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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 02 Apr 2015 22:04:48 +0100
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/Apr/02/t1428008858djc0z7cp1qalgbg.htm/, Retrieved Thu, 09 May 2024 18:38:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278664, Retrieved Thu, 09 May 2024 18:38:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact69

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2015-04-02 21:04:48] [9c6f291f5313961eaf08153dbee9a7d3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12374,6
12864,7
14905,8
12259,7
14088,9
14243,7
12732,8
11612
14176,6
14452,6
14512,7
12645,1
13820,5
13644,7
15684,1
13568,3
14531,1
15320,1
14344,2
12899,4
14462
16044,7
14731,2
12798,3
14213,1
14683,3
14652
15623,1
14880,4
15765,7
15433,1
12402,6
15639,8
14861,7
11699,4
10651,9
10086,9
10676,9
11332,1
10756,1
10450,5
11930,2
11419,9
9713,1
12608,5
12357,2
12107,9
11627,2
11105,9
11841,6
14290,8
13271,7
12909,4
14924,1
13257,4
12184,4
15035,5
14401
14165
13375,6
14210,8
15017,5
17157,8
15106,2
16696,1
16035,9
15418,9
13763,9
15595,2
15183,1
15515,9
14142,8
15012,7
16293,2
17771,4
15582,8
16049,9
16105,8
15623,6
14254,9
15266,8
16671
15665,4
13949,5
15146,9
15172,9
16981,4
16553,8
16438,5
15895,1
16989
13803,5
16678,3
17315,1
15895,4
14912,1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278664&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278664&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278664&T=0

As an alternative you can also use a QR Code:  
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'Herman Ole Andreas Wold' @ wold.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
112374.6NANA-772.888NA
212864.7NANA-277.939NA
314905.8NANA1199.77NA
412259.7NANA109.61NA
514088.9NANA297.755NA
614243.7NANA850.459NA
712732.813547.81346681.7588-814.971
81161211981.813558.8-1577-369.762
914176.614299.813623.7676.067-123.154
1014452.614518.413710.6807.709-65.7505
1114512.713755.513783.6-28.0941757.202
1212645.112479.713846.9-1367.21165.443
1313820.51318613958.9-772.888634.53
1413644.713801.714079.6-277.939-157.003
1515684.115344.914145.21199.77339.157
1613568.31433314223.4109.61-764.714
1714531.114596.614298.8297.755-65.5011
1815320.115164.814314.3850.459155.307
1914344.214418.814337.181.7588-74.6338
2012899.412819.714396.7-157779.6882
21144621507314397676.067-611.046
2216044.715247.314439.6807.709797.4
2314731.214511.714539.8-28.0941219.532
2412798.313205.714572.9-1367.21-407.374
2514213.113863.914636.8-772.888349.167
2614683.314383.614661.5-277.939299.747
271465215889.614689.91199.77-1237.64
2815623.114799.314689.6109.61823.84
2914880.414811.814514297.75568.6114
3015765.715148.714298.3850.459616.966
3115433.114118.714036.981.75881314.42
3212402.612121.113698.1-1577281.538
3315639.814068.913392.8676.0671570.94
3414861.713859.413051.7807.7091002.32
