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R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 05 Dec 2013 10:41:31 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/05/t1386258112u6s22jgvbxfgi1k.htm/, Retrieved Fri, 29 Mar 2024 10:30:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231152, Retrieved Fri, 29 Mar 2024 10:30:43 +0000
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Estimated Impact42
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-       [Classical Decomposition] [] [2013-12-05 15:41:31] [154a417cb3d2e1b589b01477b4193420] [Current]
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Dataseries X:
13953,3
14657,7
16686,2
15232,4
15014,1
16688,6
13969,6
14546,8
16292
15039
17433,8
17798,4
16870,9
16659,3
19620,4
15953,5
17420,9
17647,5
15200,8
15637,3
17124,5
17659,4
17815
16165,6
17416,6
16823,9
19171,2
16806,8
18112,8
18485,5
17668
16324,3
17877,5
20136,7
19307
17776,3
19861,3
18757
19879,3
21068,4
19358
20639,2
20008,1
18150,1
21180,4
20428,9
17241,2
15969,3
14972,4
14488,3
15885,1
14305,3
13891,5
15431,6
14199,3
13542,6
16226,3
16786,1
16034,3
16744,5
15896,5
15781,8
18590,3
17416,8
16983
18829,4
16748,6
16502,8
18616,6
19136,4
19523,9
18970,2
20118,2
20125,4
23117,8
20014,6
22228,5
20819,1
19208,9
19953,3
21041,3
20006,8
21045,1
20496,3
20873,5
21304,2
23137,8
20514,2
21343,5
20967,2
20024,4
19602,7
19804,1
22173,9
21802,6
19452,2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231152&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]5 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=231152&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231152&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
113953.3NANA-125.926NA
214657.7NANA-487.704NA
316686.2NANA1670.15NA
415232.4NANA-296.408NA
515014.1NANA100.632NA
616688.6NANA562.112NA
713969.614740.715730.9-990.186-771.106
814546.814529.815935.9-1406.117.039
91629216614.816141.5473.281-322.797
101503916816.516293.8522.682-1777.5
1117433.816764.416424.2340.282669.368
1217798.416201.616564.4-362.8181596.83
1316870.916529.716655.6-125.926341.185
1416659.316264.716752.4-487.704394.625
1519620.418502.716832.51670.151117.74
1615953.51668016976.4-296.408-726.467
1717420.917202.117101.4100.632218.826
1817647.517611.417049.3562.11236.0967
1915200.816013.817004-990.186-813.01
2015637.315627.517033.6-1406.19.80565
2117124.51749517021.7473.281-370.514
2217659.417561.317038.6522.68298.1473
231781517443.217103340.282371.764
2416165.616803.917166.7-362.818-638.282
2517416.617178.517304.4-125.926238.11
2616823.916948.117435.8-487.704-124.237
2719171.21916617495.81670.155.20565
2816806.81733417630.4-296.408-527.229
2918112.817896.517795.8100.632216.343
3018485.518487.217925.1562.112-1.71577
311766817103.918094.1-990.186564.107
3216324.316870.418276.5-1406.1-546.09
3317877.518859.818386.5473.281-982.318
3420136.719116.318593.6522.6821020.41
351930719163.318823.1340.282143.66
3617776.318601.918964.7-362.818-825.561
3719861.31902619151.9-125.926835.306
381875718837.819325.5-487.704-80.7955
