][C]9[/C][C]115.6[/C][C]114.972123033234[/C][C]114.895416666667[/C][C]1.00066761902949[/C][C]1.00546112353326[/C][/ROW]
[ROW][C]10[/C][C]116.21[/C][C]116.116417101675[/C][C]115.854166666667[/C][C]1.00226362540558[/C][C]1.00080594028528[/C][/ROW]
[ROW][C]11[/C][C]116.9[/C][C]116.865489755735[/C][C]116.687916666667[/C][C]1.00152177786819[/C][C]1.00029529884602[/C][/ROW]
[ROW][C]12[/C][C]117.31[/C][C]117.266311085529[/C][C]117.40625[/C][C]0.998808079514751[/C][C]1.00037256151461[/C][/ROW]
[ROW][C]13[/C][C]117.62[/C][C]117.345822177116[/C][C]118.087916666667[/C][C]0.993715745772321[/C][C]1.00233649411455[/C][/ROW]
[ROW][C]14[/C][C]118.66[/C][C]118.139838778733[/C][C]118.714166666667[/C][C]0.995162094768801[/C][C]1.00440292814553[/C][/ROW]
[ROW][C]15[/C][C]120[/C][C]119.148079364071[/C][C]119.289166666667[/C][C]0.998817266424619[/C][C]1.00715009961114[/C][/ROW]
[ROW][C]16[/C][C]120.41[/C][C]120.221888582523[/C][C]119.86[/C][C]1.00301926065846[/C][C]1.00156470189992[/C][/ROW]
[ROW][C]17[/C][C]120.8[/C][C]120.835606383292[/C][C]120.430416666667[/C][C]1.00336451311754[/C][C]0.999705332026232[/C][/ROW]
[ROW][C]18[/C][C]120.93[/C][C]120.915185738457[/C][C]120.995833333333[/C][C]0.999333467999233[/C][C]1.00012251779173[/C][/ROW]
[ROW][C]19[/C][C]121.54[/C][C]121.860072725242[/C][C]121.564166666667[/C][C]1.00243415528349[/C][C]0.997373440552893[/C][/ROW]
[ROW][C]20[/C][C]122.04[/C][C]122.25942298484[/C][C]122.150416666667[/C][C]1.00089239415753[/C][C]0.998205267295697[/C][/ROW]
[ROW][C]21[/C][C]122.5[/C][C]122.84529247079[/C][C]122.763333333333[/C][C]1.00066761902949[/C][C]0.997189208769462[/C][/ROW]
[ROW][C]22[/C][C]123.01[/C][C]123.799603010097[/C][C]123.52[/C][C]1.00226362540558[/C][C]0.993621926154059[/C][/ROW]
[ROW][C]23[/C][C]123.79[/C][C]124.607253098656[/C][C]124.417916666667[/C][C]1.00152177786819[/C][C]0.993441368152067[/C][/ROW]
[ROW][C]24[/C][C]123.99[/C][C]125.199760427108[/C][C]125.349166666667[/C][C]0.998808079514751[/C][C]0.990337358290617[/C][/ROW]
[ROW][C]25[/C][C]124.58[/C][C]125.476901266898[/C][C]126.270416666667[/C][C]0.993715745772321[/C][C]0.992852060755066[/C][/ROW]
[ROW][C]26[/C][C]125.77[/C][C]126.545226621674[/C][C]127.160416666667[/C][C]0.995162094768801[/C][C]0.993873916524792[/C][/ROW]
[ROW][C]27[/C][C]127.6[/C][C]127.925186092777[/C][C]128.076666666667[/C][C]0.998817266424619[/C][C]0.997457997891507[/C][/ROW]
[ROW][C]28[/C][C]130.97[/C][C]129.431277094136[/C][C]129.041666666667[/C][C]1.00301926065846[/C][C]1.01188833905073[/C][/ROW]
[ROW][C]29[/C][C]131.79[/C][C]130.474594805974[/C][C]130.037083333333[/C][C]1.00336451311754[/C][C]1.01008169594994[/C][/ROW]
[ROW][C]30[/C][C]132.29[/C][C]130.968480426529[/C][C]131.055833333333[/C][C]0.999333467999233[/C][C]1.01009036349179[/C][/ROW]
[ROW][C]31[/C][C]132.29[/C][C]132.38103686584[/C][C]132.059583333333[/C][C]1.00243415528349[/C][C]0.999312311883974[/C][/ROW]
[ROW][C]32[/C][C]132.65[/C][C]133.17373750463[/C][C]133.055[/C][C]1.00089239415753[/C][C]0.996067261350143[/C][/ROW]
[ROW][C]33[/C][C]133.88[/C][C]134.12198264757[/C][C]134.0325[/C][C]1.00066761902949[/C][C]0.998195801741126[/C][/ROW]
