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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSun, 29 Nov 2015 13:29:08 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Nov/29/t1448803784dwuo0nfr4jpbdts.htm/, Retrieved Wed, 15 May 2024 22:20:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284435, Retrieved Wed, 15 May 2024 22:20:11 +0000
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Estimated Impact123
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-       [Classical Decomposition] [classic decomp ta...] [2015-11-29 13:29:08] [4bedbbf2e5251222bc39a0f973d05821] [Current]
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Dataseries X:
89,56
89,84
89,97
90,65
91,17
91,35
91,41
91,55
91,63
91,54
91,74
91,87
92,13
92,14
92,05
92
92,51
92,67
92,68
92,77
92,85
92,71
92,73
92,28
92,49
92,46
92,55
92,24
92,41
92,83
92,85
93,04
93,04
92,83
92,96
92,83
93,01
93,21
93,58
94,07
94,57
95,03
95,21
95,89
96,43
96,35
96,71
96,32
97,23
97,88
98,2
98,56
99,31
99,69
99,77
101,06
101,77
101,91
102,52
102,09
102,22
102,74
103,56
104,4
104,76
104,86
104,84
104,96
104,83
104,58
104,8
104,17




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=284435&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=284435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284435&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
189.56NANA-0.280486NA
289.84NANA-0.234153NA
389.97NANA-0.153903NA
490.65NANA-0.106569NA
591.17NANA0.133931NA
691.35NANA0.226597NA
791.4191.157791.13040.02726390.252319
891.5591.625691.33330.292264-0.0755972
991.6391.869391.51580.353514-0.239347
1091.5491.708491.65870.0496806-0.168431
1191.7491.856791.77080.0858472-0.116681
1291.8791.487791.8817-0.3939860.382319
1392.1391.709191.9896-0.2804860.420903
1492.1491.859292.0933-0.2341530.280819
1592.0592.041192.195-0.1539030.00890278
169292.18892.2946-0.106569-0.188014
1792.5192.518592.38460.133931-0.00851389
1892.6792.669592.44290.2265970.000486111
1992.6892.502392.4750.02726390.177736
2092.7792.795692.50330.292264-0.0255972
2192.8592.89192.53750.353514-0.0410139
2292.7192.61892.56830.04968060.0919861
2392.7392.6692.57420.08584720.0699861
2492.2892.182792.5767-0.3939860.0973194
2592.4992.309992.5904-0.2804860.180069
2692.4692.374692.6087-0.2341530.0854028
2792.5592.47492.6279-0.1539030.0759861
2892.2492.534392.6408-0.106569-0.294264
2992.4192.789392.65540.133931-0.379347
3092.8392.914592.68790.226597-0.0845139
3192.8592.759892.73250.02726390.0902361
3293.0493.077792.78540.292264-0.0376806
3393.0493.213192.85960.353514-0.173097
3492.8393.028492.97870.0496806-0.198431
3592.9693.230893.1450.0858472-0.270847