3919879.321209.319539.21670.15-1330.05
4021068.419392.619689-296.4081675.82
411935819715.719615.1100.632-357.724
4220639.220015.819453.7562.112623.363
4320008.118184.519174.7-990.1861823.56
4418150.117387.118793.2-1406.1763.035
4521180.418922.218448.9473.2812258.24
4620428.918523.318000.7522.6821905.56
4717241.217831.417491.1340.282-590.169
4815969.316683.517046.3-362.818-714.215
4914972.416461.416587.3-125.926-1488.99
5014488.315665.616153.3-487.704-1177.3
5115885.117425.115754.91670.15-1539.96
5214305.315100.315396.7-296.408-794.992
5313891.515295.315194.6100.632-1403.76
5415431.615738.815176.6562.112-307.153
5514199.314257.315247.4-990.186-57.9598
5613542.613933.715339.8-1406.1-391.149
5716226.315979.715506.5473.281246.561
5816786.116271.515748.8522.682514.597
5916034.316347.616007.3340.282-313.261
6016744.515914.816277.7-362.818829.651
6115896.516399.516525.5-125.926-503.036
6215781.816267.316755-487.704-485.521
6318590.318648.1169781670.15-57.8152
6417416.816879.117175.5-296.408537.721
651698317519.417418.8100.632-536.449
6618829.418219.117657562.112610.334
6716748.616935.417925.6-990.186-186.81
6816502.816876.418282.5-1406.1-373.586
6918616.619125.418652.1473.281-508.793
7019136.419471.718949522.682-335.282
7119523.919616.119275.8340.282-92.186
7218970.219214.519577.3-362.818-244.253
7320118.219636.819762.7-125.926481.439
7420125.419521.320009-487.704604.134
7523117.821923.920253.81670.151193.88
7620014.620094.720391.1-296.408-80.0586
7722228.520591.320490.7100.6321637.15
7820819.121179.820617.7562.112-360.699
7919208.919722.620712.7-990.186-513.66
8019953.319387.220793.3-1406.1566.064
8121041.321316.620843.3473.281-275.264
8220006.821387.620864.9522.682-1380.82
8321045.121189.220848.9340.282-144.057
8420496.320455.420818.2-362.81840.9473
8520873.520732.420858.3-125.926141.106
8621304.22039020877.7-487.704914.213
8723137.822481.720811.51670.15656.114
8820514.220553.920850.3-296.408-39.6711
8921343.521072.820972.1100.632270.731
9020967.221522.320960.2562.112-555.107
9120024.4NANA-990.186NA
9219602.7NANA-1406.1NA
9319804.1NANA473.281NA
9422173.9NANA522.682NA
9521802.6NANA340.282NA
9619452.2NANA-362.818NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 13953.3 & NA & NA & -125.926 & NA \tabularnewline
2 & 14657.7 & NA & NA & -487.704 & NA \tabularnewline
3 & 16686.2 & NA & NA & 1670.15 & NA \tabularnewline
4 & 15232.4 & NA & NA & -296.408 & NA \tabularnewline
5 & 15014.1 & NA & NA & 100.632 & NA \tabularnewline
6 & 16688.6 & NA & NA & 562.112 & NA \tabularnewline
7 & 13969.6 & 14740.7 & 15730.9 & -990.186 & -771.106 \tabularnewline
8 & 14546.8 & 14529.8 & 15935.9 & -1406.1 & 17.039 \tabularnewline
9 & 16292 & 16614.8 & 16141.5 & 473.281 & -322.797 \tabularnewline
10 & 15039 & 16816.5 & 16293.8 & 522.682 & -1777.5 \tabularnewline
11 & 17433.8 & 16764.4 & 16424.2 & 340.282 & 669.368 \tabularnewline
12 & 17798.4 & 16201.6 & 16564.4 & -362.818 & 1596.83 \tabularnewline
13 & 16870.9 & 16529.7 & 16655.6 & -125.926 & 341.185 \tabularnewline