[ROW][C]34[/C][C]134.79[/C][C]135.190746722675[/C][C]134.885416666667[/C][C]1.00226362540558[/C][C]0.997035694140391[/C][/ROW]
[ROW][C]35[/C][C]135.9[/C][C]135.895238136712[/C][C]135.68875[/C][C]1.00152177786819[/C][C]1.00003504069276[/C][/ROW]
[ROW][C]36[/C][C]136.33[/C][C]136.376422836878[/C][C]136.539166666667[/C][C]0.998808079514751[/C][C]0.999659597781551[/C][/ROW]
[ROW][C]37[/C][C]136.33[/C][C]136.578776388312[/C][C]137.4425[/C][C]0.993715745772321[/C][C]0.998178513566376[/C][/ROW]
[ROW][C]38[/C][C]137.91[/C][C]137.746190649169[/C][C]138.415833333333[/C][C]0.995162094768801[/C][C]1.00118921147698[/C][/ROW]
[ROW][C]39[/C][C]138.92[/C][C]139.213485898819[/C][C]139.378333333333[/C][C]0.998817266424619[/C][C]0.997891828532814[/C][/ROW]
[ROW][C]40[/C][C]140.12[/C][C]140.736140011141[/C][C]140.3125[/C][C]1.00301926065846[/C][C]0.995622019965221[/C][/ROW]
[ROW][C]41[/C][C]141.92[/C][C]141.710605078702[/C][C]141.235416666667[/C][C]1.00336451311754[/C][C]1.0014776235073[/C][/ROW]
[ROW][C]42[/C][C]142.57[/C][C]142.061081921321[/C][C]142.155833333333[/C][C]0.999333467999233[/C][C]1.00358238915117[/C][/ROW]
[ROW][C]43[/C][C]143.69[/C][C]143.463781814295[/C][C]143.115416666667[/C][C]1.00243415528349[/C][C]1.00157683132875[/C][/ROW]
[ROW][C]44[/C][C]144.61[/C][C]144.182302724871[/C][C]144.05375[/C][C]1.00089239415753[/C][C]1.00296636457489[/C][/ROW]
[ROW][C]45[/C][C]145.02[/C][C]145.106811435466[/C][C]145.01[/C][C]1.00066761902949[/C][C]0.99940174114084[/C][/ROW]
[ROW][C]46[/C][C]146.07[/C][C]146.368909414854[/C][C]146.038333333333[/C][C]1.00226362540558[/C][C]0.997957835335048[/C][/ROW]
[ROW][C]47[/C][C]146.77[/C][C]147.306744194039[/C][C]147.082916666667[/C][C]1.00152177786819[/C][C]0.996356282280384[/C][/ROW]
[ROW][C]48[/C][C]147.55[/C][C]147.999219522165[/C][C]148.175833333333[/C][C]0.998808079514751[/C][C]0.996964716951786[/C][/ROW]
[ROW][C]49[/C][C]148.14[/C][C]148.433391187149[/C][C]149.372083333333[/C][C]0.993715745772321[/C][C]0.998023415184399[/C][/ROW]
[ROW][C]50[/C][C]148.62[/C][C]149.88882680884[/C][C]150.6175[/C][C]0.995162094768801[/C][C]0.99153488064552[/C][/ROW]
[ROW][C]51[/C][C]151.16[/C][C]151.779439458163[/C][C]151.959166666667[/C][C]0.998817266424619[/C][C]0.995918818382948[/C][/ROW]
[ROW][C]52[/C][C]152.56[/C][C]153.998980109889[/C][C]153.535416666667[/C][C]1.00301926065846[/C][C]0.990655911429658[/C][/ROW]
[ROW][C]53[/C][C]154.55[/C][C]155.805368076721[/C][C]155.282916666667[/C][C]1.00336451311754[/C][C]0.991942716145038[/C][/ROW]
[ROW][C]54[/C][C]156.17[/C][C]157.024018659885[/C][C]157.12875[/C][C]0.999333467999233[/C][C]0.994561222753225[/C][/ROW]
[ROW][C]55[/C][C]158.8[/C][C]159.402067202404[/C][C]159.015[/C][C]1.00243415528349[/C][C]0.996222964902708[/C][/ROW]
[ROW][C]56[/C][C]159.39[/C][C]161.105724956084[/C][C]160.962083333333[/C][C]1.00089239415753[/C][C]0.98935031665354[/C][/ROW]
[ROW][C]57[/C][C]162.44[/C][C]163.047947954982[/C][C]162.939166666667[/C][C]1.00066761902949[/C][C]0.99627135476032[/C][/ROW]
[ROW][C]58[/C][C]166.48[/C][C]165.306680616893[/C][C]164.933333333333[/C][C]1.00226362540558[/C][C]1.00709783403023[/C][/ROW]
[ROW][C]59[/C][C]168.3[/C][C]167.231185363245[/C][C]166.977083333333[/C][C]1.00152177786819[/C][C]1.00639123997377[/C][/ROW]