3511699.412636.212664.3-28.0941-936.81
3610651.910952.712319.9-1367.21-300.803
3710086.91122011992.9-772.888-1133.1
3810676.911435.711713.6-277.939-758.765
3911332.11267511475.21199.77-1342.91
4010756.111354.211244.6109.61-598.089
4110450.51145511157.2297.755-1004.5
4211930.212065.411214.9850.459-135.164
4311419.911379.81129881.758840.1412
449713.19811.9911389-1577-98.891
4512608.512236.911560.8676.067371.638
4612357.212596.611788.9807.709-239.4
4712107.911968.111996.2-28.0941139.832
4811627.210856.212223.4-1367.21771.047
4911105.911651.812424.7-772.888-545.883
5011841.612326.312604.2-277.939-484.665
5114290.814008.112808.31199.77282.732
5213271.713104.212994.6109.61167.507
5312909.413463.213165.5297.755-553.809
5414924.114174.513324850.459749.624
5513257.41360813526.281.7588-350.596
5612184.412210.913787.9-1577-26.541
5715035.514715.814039.7676.067319.708
581440115043.314235.6807.709-642.33
591416514441.714469.8-28.0941-276.743
6013375.613306.714673.9-1367.2168.868
6114210.814037.414810.3-772.888173.359
6215017.514688.314966.2-277.939329.235
6317157.816255.115055.31199.77902.694
6415106.215220.915111.2109.61-114.656
6516696.115497.915200.1297.7551198.22
6616035.916138.815288.4850.459-102.934
6715418.915435.515353.881.7588-16.613
6813763.913863.315440.3-1577-99.4243
6915595.216195.115519676.067-599.908
7015183.116372.215564.5807.709-1189.08
7115515.915529.315557.4-28.0941-13.4059
7214142.814166.215533.4-1367.21-23.3779
7315012.714771.915544.8-772.888240.759
7416293.215295.915573.8-277.939997.322
7517771.416780.415580.61199.77991.04
7615582.815738.515628.9109.61-155.714
7716049.915994.915697.1297.75555.0156
7816105.816545.815695.3850.459-439.964
7915623.615774.615692.881.7588-151
8014254.914074.815651.8-1577180.142
8115266.816248.215572.2676.067-981.425
821667116387.415579.7807.709283.591
8315665.415608.315636.4-28.094157.1441
8413949.514276.615643.8-1367.21-327.053
8515146.91491915691.9-772.888227.913
8615172.91545215730-277.939-279.12
8716981.416969.7157701199.7711.6691
8816553.815965.215855.6109.61588.577
8916438.516189.815892297.755248.711
9015895.116792.215941.7850.459-897.084
9116989NANA81.7588NA
9213803.5NANA-1577NA
9316678.3NANA676.067NA
9417315.1NANA807.709NA
9515895.4NANA-28.0941NA
9614912.1NANA-1367.21NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 12374.6 & NA & NA & -772.888 & NA \tabularnewline
2 & 12864.7 & NA & NA & -277.939 & NA \tabularnewline
3 & 14905.8 & NA & NA & 1199.77 & NA \tabularnewline
4 & 12259.7 & NA & NA & 109.61 & NA \tabularnewline
5 & 14088.9 & NA & NA & 297.755 & NA \tabularnewline
6 & 14243.7 & NA & NA & 850.459 & NA \tabularnewline
7 & 12732.8 & 13547.8 & 13466 & 81.7588 & -814.971 \tabularnewline
8 & 11612 & 11981.8 & 13558.8 & -1577 & -369.762 \tabularnewline
9 & 14176.6 & 14299.8 & 13623.7 & 676.067 & -123.154 \tabularnewline
10 & 14452.6 & 14518.4 & 13710.6 & 807.709 & -65.7505 \tabularnewline