3692.8392.932793.3267-0.393986-0.102681
3793.0193.236293.5167-0.280486-0.226181
3893.2193.499693.7337-0.234153-0.289597
3993.5893.839893.9937-0.153903-0.259847
4094.0794.175194.2817-0.106569-0.105097
4194.5794.718594.58460.133931-0.148514
4295.0395.112894.88620.226597-0.0828472
4395.2195.234895.20750.0272639-0.0247639
4495.8995.870295.57790.2922640.0198194
4596.4396.318595.9650.3535140.111486
4696.3596.394396.34460.0496806-0.0442639
4796.7196.81596.72920.0858472-0.105014
4896.3296.726897.1208-0.393986-0.406847
4997.2397.224597.505-0.2804860.00548611
5097.8897.676397.9104-0.2341530.203736
5198.298.194498.3483-0.1539030.00556944
5298.5698.695998.8025-0.106569-0.135931
5399.3199.410299.27620.133931-0.100181
5499.6999.985399.75880.226597-0.295347
5599.77100.234100.2070.0272639-0.464347
56101.06100.91100.6180.2922640.150236
57101.77101.397101.0430.3535140.373153
58101.91101.56101.510.04968060.350319
59102.52102.066101.980.08584720.453736
60102.09102.029102.423-0.3939860.0610694
61102.22102.569102.85-0.280486-0.349097
62102.74102.989103.223-0.234153-0.249181
63103.56103.359103.513-0.1539030.200569
64104.4103.646103.752-0.1065690.754486
65104.76104.092103.9580.1339310.667736
66104.86104.367104.140.2265970.493403
67104.84NANA0.0272639NA
68104.96NANA0.292264NA
69104.83NANA0.353514NA
70104.58NANA0.0496806NA
71104.8NANA0.0858472NA
72104.17NANA-0.393986NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 89.56 & NA & NA & -0.280486 & NA \tabularnewline
2 & 89.84 & NA & NA & -0.234153 & NA \tabularnewline
3 & 89.97 & NA & NA & -0.153903 & NA \tabularnewline
4 & 90.65 & NA & NA & -0.106569 & NA \tabularnewline
5 & 91.17 & NA & NA & 0.133931 & NA \tabularnewline
6 & 91.35 & NA & NA & 0.226597 & NA \tabularnewline
7 & 91.41 & 91.1577 & 91.1304 & 0.0272639 & 0.252319 \tabularnewline
8 & 91.55 & 91.6256 & 91.3333 & 0.292264 & -0.0755972 \tabularnewline
9 & 91.63 & 91.8693 & 91.5158 & 0.353514 & -0.239347 \tabularnewline
10 & 91.54 & 91.7084 & 91.6587 & 0.0496806 & -0.168431 \tabularnewline
11 & 91.74 & 91.8567 & 91.7708 & 0.0858472 & -0.116681 \tabularnewline
12 & 91.87 & 91.4877 & 91.8817 & -0.393986 & 0.382319 \tabularnewline
13 & 92.13 & 91.7091 & 91.9896 & -0.280486 & 0.420903 \tabularnewline
14 & 92.14 & 91.8592 & 92.0933 & -0.234153 & 0.280819 \tabularnewline
15 & 92.05 & 92.0411 & 92.195 & -0.153903 & 0.00890278 \tabularnewline
16 & 92 & 92.188 & 92.2946 & -0.106569 & -0.188014 \tabularnewline
17 & 92.51 & 92.5185 & 92.3846 & 0.133931 & -0.00851389 \tabularnewline
18 & 92.67 & 92.6695 & 92.4429 & 0.226597 & 0.000486111 \tabularnewline
19 & 92.68 & 92.5023 & 92.475 & 0.0272639 & 0.177736 \tabularnewline