14 & 16659.3 & 16264.7 & 16752.4 & -487.704 & 394.625 \tabularnewline
15 & 19620.4 & 18502.7 & 16832.5 & 1670.15 & 1117.74 \tabularnewline
16 & 15953.5 & 16680 & 16976.4 & -296.408 & -726.467 \tabularnewline
17 & 17420.9 & 17202.1 & 17101.4 & 100.632 & 218.826 \tabularnewline
18 & 17647.5 & 17611.4 & 17049.3 & 562.112 & 36.0967 \tabularnewline
19 & 15200.8 & 16013.8 & 17004 & -990.186 & -813.01 \tabularnewline
20 & 15637.3 & 15627.5 & 17033.6 & -1406.1 & 9.80565 \tabularnewline
21 & 17124.5 & 17495 & 17021.7 & 473.281 & -370.514 \tabularnewline
22 & 17659.4 & 17561.3 & 17038.6 & 522.682 & 98.1473 \tabularnewline
23 & 17815 & 17443.2 & 17103 & 340.282 & 371.764 \tabularnewline
24 & 16165.6 & 16803.9 & 17166.7 & -362.818 & -638.282 \tabularnewline
25 & 17416.6 & 17178.5 & 17304.4 & -125.926 & 238.11 \tabularnewline
26 & 16823.9 & 16948.1 & 17435.8 & -487.704 & -124.237 \tabularnewline
27 & 19171.2 & 19166 & 17495.8 & 1670.15 & 5.20565 \tabularnewline
28 & 16806.8 & 17334 & 17630.4 & -296.408 & -527.229 \tabularnewline
29 & 18112.8 & 17896.5 & 17795.8 & 100.632 & 216.343 \tabularnewline
30 & 18485.5 & 18487.2 & 17925.1 & 562.112 & -1.71577 \tabularnewline
31 & 17668 & 17103.9 & 18094.1 & -990.186 & 564.107 \tabularnewline
32 & 16324.3 & 16870.4 & 18276.5 & -1406.1 & -546.09 \tabularnewline
33 & 17877.5 & 18859.8 & 18386.5 & 473.281 & -982.318 \tabularnewline
34 & 20136.7 & 19116.3 & 18593.6 & 522.682 & 1020.41 \tabularnewline
35 & 19307 & 19163.3 & 18823.1 & 340.282 & 143.66 \tabularnewline
36 & 17776.3 & 18601.9 & 18964.7 & -362.818 & -825.561 \tabularnewline
37 & 19861.3 & 19026 & 19151.9 & -125.926 & 835.306 \tabularnewline
38 & 18757 & 18837.8 & 19325.5 & -487.704 & -80.7955 \tabularnewline
39 & 19879.3 & 21209.3 & 19539.2 & 1670.15 & -1330.05 \tabularnewline
40 & 21068.4 & 19392.6 & 19689 & -296.408 & 1675.82 \tabularnewline
41 & 19358 & 19715.7 & 19615.1 & 100.632 & -357.724 \tabularnewline
42 & 20639.2 & 20015.8 & 19453.7 & 562.112 & 623.363 \tabularnewline
43 & 20008.1 & 18184.5 & 19174.7 & -990.186 & 1823.56 \tabularnewline
44 & 18150.1 & 17387.1 & 18793.2 & -1406.1 & 763.035 \tabularnewline
45 & 21180.4 & 18922.2 & 18448.9 & 473.281 & 2258.24 \tabularnewline
46 & 20428.9 & 18523.3 & 18000.7 & 522.682 & 1905.56 \tabularnewline
47 & 17241.2 & 17831.4 & 17491.1 & 340.282 & -590.169 \tabularnewline
48 & 15969.3 & 16683.5 & 17046.3 & -362.818 & -714.215 \tabularnewline
49 & 14972.4 & 16461.4 & 16587.3 & -125.926 & -1488.99 \tabularnewline
50 & 14488.3 & 15665.6 & 16153.3 & -487.704 & -1177.3 \tabularnewline
51 & 15885.1 & 17425.1 & 15754.9 & 1670.15 & -1539.96 \tabularnewline
52 & 14305.3 & 15100.3 & 15396.7 & -296.408 & -794.992 \tabularnewline
53 & 13891.5 & 15295.3 & 15194.6 & 100.632 & -1403.76 \tabularnewline
54 & 15431.6 & 15738.8 & 15176.6 & 562.112 & -307.153 \tabularnewline
55 & 14199.3 & 14257.3 & 15247.4 & -990.186 & -57.9598 \tabularnewline
56 & 13542.6 & 13933.7 & 15339.8 & -1406.1 & -391.149 \tabularnewline
57 & 16226.3 & 15979.7 & 15506.5 & 473.281 & 246.561 \tabularnewline