11 & 14512.7 & 13755.5 & 13783.6 & -28.0941 & 757.202 \tabularnewline
12 & 12645.1 & 12479.7 & 13846.9 & -1367.21 & 165.443 \tabularnewline
13 & 13820.5 & 13186 & 13958.9 & -772.888 & 634.53 \tabularnewline
14 & 13644.7 & 13801.7 & 14079.6 & -277.939 & -157.003 \tabularnewline
15 & 15684.1 & 15344.9 & 14145.2 & 1199.77 & 339.157 \tabularnewline
16 & 13568.3 & 14333 & 14223.4 & 109.61 & -764.714 \tabularnewline
17 & 14531.1 & 14596.6 & 14298.8 & 297.755 & -65.5011 \tabularnewline
18 & 15320.1 & 15164.8 & 14314.3 & 850.459 & 155.307 \tabularnewline
19 & 14344.2 & 14418.8 & 14337.1 & 81.7588 & -74.6338 \tabularnewline
20 & 12899.4 & 12819.7 & 14396.7 & -1577 & 79.6882 \tabularnewline
21 & 14462 & 15073 & 14397 & 676.067 & -611.046 \tabularnewline
22 & 16044.7 & 15247.3 & 14439.6 & 807.709 & 797.4 \tabularnewline
23 & 14731.2 & 14511.7 & 14539.8 & -28.0941 & 219.532 \tabularnewline
24 & 12798.3 & 13205.7 & 14572.9 & -1367.21 & -407.374 \tabularnewline
25 & 14213.1 & 13863.9 & 14636.8 & -772.888 & 349.167 \tabularnewline
26 & 14683.3 & 14383.6 & 14661.5 & -277.939 & 299.747 \tabularnewline
27 & 14652 & 15889.6 & 14689.9 & 1199.77 & -1237.64 \tabularnewline
28 & 15623.1 & 14799.3 & 14689.6 & 109.61 & 823.84 \tabularnewline
29 & 14880.4 & 14811.8 & 14514 & 297.755 & 68.6114 \tabularnewline
30 & 15765.7 & 15148.7 & 14298.3 & 850.459 & 616.966 \tabularnewline
31 & 15433.1 & 14118.7 & 14036.9 & 81.7588 & 1314.42 \tabularnewline
32 & 12402.6 & 12121.1 & 13698.1 & -1577 & 281.538 \tabularnewline
33 & 15639.8 & 14068.9 & 13392.8 & 676.067 & 1570.94 \tabularnewline
34 & 14861.7 & 13859.4 & 13051.7 & 807.709 & 1002.32 \tabularnewline
35 & 11699.4 & 12636.2 & 12664.3 & -28.0941 & -936.81 \tabularnewline
36 & 10651.9 & 10952.7 & 12319.9 & -1367.21 & -300.803 \tabularnewline
37 & 10086.9 & 11220 & 11992.9 & -772.888 & -1133.1 \tabularnewline
38 & 10676.9 & 11435.7 & 11713.6 & -277.939 & -758.765 \tabularnewline
39 & 11332.1 & 12675 & 11475.2 & 1199.77 & -1342.91 \tabularnewline
40 & 10756.1 & 11354.2 & 11244.6 & 109.61 & -598.089 \tabularnewline
41 & 10450.5 & 11455 & 11157.2 & 297.755 & -1004.5 \tabularnewline
42 & 11930.2 & 12065.4 & 11214.9 & 850.459 & -135.164 \tabularnewline
43 & 11419.9 & 11379.8 & 11298 & 81.7588 & 40.1412 \tabularnewline
44 & 9713.1 & 9811.99 & 11389 & -1577 & -98.891 \tabularnewline
45 & 12608.5 & 12236.9 & 11560.8 & 676.067 & 371.638 \tabularnewline
46 & 12357.2 & 12596.6 & 11788.9 & 807.709 & -239.4 \tabularnewline
47 & 12107.9 & 11968.1 & 11996.2 & -28.0941 & 139.832 \tabularnewline
48 & 11627.2 & 10856.2 & 12223.4 & -1367.21 & 771.047 \tabularnewline
49 & 11105.9 & 11651.8 & 12424.7 & -772.888 & -545.883 \tabularnewline
50 & 11841.6 & 12326.3 & 12604.2 & -277.939 & -484.665 \tabularnewline
51 & 14290.8 & 14008.1 & 12808.3 & 1199.77 & 282.732 \tabularnewline
52 & 13271.7 & 13104.2 & 12994.6 & 109.61 & 167.507 \tabularnewline