20 & 92.77 & 92.7956 & 92.5033 & 0.292264 & -0.0255972 \tabularnewline
21 & 92.85 & 92.891 & 92.5375 & 0.353514 & -0.0410139 \tabularnewline
22 & 92.71 & 92.618 & 92.5683 & 0.0496806 & 0.0919861 \tabularnewline
23 & 92.73 & 92.66 & 92.5742 & 0.0858472 & 0.0699861 \tabularnewline
24 & 92.28 & 92.1827 & 92.5767 & -0.393986 & 0.0973194 \tabularnewline
25 & 92.49 & 92.3099 & 92.5904 & -0.280486 & 0.180069 \tabularnewline
26 & 92.46 & 92.3746 & 92.6087 & -0.234153 & 0.0854028 \tabularnewline
27 & 92.55 & 92.474 & 92.6279 & -0.153903 & 0.0759861 \tabularnewline
28 & 92.24 & 92.5343 & 92.6408 & -0.106569 & -0.294264 \tabularnewline
29 & 92.41 & 92.7893 & 92.6554 & 0.133931 & -0.379347 \tabularnewline
30 & 92.83 & 92.9145 & 92.6879 & 0.226597 & -0.0845139 \tabularnewline
31 & 92.85 & 92.7598 & 92.7325 & 0.0272639 & 0.0902361 \tabularnewline
32 & 93.04 & 93.0777 & 92.7854 & 0.292264 & -0.0376806 \tabularnewline
33 & 93.04 & 93.2131 & 92.8596 & 0.353514 & -0.173097 \tabularnewline
34 & 92.83 & 93.0284 & 92.9787 & 0.0496806 & -0.198431 \tabularnewline
35 & 92.96 & 93.2308 & 93.145 & 0.0858472 & -0.270847 \tabularnewline
36 & 92.83 & 92.9327 & 93.3267 & -0.393986 & -0.102681 \tabularnewline
37 & 93.01 & 93.2362 & 93.5167 & -0.280486 & -0.226181 \tabularnewline
38 & 93.21 & 93.4996 & 93.7337 & -0.234153 & -0.289597 \tabularnewline
39 & 93.58 & 93.8398 & 93.9937 & -0.153903 & -0.259847 \tabularnewline
40 & 94.07 & 94.1751 & 94.2817 & -0.106569 & -0.105097 \tabularnewline
41 & 94.57 & 94.7185 & 94.5846 & 0.133931 & -0.148514 \tabularnewline
42 & 95.03 & 95.1128 & 94.8862 & 0.226597 & -0.0828472 \tabularnewline
43 & 95.21 & 95.2348 & 95.2075 & 0.0272639 & -0.0247639 \tabularnewline
44 & 95.89 & 95.8702 & 95.5779 & 0.292264 & 0.0198194 \tabularnewline
45 & 96.43 & 96.3185 & 95.965 & 0.353514 & 0.111486 \tabularnewline
46 & 96.35 & 96.3943 & 96.3446 & 0.0496806 & -0.0442639 \tabularnewline
47 & 96.71 & 96.815 & 96.7292 & 0.0858472 & -0.105014 \tabularnewline
48 & 96.32 & 96.7268 & 97.1208 & -0.393986 & -0.406847 \tabularnewline
49 & 97.23 & 97.2245 & 97.505 & -0.280486 & 0.00548611 \tabularnewline
50 & 97.88 & 97.6763 & 97.9104 & -0.234153 & 0.203736 \tabularnewline
51 & 98.2 & 98.1944 & 98.3483 & -0.153903 & 0.00556944 \tabularnewline
52 & 98.56 & 98.6959 & 98.8025 & -0.106569 & -0.135931 \tabularnewline
53 & 99.31 & 99.4102 & 99.2762 & 0.133931 & -0.100181 \tabularnewline
54 & 99.69 & 99.9853 & 99.7588 & 0.226597 & -0.295347 \tabularnewline
55 & 99.77 & 100.234 & 100.207 & 0.0272639 & -0.464347 \tabularnewline
56 & 101.06 & 100.91 & 100.618 & 0.292264 & 0.150236 \tabularnewline