58 & 16786.1 & 16271.5 & 15748.8 & 522.682 & 514.597 \tabularnewline
59 & 16034.3 & 16347.6 & 16007.3 & 340.282 & -313.261 \tabularnewline
60 & 16744.5 & 15914.8 & 16277.7 & -362.818 & 829.651 \tabularnewline
61 & 15896.5 & 16399.5 & 16525.5 & -125.926 & -503.036 \tabularnewline
62 & 15781.8 & 16267.3 & 16755 & -487.704 & -485.521 \tabularnewline
63 & 18590.3 & 18648.1 & 16978 & 1670.15 & -57.8152 \tabularnewline
64 & 17416.8 & 16879.1 & 17175.5 & -296.408 & 537.721 \tabularnewline
65 & 16983 & 17519.4 & 17418.8 & 100.632 & -536.449 \tabularnewline
66 & 18829.4 & 18219.1 & 17657 & 562.112 & 610.334 \tabularnewline
67 & 16748.6 & 16935.4 & 17925.6 & -990.186 & -186.81 \tabularnewline
68 & 16502.8 & 16876.4 & 18282.5 & -1406.1 & -373.586 \tabularnewline
69 & 18616.6 & 19125.4 & 18652.1 & 473.281 & -508.793 \tabularnewline
70 & 19136.4 & 19471.7 & 18949 & 522.682 & -335.282 \tabularnewline
71 & 19523.9 & 19616.1 & 19275.8 & 340.282 & -92.186 \tabularnewline
72 & 18970.2 & 19214.5 & 19577.3 & -362.818 & -244.253 \tabularnewline
73 & 20118.2 & 19636.8 & 19762.7 & -125.926 & 481.439 \tabularnewline
74 & 20125.4 & 19521.3 & 20009 & -487.704 & 604.134 \tabularnewline
75 & 23117.8 & 21923.9 & 20253.8 & 1670.15 & 1193.88 \tabularnewline
76 & 20014.6 & 20094.7 & 20391.1 & -296.408 & -80.0586 \tabularnewline
77 & 22228.5 & 20591.3 & 20490.7 & 100.632 & 1637.15 \tabularnewline
78 & 20819.1 & 21179.8 & 20617.7 & 562.112 & -360.699 \tabularnewline
79 & 19208.9 & 19722.6 & 20712.7 & -990.186 & -513.66 \tabularnewline
80 & 19953.3 & 19387.2 & 20793.3 & -1406.1 & 566.064 \tabularnewline
81 & 21041.3 & 21316.6 & 20843.3 & 473.281 & -275.264 \tabularnewline
82 & 20006.8 & 21387.6 & 20864.9 & 522.682 & -1380.82 \tabularnewline
83 & 21045.1 & 21189.2 & 20848.9 & 340.282 & -144.057 \tabularnewline
84 & 20496.3 & 20455.4 & 20818.2 & -362.818 & 40.9473 \tabularnewline
85 & 20873.5 & 20732.4 & 20858.3 & -125.926 & 141.106 \tabularnewline
86 & 21304.2 & 20390 & 20877.7 & -487.704 & 914.213 \tabularnewline
87 & 23137.8 & 22481.7 & 20811.5 & 1670.15 & 656.114 \tabularnewline
88 & 20514.2 & 20553.9 & 20850.3 & -296.408 & -39.6711 \tabularnewline
89 & 21343.5 & 21072.8 & 20972.1 & 100.632 & 270.731 \tabularnewline
90 & 20967.2 & 21522.3 & 20960.2 & 562.112 & -555.107 \tabularnewline
91 & 20024.4 & NA & NA & -990.186 & NA \tabularnewline
92 & 19602.7 & NA & NA & -1406.1 & NA \tabularnewline
93 & 19804.1 & NA & NA & 473.281 & NA \tabularnewline
94 & 22173.9 & NA & NA & 522.682 & NA \tabularnewline
95 & 21802.6 & NA & NA & 340.282 & NA \tabularnewline
96 & 19452.2 & NA & NA & -362.818 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231152&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]13953.3[/C][C]NA[/C][C]NA[/C][C]-125.926[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]14657.7[/C][C]NA[/C][C]NA[/C][C]-487.704[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]16686.2[/C][C]NA[/C][C]NA[/C][C]1670.15[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]15232.4[/C][C]NA[/C][C]NA[/C][C]-296.408[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]15014.1[/C][C]NA[/C][C]NA[/C][C]100.632[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]16688.6[/C][C]NA[/C][C]NA[/C][C]562.112[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]13969.6[/C][C]14740.7[/C][C]15730.9[/C][C]-990.186[/C][C]-771.106[/C][/ROW]