53 & 12909.4 & 13463.2 & 13165.5 & 297.755 & -553.809 \tabularnewline
54 & 14924.1 & 14174.5 & 13324 & 850.459 & 749.624 \tabularnewline
55 & 13257.4 & 13608 & 13526.2 & 81.7588 & -350.596 \tabularnewline
56 & 12184.4 & 12210.9 & 13787.9 & -1577 & -26.541 \tabularnewline
57 & 15035.5 & 14715.8 & 14039.7 & 676.067 & 319.708 \tabularnewline
58 & 14401 & 15043.3 & 14235.6 & 807.709 & -642.33 \tabularnewline
59 & 14165 & 14441.7 & 14469.8 & -28.0941 & -276.743 \tabularnewline
60 & 13375.6 & 13306.7 & 14673.9 & -1367.21 & 68.868 \tabularnewline
61 & 14210.8 & 14037.4 & 14810.3 & -772.888 & 173.359 \tabularnewline
62 & 15017.5 & 14688.3 & 14966.2 & -277.939 & 329.235 \tabularnewline
63 & 17157.8 & 16255.1 & 15055.3 & 1199.77 & 902.694 \tabularnewline
64 & 15106.2 & 15220.9 & 15111.2 & 109.61 & -114.656 \tabularnewline
65 & 16696.1 & 15497.9 & 15200.1 & 297.755 & 1198.22 \tabularnewline
66 & 16035.9 & 16138.8 & 15288.4 & 850.459 & -102.934 \tabularnewline
67 & 15418.9 & 15435.5 & 15353.8 & 81.7588 & -16.613 \tabularnewline
68 & 13763.9 & 13863.3 & 15440.3 & -1577 & -99.4243 \tabularnewline
69 & 15595.2 & 16195.1 & 15519 & 676.067 & -599.908 \tabularnewline
70 & 15183.1 & 16372.2 & 15564.5 & 807.709 & -1189.08 \tabularnewline
71 & 15515.9 & 15529.3 & 15557.4 & -28.0941 & -13.4059 \tabularnewline
72 & 14142.8 & 14166.2 & 15533.4 & -1367.21 & -23.3779 \tabularnewline
73 & 15012.7 & 14771.9 & 15544.8 & -772.888 & 240.759 \tabularnewline
74 & 16293.2 & 15295.9 & 15573.8 & -277.939 & 997.322 \tabularnewline
75 & 17771.4 & 16780.4 & 15580.6 & 1199.77 & 991.04 \tabularnewline
76 & 15582.8 & 15738.5 & 15628.9 & 109.61 & -155.714 \tabularnewline
77 & 16049.9 & 15994.9 & 15697.1 & 297.755 & 55.0156 \tabularnewline
78 & 16105.8 & 16545.8 & 15695.3 & 850.459 & -439.964 \tabularnewline
79 & 15623.6 & 15774.6 & 15692.8 & 81.7588 & -151 \tabularnewline
80 & 14254.9 & 14074.8 & 15651.8 & -1577 & 180.142 \tabularnewline
81 & 15266.8 & 16248.2 & 15572.2 & 676.067 & -981.425 \tabularnewline
82 & 16671 & 16387.4 & 15579.7 & 807.709 & 283.591 \tabularnewline
83 & 15665.4 & 15608.3 & 15636.4 & -28.0941 & 57.1441 \tabularnewline
84 & 13949.5 & 14276.6 & 15643.8 & -1367.21 & -327.053 \tabularnewline
85 & 15146.9 & 14919 & 15691.9 & -772.888 & 227.913 \tabularnewline
86 & 15172.9 & 15452 & 15730 & -277.939 & -279.12 \tabularnewline
87 & 16981.4 & 16969.7 & 15770 & 1199.77 & 11.6691 \tabularnewline
88 & 16553.8 & 15965.2 & 15855.6 & 109.61 & 588.577 \tabularnewline
89 & 16438.5 & 16189.8 & 15892 & 297.755 & 248.711 \tabularnewline
90 & 15895.1 & 16792.2 & 15941.7 & 850.459 & -897.084 \tabularnewline
91 & 16989 & NA & NA & 81.7588 & NA \tabularnewline
92 & 13803.5 & NA & NA & -1577 & NA \tabularnewline
93 & 16678.3 & NA & NA & 676.067 & NA \tabularnewline
94 & 17315.1 & NA & NA & 807.709 & NA \tabularnewline
95 & 15895.4 & NA & NA & -28.0941 & NA \tabularnewline