57 & 101.77 & 101.397 & 101.043 & 0.353514 & 0.373153 \tabularnewline
58 & 101.91 & 101.56 & 101.51 & 0.0496806 & 0.350319 \tabularnewline
59 & 102.52 & 102.066 & 101.98 & 0.0858472 & 0.453736 \tabularnewline
60 & 102.09 & 102.029 & 102.423 & -0.393986 & 0.0610694 \tabularnewline
61 & 102.22 & 102.569 & 102.85 & -0.280486 & -0.349097 \tabularnewline
62 & 102.74 & 102.989 & 103.223 & -0.234153 & -0.249181 \tabularnewline
63 & 103.56 & 103.359 & 103.513 & -0.153903 & 0.200569 \tabularnewline
64 & 104.4 & 103.646 & 103.752 & -0.106569 & 0.754486 \tabularnewline
65 & 104.76 & 104.092 & 103.958 & 0.133931 & 0.667736 \tabularnewline
66 & 104.86 & 104.367 & 104.14 & 0.226597 & 0.493403 \tabularnewline
67 & 104.84 & NA & NA & 0.0272639 & NA \tabularnewline
68 & 104.96 & NA & NA & 0.292264 & NA \tabularnewline
69 & 104.83 & NA & NA & 0.353514 & NA \tabularnewline
70 & 104.58 & NA & NA & 0.0496806 & NA \tabularnewline
71 & 104.8 & NA & NA & 0.0858472 & NA \tabularnewline
72 & 104.17 & NA & NA & -0.393986 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284435&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]89.56[/C][C]NA[/C][C]NA[/C][C]-0.280486[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]89.84[/C][C]NA[/C][C]NA[/C][C]-0.234153[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]89.97[/C][C]NA[/C][C]NA[/C][C]-0.153903[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]90.65[/C][C]NA[/C][C]NA[/C][C]-0.106569[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]91.17[/C][C]NA[/C][C]NA[/C][C]0.133931[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]91.35[/C][C]NA[/C][C]NA[/C][C]0.226597[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]91.41[/C][C]91.1577[/C][C]91.1304[/C][C]0.0272639[/C][C]0.252319[/C][/ROW]
[ROW][C]8[/C][C]91.55[/C][C]91.6256[/C][C]91.3333[/C][C]0.292264[/C][C]-0.0755972[/C][/ROW]
[ROW][C]9[/C][C]91.63[/C][C]91.8693[/C][C]91.5158[/C][C]0.353514[/C][C]-0.239347[/C][/ROW]
[ROW][C]10[/C][C]91.54[/C][C]91.7084[/C][C]91.6587[/C][C]0.0496806[/C][C]-0.168431[/C][/ROW]
[ROW][C]11[/C][C]91.74[/C][C]91.8567[/C][C]91.7708[/C][C]0.0858472[/C][C]-0.116681[/C][/ROW]
[ROW][C]12[/C][C]91.87[/C][C]91.4877[/C][C]91.8817[/C][C]-0.393986[/C][C]0.382319[/C][/ROW]
[ROW][C]13[/C][C]92.13[/C][C]91.7091[/C][C]91.9896[/C][C]-0.280486[/C][C]0.420903[/C][/ROW]
[ROW][C]14[/C][C]92.14[/C][C]91.8592[/C][C]92.0933[/C][C]-0.234153[/C][C]0.280819[/C][/ROW]
[ROW][C]15[/C][C]92.05[/C][C]92.0411[/C][C]92.195[/C][C]-0.153903[/C][C]0.00890278[/C][/ROW]
[ROW][C]16[/C][C]92[/C][C]92.188[/C][C]92.2946[/C][C]-0.106569[/C][C]-0.188014[/C][/ROW]
[ROW][C]17[/C][C]92.51[/C][C]92.5185[/C][C]92.3846[/C][C]0.133931[/C][C]-0.00851389[/C][/ROW]