[ROW][C]60[/C][C]170.32[/C][C]168.769849705707[/C][C]168.97125[/C][C]0.998808079514751[/C][C]1.00918499540644[/C][/ROW]
[ROW][C]61[/C][C]170.64[/C][C]169.769296345335[/C][C]170.842916666667[/C][C]0.993715745772321[/C][C]1.00512874632462[/C][/ROW]
[ROW][C]62[/C][C]172.85[/C][C]171.901397694253[/C][C]172.737083333333[/C][C]0.995162094768801[/C][C]1.00551829315218[/C][/ROW]
[ROW][C]63[/C][C]174.38[/C][C]174.711867721411[/C][C]174.91875[/C][C]0.998817266424619[/C][C]0.998100485526601[/C][/ROW]
[ROW][C]64[/C][C]177.2[/C][C]177.770954512187[/C][C]177.235833333333[/C][C]1.00301926065846[/C][C]0.996788257599486[/C][/ROW]
[ROW][C]65[/C][C]178.96[/C][C]180.164968112479[/C][C]179.560833333333[/C][C]1.00336451311754[/C][C]0.993311862316503[/C][/ROW]
[ROW][C]66[/C][C]179.62[/C][C]181.771679216995[/C][C]181.892916666667[/C][C]0.999333467999233[/C][C]0.9881627367571[/C][/ROW]
[ROW][C]67[/C][C]180.27[/C][C]NA[/C][C]NA[/C][C]1.00243415528349[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]183.38[/C][C]NA[/C][C]NA[/C][C]1.00089239415753[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]190.81[/C][C]NA[/C][C]NA[/C][C]1.00066761902949[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]193.72[/C][C]NA[/C][C]NA[/C][C]1.00226362540558[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]196.86[/C][C]NA[/C][C]NA[/C][C]1.00152177786819[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]197.73[/C][C]NA[/C][C]NA[/C][C]0.998808079514751[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166224&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166224&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
1105.32NANA0.993715745772321NA
2106.93NANA0.995162094768801NA
3107.99NANA0.998817266424619NA
4109.41NANA1.00301926065846NA
5111.79NANA1.00336451311754NA
6112.7NANA0.999333467999233NA
7113.41113.179828302283112.9051.002434155283491.00203368127669
8115.14114.007899272006113.906251.000892394157531.00993002007074
9115.6114.972123033234114.8954166666671.000667619029491.00546112353326
10116.21116.116417101675115.8541666666671.002263625405581.00080594028528
11116.9116.865489755735116.6879166666671.001521777868191.00029529884602
12117.31117.266311085529117.406250.9988080795147511.00037256151461
13117.62117.345822177116118.0879166666670.9937157457723211.00233649411455
14118.66118.139838778733118.7141666666670.9951620947688011.00440292814553
15120119.148079364071119.2891666666670.9988172664246191.00715009961114
16120.41120.221888582523119.861.003019260658461.00156470189992
17120.8120.835606383292120.4304166666671.003364513117540.999705332026232
18120.93120.915185738457120.9958333333330.9993334679992331.00012251779173
19121.54121.860072725242121.5641666666671.002434155283490.997373440552893
20122.04122.25942298484122.1504166666671.000892394157530.998205267295697
21122.5122.84529247079122.7633333333331.000667619029490.997189208769462
22123.01123.799603010097123.521.002263625405580.993621926154059
23123.79124.607253098656124.4179166666671.001521777868190.993441368152067
24123.99125.199760427108125.3491666666670.9988080795147510.990337358290617
25124.58125.476901266898126.2704166666670.9937157457723210.992852060755066