[ROW][C]8[/C][C]14546.8[/C][C]14529.8[/C][C]15935.9[/C][C]-1406.1[/C][C]17.039[/C][/ROW]
[ROW][C]9[/C][C]16292[/C][C]16614.8[/C][C]16141.5[/C][C]473.281[/C][C]-322.797[/C][/ROW]
[ROW][C]10[/C][C]15039[/C][C]16816.5[/C][C]16293.8[/C][C]522.682[/C][C]-1777.5[/C][/ROW]
[ROW][C]11[/C][C]17433.8[/C][C]16764.4[/C][C]16424.2[/C][C]340.282[/C][C]669.368[/C][/ROW]
[ROW][C]12[/C][C]17798.4[/C][C]16201.6[/C][C]16564.4[/C][C]-362.818[/C][C]1596.83[/C][/ROW]
[ROW][C]13[/C][C]16870.9[/C][C]16529.7[/C][C]16655.6[/C][C]-125.926[/C][C]341.185[/C][/ROW]
[ROW][C]14[/C][C]16659.3[/C][C]16264.7[/C][C]16752.4[/C][C]-487.704[/C][C]394.625[/C][/ROW]
[ROW][C]15[/C][C]19620.4[/C][C]18502.7[/C][C]16832.5[/C][C]1670.15[/C][C]1117.74[/C][/ROW]
[ROW][C]16[/C][C]15953.5[/C][C]16680[/C][C]16976.4[/C][C]-296.408[/C][C]-726.467[/C][/ROW]
[ROW][C]17[/C][C]17420.9[/C][C]17202.1[/C][C]17101.4[/C][C]100.632[/C][C]218.826[/C][/ROW]
[ROW][C]18[/C][C]17647.5[/C][C]17611.4[/C][C]17049.3[/C][C]562.112[/C][C]36.0967[/C][/ROW]
[ROW][C]19[/C][C]15200.8[/C][C]16013.8[/C][C]17004[/C][C]-990.186[/C][C]-813.01[/C][/ROW]
[ROW][C]20[/C][C]15637.3[/C][C]15627.5[/C][C]17033.6[/C][C]-1406.1[/C][C]9.80565[/C][/ROW]
[ROW][C]21[/C][C]17124.5[/C][C]17495[/C][C]17021.7[/C][C]473.281[/C][C]-370.514[/C][/ROW]
[ROW][C]22[/C][C]17659.4[/C][C]17561.3[/C][C]17038.6[/C][C]522.682[/C][C]98.1473[/C][/ROW]
[ROW][C]23[/C][C]17815[/C][C]17443.2[/C][C]17103[/C][C]340.282[/C][C]371.764[/C][/ROW]
[ROW][C]24[/C][C]16165.6[/C][C]16803.9[/C][C]17166.7[/C][C]-362.818[/C][C]-638.282[/C][/ROW]
[ROW][C]25[/C][C]17416.6[/C][C]17178.5[/C][C]17304.4[/C][C]-125.926[/C][C]238.11[/C][/ROW]
[ROW][C]26[/C][C]16823.9[/C][C]16948.1[/C][C]17435.8[/C][C]-487.704[/C][C]-124.237[/C][/ROW]
[ROW][C]27[/C][C]19171.2[/C][C]19166[/C][C]17495.8[/C][C]1670.15[/C][C]5.20565[/C][/ROW]
[ROW][C]28[/C][C]16806.8[/C][C]17334[/C][C]17630.4[/C][C]-296.408[/C][C]-527.229[/C][/ROW]
[ROW][C]29[/C][C]18112.8[/C][C]17896.5[/C][C]17795.8[/C][C]100.632[/C][C]216.343[/C][/ROW]
[ROW][C]30[/C][C]18485.5[/C][C]18487.2[/C][C]17925.1[/C][C]562.112[/C][C]-1.71577[/C][/ROW]
[ROW][C]31[/C][C]17668[/C][C]17103.9[/C][C]18094.1[/C][C]-990.186[/C][C]564.107[/C][/ROW]
[ROW][C]32[/C][C]16324.3[/C][C]16870.4[/C][C]18276.5[/C][C]-1406.1[/C][C]-546.09[/C][/ROW]
[ROW][C]33[/C][C]17877.5[/C][C]18859.8[/C][C]18386.5[/C][C]473.281[/C][C]-982.318[/C][/ROW]
[ROW][C]34[/C][C]20136.7[/C][C]19116.3[/C][C]18593.6[/C][C]522.682[/C][C]1020.41[/C][/ROW]
[ROW][C]35[/C][C]19307[/C][C]19163.3[/C][C]18823.1[/C][C]340.282[/C][C]143.66[/C][/ROW]
[ROW][C]36[/C][C]17776.3[/C][C]18601.9[/C][C]18964.7[/C][C]-362.818[/C][C]-825.561[/C][/ROW]
[ROW][C]37[/C][C]19861.3[/C][C]19026[/C][C]19151.9[/C][C]-125.926[/C][C]835.306[/C][/ROW]