[ROW][C]18[/C][C]92.67[/C][C]92.6695[/C][C]92.4429[/C][C]0.226597[/C][C]0.000486111[/C][/ROW]
[ROW][C]19[/C][C]92.68[/C][C]92.5023[/C][C]92.475[/C][C]0.0272639[/C][C]0.177736[/C][/ROW]
[ROW][C]20[/C][C]92.77[/C][C]92.7956[/C][C]92.5033[/C][C]0.292264[/C][C]-0.0255972[/C][/ROW]
[ROW][C]21[/C][C]92.85[/C][C]92.891[/C][C]92.5375[/C][C]0.353514[/C][C]-0.0410139[/C][/ROW]
[ROW][C]22[/C][C]92.71[/C][C]92.618[/C][C]92.5683[/C][C]0.0496806[/C][C]0.0919861[/C][/ROW]
[ROW][C]23[/C][C]92.73[/C][C]92.66[/C][C]92.5742[/C][C]0.0858472[/C][C]0.0699861[/C][/ROW]
[ROW][C]24[/C][C]92.28[/C][C]92.1827[/C][C]92.5767[/C][C]-0.393986[/C][C]0.0973194[/C][/ROW]
[ROW][C]25[/C][C]92.49[/C][C]92.3099[/C][C]92.5904[/C][C]-0.280486[/C][C]0.180069[/C][/ROW]
[ROW][C]26[/C][C]92.46[/C][C]92.3746[/C][C]92.6087[/C][C]-0.234153[/C][C]0.0854028[/C][/ROW]
[ROW][C]27[/C][C]92.55[/C][C]92.474[/C][C]92.6279[/C][C]-0.153903[/C][C]0.0759861[/C][/ROW]
[ROW][C]28[/C][C]92.24[/C][C]92.5343[/C][C]92.6408[/C][C]-0.106569[/C][C]-0.294264[/C][/ROW]
[ROW][C]29[/C][C]92.41[/C][C]92.7893[/C][C]92.6554[/C][C]0.133931[/C][C]-0.379347[/C][/ROW]
[ROW][C]30[/C][C]92.83[/C][C]92.9145[/C][C]92.6879[/C][C]0.226597[/C][C]-0.0845139[/C][/ROW]
[ROW][C]31[/C][C]92.85[/C][C]92.7598[/C][C]92.7325[/C][C]0.0272639[/C][C]0.0902361[/C][/ROW]
[ROW][C]32[/C][C]93.04[/C][C]93.0777[/C][C]92.7854[/C][C]0.292264[/C][C]-0.0376806[/C][/ROW]
[ROW][C]33[/C][C]93.04[/C][C]93.2131[/C][C]92.8596[/C][C]0.353514[/C][C]-0.173097[/C][/ROW]
[ROW][C]34[/C][C]92.83[/C][C]93.0284[/C][C]92.9787[/C][C]0.0496806[/C][C]-0.198431[/C][/ROW]
[ROW][C]35[/C][C]92.96[/C][C]93.2308[/C][C]93.145[/C][C]0.0858472[/C][C]-0.270847[/C][/ROW]
[ROW][C]36[/C][C]92.83[/C][C]92.9327[/C][C]93.3267[/C][C]-0.393986[/C][C]-0.102681[/C][/ROW]
[ROW][C]37[/C][C]93.01[/C][C]93.2362[/C][C]93.5167[/C][C]-0.280486[/C][C]-0.226181[/C][/ROW]
[ROW][C]38[/C][C]93.21[/C][C]93.4996[/C][C]93.7337[/C][C]-0.234153[/C][C]-0.289597[/C][/ROW]
[ROW][C]39[/C][C]93.58[/C][C]93.8398[/C][C]93.9937[/C][C]-0.153903[/C][C]-0.259847[/C][/ROW]
[ROW][C]40[/C][C]94.07[/C][C]94.1751[/C][C]94.2817[/C][C]-0.106569[/C][C]-0.105097[/C][/ROW]
[ROW][C]41[/C][C]94.57[/C][C]94.7185[/C][C]94.5846[/C][C]0.133931[/C][C]-0.148514[/C][/ROW]
[ROW][C]42[/C][C]95.03[/C][C]95.1128[/C][C]94.8862[/C][C]0.226597[/C][C]-0.0828472[/C][/ROW]
[ROW][C]43[/C][C]95.21[/C][C]95.2348[/C][C]95.2075[/C][C]0.0272639[/C][C]-0.0247639[/C][/ROW]
[ROW][C]44[/C][C]95.89[/C][C]95.8702[/C][C]95.5779[/C][C]0.292264[/C][C]0.0198194[/C][/ROW]
[ROW][C]45[/C][C]96.43[/C][C]96.3185[/C][C]95.965[/C][C]0.353514[/C][C]0.111486[/C][/ROW]