26125.77126.545226621674127.1604166666670.9951620947688010.993873916524792
27127.6127.925186092777128.0766666666670.9988172664246190.997457997891507
28130.97129.431277094136129.0416666666671.003019260658461.01188833905073
29131.79130.474594805974130.0370833333331.003364513117541.01008169594994
30132.29130.968480426529131.0558333333330.9993334679992331.01009036349179
31132.29132.38103686584132.0595833333331.002434155283490.999312311883974
32132.65133.17373750463133.0551.000892394157530.996067261350143
33133.88134.12198264757134.03251.000667619029490.998195801741126
34134.79135.190746722675134.8854166666671.002263625405580.997035694140391
35135.9135.895238136712135.688751.001521777868191.00003504069276
36136.33136.376422836878136.5391666666670.9988080795147510.999659597781551
37136.33136.578776388312137.44250.9937157457723210.998178513566376
38137.91137.746190649169138.4158333333330.9951620947688011.00118921147698
39138.92139.213485898819139.3783333333330.9988172664246190.997891828532814
40140.12140.736140011141140.31251.003019260658460.995622019965221
41141.92141.710605078702141.2354166666671.003364513117541.0014776235073
42142.57142.061081921321142.1558333333330.9993334679992331.00358238915117
43143.69143.463781814295143.1154166666671.002434155283491.00157683132875
44144.61144.182302724871144.053751.000892394157531.00296636457489
45145.02145.106811435466145.011.000667619029490.99940174114084
46146.07146.368909414854146.0383333333331.002263625405580.997957835335048
47146.77147.306744194039147.0829166666671.001521777868190.996356282280384
48147.55147.999219522165148.1758333333330.9988080795147510.996964716951786
49148.14148.433391187149149.3720833333330.9937157457723210.998023415184399
50148.62149.88882680884150.61750.9951620947688010.99153488064552
51151.16151.779439458163151.9591666666670.9988172664246190.995918818382948
52152.56153.998980109889153.5354166666671.003019260658460.990655911429658
53154.55155.805368076721155.2829166666671.003364513117540.991942716145038
54156.17157.024018659885157.128750.9993334679992330.994561222753225
55158.8159.402067202404159.0151.002434155283490.996222964902708
56159.39161.105724956084160.9620833333331.000892394157530.98935031665354
57162.44163.047947954982162.9391666666671.000667619029490.99627135476032
58166.48165.306680616893164.9333333333331.002263625405581.00709783403023
59168.3167.231185363245166.9770833333331.001521777868191.00639123997377
60170.32168.769849705707168.971250.9988080795147511.00918499540644
61170.64169.769296345335170.8429166666670.9937157457723211.00512874632462
62172.85171.901397694253172.7370833333330.9951620947688011.00551829315218
63174.38174.711867721411174.918750.9988172664246190.998100485526601
64177.2177.770954512187177.2358333333331.003019260658460.996788257599486
65178.96180.164968112479179.5608333333331.003364513117540.993311862316503
66179.62181.771679216995181.8929166666670.9993334679992330.9881627367571
67180.27NANA1.00243415528349NA
68183.38NANA1.00089239415753NA
69190.81NANA1.00066761902949NA
70193.72NANA1.00226362540558NA
71196.86NANA1.00152177786819NA
72197.73NANA0.998808079514751NA



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')