[ROW][C]38[/C][C]18757[/C][C]18837.8[/C][C]19325.5[/C][C]-487.704[/C][C]-80.7955[/C][/ROW]
[ROW][C]39[/C][C]19879.3[/C][C]21209.3[/C][C]19539.2[/C][C]1670.15[/C][C]-1330.05[/C][/ROW]
[ROW][C]40[/C][C]21068.4[/C][C]19392.6[/C][C]19689[/C][C]-296.408[/C][C]1675.82[/C][/ROW]
[ROW][C]41[/C][C]19358[/C][C]19715.7[/C][C]19615.1[/C][C]100.632[/C][C]-357.724[/C][/ROW]
[ROW][C]42[/C][C]20639.2[/C][C]20015.8[/C][C]19453.7[/C][C]562.112[/C][C]623.363[/C][/ROW]
[ROW][C]43[/C][C]20008.1[/C][C]18184.5[/C][C]19174.7[/C][C]-990.186[/C][C]1823.56[/C][/ROW]
[ROW][C]44[/C][C]18150.1[/C][C]17387.1[/C][C]18793.2[/C][C]-1406.1[/C][C]763.035[/C][/ROW]
[ROW][C]45[/C][C]21180.4[/C][C]18922.2[/C][C]18448.9[/C][C]473.281[/C][C]2258.24[/C][/ROW]
[ROW][C]46[/C][C]20428.9[/C][C]18523.3[/C][C]18000.7[/C][C]522.682[/C][C]1905.56[/C][/ROW]
[ROW][C]47[/C][C]17241.2[/C][C]17831.4[/C][C]17491.1[/C][C]340.282[/C][C]-590.169[/C][/ROW]
[ROW][C]48[/C][C]15969.3[/C][C]16683.5[/C][C]17046.3[/C][C]-362.818[/C][C]-714.215[/C][/ROW]
[ROW][C]49[/C][C]14972.4[/C][C]16461.4[/C][C]16587.3[/C][C]-125.926[/C][C]-1488.99[/C][/ROW]
[ROW][C]50[/C][C]14488.3[/C][C]15665.6[/C][C]16153.3[/C][C]-487.704[/C][C]-1177.3[/C][/ROW]
[ROW][C]51[/C][C]15885.1[/C][C]17425.1[/C][C]15754.9[/C][C]1670.15[/C][C]-1539.96[/C][/ROW]
[ROW][C]52[/C][C]14305.3[/C][C]15100.3[/C][C]15396.7[/C][C]-296.408[/C][C]-794.992[/C][/ROW]
[ROW][C]53[/C][C]13891.5[/C][C]15295.3[/C][C]15194.6[/C][C]100.632[/C][C]-1403.76[/C][/ROW]
[ROW][C]54[/C][C]15431.6[/C][C]15738.8[/C][C]15176.6[/C][C]562.112[/C][C]-307.153[/C][/ROW]
[ROW][C]55[/C][C]14199.3[/C][C]14257.3[/C][C]15247.4[/C][C]-990.186[/C][C]-57.9598[/C][/ROW]
[ROW][C]56[/C][C]13542.6[/C][C]13933.7[/C][C]15339.8[/C][C]-1406.1[/C][C]-391.149[/C][/ROW]
[ROW][C]57[/C][C]16226.3[/C][C]15979.7[/C][C]15506.5[/C][C]473.281[/C][C]246.561[/C][/ROW]
[ROW][C]58[/C][C]16786.1[/C][C]16271.5[/C][C]15748.8[/C][C]522.682[/C][C]514.597[/C][/ROW]
[ROW][C]59[/C][C]16034.3[/C][C]16347.6[/C][C]16007.3[/C][C]340.282[/C][C]-313.261[/C][/ROW]
[ROW][C]60[/C][C]16744.5[/C][C]15914.8[/C][C]16277.7[/C][C]-362.818[/C][C]829.651[/C][/ROW]
[ROW][C]61[/C][C]15896.5[/C][C]16399.5[/C][C]16525.5[/C][C]-125.926[/C][C]-503.036[/C][/ROW]
[ROW][C]62[/C][C]15781.8[/C][C]16267.3[/C][C]16755[/C][C]-487.704[/C][C]-485.521[/C][/ROW]
[ROW][C]63[/C][C]18590.3[/C][C]18648.1[/C][C]16978[/C][C]1670.15[/C][C]-57.8152[/C][/ROW]
[ROW][C]64[/C][C]17416.8[/C][C]16879.1[/C][C]17175.5[/C][C]-296.408[/C][C]537.721[/C][/ROW]
[ROW][C]65[/C][C]16983[/C][C]17519.4[/C][C]17418.8[/C][C]100.632[/C][C]-536.449[/C][/ROW]
[ROW][C]66[/C][C]18829.4[/C][C]18219.1[/C][C]17657[/C][C]562.112[/C][C]610.334[/C][/ROW]
[ROW][C]67[/C][C]16748.6[/C][C]16935.4[/C][C]17925.6[/C][C]-990.186[/C][C]-186.81[/C][/ROW]
[ROW][C]68[/C][C]16502.8[/C][C]16876.4[/C][C]18282.5[/C][C]-1406.1[/C][C]-373.586[/C][/ROW]
[ROW][C]69[/C][C]18616.6[/C][C]19125.4[/C][C]18652.1[/C][C]473.281[/C][C]-508.793[/C][/ROW]
[ROW][C]70[/C][C]19136.4[/C][C]19471.7[/C][C]18949[/C][C]522.682[/C][C]-335.282[/C][/ROW]