[ROW][C]46[/C][C]96.35[/C][C]96.3943[/C][C]96.3446[/C][C]0.0496806[/C][C]-0.0442639[/C][/ROW]
[ROW][C]47[/C][C]96.71[/C][C]96.815[/C][C]96.7292[/C][C]0.0858472[/C][C]-0.105014[/C][/ROW]
[ROW][C]48[/C][C]96.32[/C][C]96.7268[/C][C]97.1208[/C][C]-0.393986[/C][C]-0.406847[/C][/ROW]
[ROW][C]49[/C][C]97.23[/C][C]97.2245[/C][C]97.505[/C][C]-0.280486[/C][C]0.00548611[/C][/ROW]
[ROW][C]50[/C][C]97.88[/C][C]97.6763[/C][C]97.9104[/C][C]-0.234153[/C][C]0.203736[/C][/ROW]
[ROW][C]51[/C][C]98.2[/C][C]98.1944[/C][C]98.3483[/C][C]-0.153903[/C][C]0.00556944[/C][/ROW]
[ROW][C]52[/C][C]98.56[/C][C]98.6959[/C][C]98.8025[/C][C]-0.106569[/C][C]-0.135931[/C][/ROW]
[ROW][C]53[/C][C]99.31[/C][C]99.4102[/C][C]99.2762[/C][C]0.133931[/C][C]-0.100181[/C][/ROW]
[ROW][C]54[/C][C]99.69[/C][C]99.9853[/C][C]99.7588[/C][C]0.226597[/C][C]-0.295347[/C][/ROW]
[ROW][C]55[/C][C]99.77[/C][C]100.234[/C][C]100.207[/C][C]0.0272639[/C][C]-0.464347[/C][/ROW]
[ROW][C]56[/C][C]101.06[/C][C]100.91[/C][C]100.618[/C][C]0.292264[/C][C]0.150236[/C][/ROW]
[ROW][C]57[/C][C]101.77[/C][C]101.397[/C][C]101.043[/C][C]0.353514[/C][C]0.373153[/C][/ROW]
[ROW][C]58[/C][C]101.91[/C][C]101.56[/C][C]101.51[/C][C]0.0496806[/C][C]0.350319[/C][/ROW]
[ROW][C]59[/C][C]102.52[/C][C]102.066[/C][C]101.98[/C][C]0.0858472[/C][C]0.453736[/C][/ROW]
[ROW][C]60[/C][C]102.09[/C][C]102.029[/C][C]102.423[/C][C]-0.393986[/C][C]0.0610694[/C][/ROW]
[ROW][C]61[/C][C]102.22[/C][C]102.569[/C][C]102.85[/C][C]-0.280486[/C][C]-0.349097[/C][/ROW]
[ROW][C]62[/C][C]102.74[/C][C]102.989[/C][C]103.223[/C][C]-0.234153[/C][C]-0.249181[/C][/ROW]
[ROW][C]63[/C][C]103.56[/C][C]103.359[/C][C]103.513[/C][C]-0.153903[/C][C]0.200569[/C][/ROW]
[ROW][C]64[/C][C]104.4[/C][C]103.646[/C][C]103.752[/C][C]-0.106569[/C][C]0.754486[/C][/ROW]
[ROW][C]65[/C][C]104.76[/C][C]104.092[/C][C]103.958[/C][C]0.133931[/C][C]0.667736[/C][/ROW]
[ROW][C]66[/C][C]104.86[/C][C]104.367[/C][C]104.14[/C][C]0.226597[/C][C]0.493403[/C][/ROW]
[ROW][C]67[/C][C]104.84[/C][C]NA[/C][C]NA[/C][C]0.0272639[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]104.96[/C][C]NA[/C][C]NA[/C][C]0.292264[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]104.83[/C][C]NA[/C][C]NA[/C][C]0.353514[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]104.58[/C][C]NA[/C][C]NA[/C][C]0.0496806[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]104.8[/C][C]NA[/C][C]NA[/C][C]0.0858472[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]104.17[/C][C]NA[/C][C]NA[/C][C]-0.393986[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284435&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
189.56NANA-0.280486NA
289.84NANA-0.234153NA
389.97NANA-0.153903NA
490.65NANA-0.106569NA
591.17NANA0.133931NA
691.35NANA0.226597NA
791.4191.157791.13040.02726390.252319
891.5591.625691.33330.292264-0.0755972
991.6391.869391.51580.353514-0.239347
1091.5491.708491.65870.0496806-0.168431
1191.7491.856791.77080.0858472-0.116681
1291.8791.487791.8817-0.3939860.382319
1392.1391.709191.9896-0.2804860.420903
1492.1491.859292.0933-0.2341530.280819
1592.0592.041192.195-0.1539030.00890278
169292.18892.2946-0.106569-0.188014
1792.5192.518592.38460.133931-0.00851389
1892.6792.669592.44290.2265970.000486111
1992.6892.502392.4750.02726390.177736
2092.7792.795692.50330.292264-0.0255972
2192.8592.89192.53750.353514-0.0410139
2292.7192.61892.56830.04968060.0919861
2392.7392.6692.57420.08584720.0699861
2492.2892.182792.5767-0.3939860.0973194
2592.4992.309992.5904-0.2804860.180069
2692.4692.374692.6087-0.2341530.0854028
2792.5592.47492.6279-0.1539030.0759861
2892.2492.534392.6408-0.106569-0.294264
2992.4192.789392.65540.133931-0.379347
3092.8392.914592.68790.226597-0.0845139
3192.8592.759892.73250.02726390.0902361
3293.0493.077792.78540.292264-0.0376806
3393.0493.213192.85960.353514-0.173097
3492.8393.028492.97870.0496806-0.198431
3592.9693.230893.1450.0858472-0.270847
3692.8392.932793.3267-0.393986-0.102681
3793.0193.236293.5167-0.280486-0.226181
3893.2193.499693.7337-0.234153-0.289597
3993.5893.839893.9937-0.153903-0.259847
4094.0794.175194.2817-0.106569-0.105097
4194.5794.718594.58460.133931-0.148514
4295.0395.112894.88620.226597-0.0828472
4395.2195.234895.20750.0272639-0.0247639
4495.8995.870295.57790.2922640.0198194
4596.4396.318595.9650.3535140.111486
4696.3596.394396.34460.0496806-0.0442639
4796.7196.81596.72920.0858472-0.105014
4896.3296.726897.1208-0.393986-0.406847
4997.2397.224597.505-0.2804860.00548611
5097.8897.676397.9104-0.2341530.203736
5198.298.194498.3483-0.1539030.00556944
5298.5698.695998.8025-0.106569-0.135931
5399.3199.410299.27620.133931-0.100181
5499.6999.985399.75880.226597-0.295347
5599.77100.234100.2070.0272639-0.464347
56101.06100.91100.6180.2922640.150236
57101.77101.397101.0430.3535140.373153
58101.91101.56101.510.04968060.350319
59102.52102.066101.980.08584720.453736
60102.09102.029102.423-0.3939860.0610694
61102.22102.569102.85-0.280486-0.349097
62102.74102.989103.223-0.234153-0.249181
63103.56103.359103.513-0.1539030.200569
64104.4103.646103.752-0.1065690.754486
65104.76104.092103.9580.1339310.667736
66104.86104.367104.140.2265970.493403
67104.84NANA0.0272639NA
68104.96NANA0.292264NA
69104.83NANA0.353514NA
70104.58NANA0.0496806NA
71104.8NANA0.0858472NA
72104.17NANA-0.393986NA



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