[ROW][C]71[/C][C]19523.9[/C][C]19616.1[/C][C]19275.8[/C][C]340.282[/C][C]-92.186[/C][/ROW]
[ROW][C]72[/C][C]18970.2[/C][C]19214.5[/C][C]19577.3[/C][C]-362.818[/C][C]-244.253[/C][/ROW]
[ROW][C]73[/C][C]20118.2[/C][C]19636.8[/C][C]19762.7[/C][C]-125.926[/C][C]481.439[/C][/ROW]
[ROW][C]74[/C][C]20125.4[/C][C]19521.3[/C][C]20009[/C][C]-487.704[/C][C]604.134[/C][/ROW]
[ROW][C]75[/C][C]23117.8[/C][C]21923.9[/C][C]20253.8[/C][C]1670.15[/C][C]1193.88[/C][/ROW]
[ROW][C]76[/C][C]20014.6[/C][C]20094.7[/C][C]20391.1[/C][C]-296.408[/C][C]-80.0586[/C][/ROW]
[ROW][C]77[/C][C]22228.5[/C][C]20591.3[/C][C]20490.7[/C][C]100.632[/C][C]1637.15[/C][/ROW]
[ROW][C]78[/C][C]20819.1[/C][C]21179.8[/C][C]20617.7[/C][C]562.112[/C][C]-360.699[/C][/ROW]
[ROW][C]79[/C][C]19208.9[/C][C]19722.6[/C][C]20712.7[/C][C]-990.186[/C][C]-513.66[/C][/ROW]
[ROW][C]80[/C][C]19953.3[/C][C]19387.2[/C][C]20793.3[/C][C]-1406.1[/C][C]566.064[/C][/ROW]
[ROW][C]81[/C][C]21041.3[/C][C]21316.6[/C][C]20843.3[/C][C]473.281[/C][C]-275.264[/C][/ROW]
[ROW][C]82[/C][C]20006.8[/C][C]21387.6[/C][C]20864.9[/C][C]522.682[/C][C]-1380.82[/C][/ROW]
[ROW][C]83[/C][C]21045.1[/C][C]21189.2[/C][C]20848.9[/C][C]340.282[/C][C]-144.057[/C][/ROW]
[ROW][C]84[/C][C]20496.3[/C][C]20455.4[/C][C]20818.2[/C][C]-362.818[/C][C]40.9473[/C][/ROW]
[ROW][C]85[/C][C]20873.5[/C][C]20732.4[/C][C]20858.3[/C][C]-125.926[/C][C]141.106[/C][/ROW]
[ROW][C]86[/C][C]21304.2[/C][C]20390[/C][C]20877.7[/C][C]-487.704[/C][C]914.213[/C][/ROW]
[ROW][C]87[/C][C]23137.8[/C][C]22481.7[/C][C]20811.5[/C][C]1670.15[/C][C]656.114[/C][/ROW]
[ROW][C]88[/C][C]20514.2[/C][C]20553.9[/C][C]20850.3[/C][C]-296.408[/C][C]-39.6711[/C][/ROW]
[ROW][C]89[/C][C]21343.5[/C][C]21072.8[/C][C]20972.1[/C][C]100.632[/C][C]270.731[/C][/ROW]
[ROW][C]90[/C][C]20967.2[/C][C]21522.3[/C][C]20960.2[/C][C]562.112[/C][C]-555.107[/C][/ROW]
[ROW][C]91[/C][C]20024.4[/C][C]NA[/C][C]NA[/C][C]-990.186[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]19602.7[/C][C]NA[/C][C]NA[/C][C]-1406.1[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]19804.1[/C][C]NA[/C][C]NA[/C][C]473.281[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]22173.9[/C][C]NA[/C][C]NA[/C][C]522.682[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]21802.6[/C][C]NA[/C][C]NA[/C][C]340.282[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]19452.2[/C][C]NA[/C][C]NA[/C][C]-362.818[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231152&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231152&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
113953.3NANA-125.926NA
214657.7NANA-487.704NA
316686.2NANA1670.15NA
415232.4NANA-296.408NA
515014.1NANA100.632NA
616688.6NANA562.112NA
713969.614740.715730.9-990.186-771.106
814546.814529.815935.9-1406.117.039
91629216614.816141.5473.281-322.797
101503916816.516293.8522.682-1777.5
1117433.816764.416424.2340.282669.368
1217798.416201.616564.4-362.8181596.83
1316870.916529.716655.6-125.926341.185
1416659.316264.716752.4-487.704394.625
1519620.418502.716832.51670.151117.74
1615953.51668016976.4-296.408-726.467
1717420.917202.117101.4100.632218.826
1817647.517611.417049.3562.11236.0967
1915200.816013.817004-990.186-813.01
2015637.315627.517033.6-1406.19.80565
2117124.51749517021.7473.281-370.514
2217659.417561.317038.6522.68298.1473
231781517443.217103340.282371.764
2416165.616803.917166.7-362.818-638.282
2517416.617178.517304.4-125.926238.11
2616823.916948.117435.8-487.704-124.237
2719171.21916617495.81670.155.20565
2816806.81733417630.4-296.408-527.229
2918112.817896.517795.8100.632216.343
3018485.518487.217925.1562.112-1.71577
311766817103.918094.1-990.186564.107
3216324.316870.418276.5-1406.1-546.09
3317877.518859.818386.5473.281-982.318
3420136.719116.318593.6522.6821020.41
351930719163.318823.1340.282143.66
3617776.318601.918964.7-362.818-825.561
3719861.31902619151.9-125.926835.306
381875718837.819325.5-487.704-80.7955
3919879.321209.319539.21670.15-1330.05
4021068.419392.619689-296.4081675.82
411935819715.719615.1100.632-357.724
4220639.220015.819453.7562.112623.363
4320008.118184.519174.7-990.1861823.56
4418150.117387.118793.2-1406.1763.035
4521180.418922.218448.9473.2812258.24
4620428.918523.318000.7522.6821905.56
4717241.217831.417491.1340.282-590.169
4815969.316683.517046.3-362.818-714.215
4914972.416461.416587.3-125.926-1488.99
5014488.315665.616153.3-487.704-1177.3
5115885.117425.115754.91670.15-1539.96
5214305.315100.315396.7-296.408-794.992
5313891.515295.315194.6100.632-1403.76
5415431.615738.815176.6562.112-307.153
5514199.314257.315247.4-990.186-57.9598
5613542.613933.715339.8-1406.1-391.149
5716226.315979.715506.5473.281246.561
5816786.116271.515748.8522.682514.597
5916034.316347.616007.3340.282-313.261
6016744.515914.816277.7-362.818829.651
6115896.516399.516525.5-125.926-503.036
6215781.816267.316755-487.704-485.521
6318590.318648.1169781670.15-57.8152
6417416.816879.117175.5-296.408537.721
651698317519.417418.8100.632-536.449
6618829.418219.117657562.112610.334
6716748.616935.417925.6-990.186-186.81
6816502.816876.418282.5-1406.1-373.586
6918616.619125.418652.1473.281-508.793
7019136.419471.718949522.682-335.282
7119523.919616.119275.8340.282-92.186
7218970.219214.519577.3-362.818-244.253
7320118.219636.819762.7-125.926481.439
7420125.419521.320009-487.704604.134
7523117.821923.920253.81670.151193.88
7620014.620094.720391.1-296.408-80.0586
7722228.520591.320490.7100.6321637.15
7820819.121179.820617.7562.112-360.699
7919208.919722.620712.7-990.186-513.66
8019953.319387.220793.3-1406.1566.064
8121041.321316.620843.3473.281-275.264
8220006.821387.620864.9522.682-1380.82
8321045.121189.220848.9340.282-144.057
8420496.320455.420818.2-362.81840.9473
8520873.520732.420858.3-125.926141.106
8621304.22039020877.7-487.704914.213
8723137.822481.720811.51670.15656.114
8820514.220553.920850.3-296.408-39.6711
8921343.521072.820972.1100.632270.731
9020967.221522.320960.2562.112-555.107
9120024.4NANA-990.186NA
9219602.7NANA-1406.1NA
9319804.1NANA473.281NA
9422173.9NANA522.682NA
9521802.6NANA340.282NA
9619452.2NANA-362.818NA



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')