96 & 14912.1 & NA & NA & -1367.21 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278664&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]12374.6[/C][C]NA[/C][C]NA[/C][C]-772.888[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]12864.7[/C][C]NA[/C][C]NA[/C][C]-277.939[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]14905.8[/C][C]NA[/C][C]NA[/C][C]1199.77[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]12259.7[/C][C]NA[/C][C]NA[/C][C]109.61[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]14088.9[/C][C]NA[/C][C]NA[/C][C]297.755[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]14243.7[/C][C]NA[/C][C]NA[/C][C]850.459[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]12732.8[/C][C]13547.8[/C][C]13466[/C][C]81.7588[/C][C]-814.971[/C][/ROW]
[ROW][C]8[/C][C]11612[/C][C]11981.8[/C][C]13558.8[/C][C]-1577[/C][C]-369.762[/C][/ROW]
[ROW][C]9[/C][C]14176.6[/C][C]14299.8[/C][C]13623.7[/C][C]676.067[/C][C]-123.154[/C][/ROW]
[ROW][C]10[/C][C]14452.6[/C][C]14518.4[/C][C]13710.6[/C][C]807.709[/C][C]-65.7505[/C][/ROW]
[ROW][C]11[/C][C]14512.7[/C][C]13755.5[/C][C]13783.6[/C][C]-28.0941[/C][C]757.202[/C][/ROW]
[ROW][C]12[/C][C]12645.1[/C][C]12479.7[/C][C]13846.9[/C][C]-1367.21[/C][C]165.443[/C][/ROW]
[ROW][C]13[/C][C]13820.5[/C][C]13186[/C][C]13958.9[/C][C]-772.888[/C][C]634.53[/C][/ROW]
[ROW][C]14[/C][C]13644.7[/C][C]13801.7[/C][C]14079.6[/C][C]-277.939[/C][C]-157.003[/C][/ROW]
[ROW][C]15[/C][C]15684.1[/C][C]15344.9[/C][C]14145.2[/C][C]1199.77[/C][C]339.157[/C][/ROW]
[ROW][C]16[/C][C]13568.3[/C][C]14333[/C][C]14223.4[/C][C]109.61[/C][C]-764.714[/C][/ROW]
[ROW][C]17[/C][C]14531.1[/C][C]14596.6[/C][C]14298.8[/C][C]297.755[/C][C]-65.5011[/C][/ROW]
[ROW][C]18[/C][C]15320.1[/C][C]15164.8[/C][C]14314.3[/C][C]850.459[/C][C]155.307[/C][/ROW]
[ROW][C]19[/C][C]14344.2[/C][C]14418.8[/C][C]14337.1[/C][C]81.7588[/C][C]-74.6338[/C][/ROW]
[ROW][C]20[/C][C]12899.4[/C][C]12819.7[/C][C]14396.7[/C][C]-1577[/C][C]79.6882[/C][/ROW]
[ROW][C]21[/C][C]14462[/C][C]15073[/C][C]14397[/C][C]676.067[/C][C]-611.046[/C][/ROW]
[ROW][C]22[/C][C]16044.7[/C][C]15247.3[/C][C]14439.6[/C][C]807.709[/C][C]797.4[/C][/ROW]
[ROW][C]23[/C][C]14731.2[/C][C]14511.7[/C][C]14539.8[/C][C]-28.0941[/C][C]219.532[/C][/ROW]
[ROW][C]24[/C][C]12798.3[/C][C]13205.7[/C][C]14572.9[/C][C]-1367.21[/C][C]-407.374[/C][/ROW]
[ROW][C]25[/C][C]14213.1[/C][C]13863.9[/C][C]14636.8[/C][C]-772.888[/C][C]349.167[/C][/ROW]
[ROW][C]26[/C][C]14683.3[/C][C]14383.6[/C][C]14661.5[/C][C]-277.939[/C][C]299.747[/C][/ROW]
[ROW][C]27[/C][C]14652[/C][C]15889.6[/C][C]14689.9[/C][C]1199.77[/C][C]-1237.64[/C][/ROW]
[ROW][C]28[/C][C]15623.1[/C][C]14799.3[/C][C]14689.6[/C][C]109.61[/C][C]823.84[/C][/ROW]
[ROW][C]29[/C][C]14880.4[/C][C]14811.8[/C][C]14514[/C][C]297.755[/C][C]68.6114[/C][/ROW]
[ROW][C]30[/C][C]15765.7[/C][C]15148.7[/C][C]14298.3[/C][C]850.459[/C][C]616.966[/C][/ROW]
[ROW][C]31[/C][C]15433.1[/C][C]14118.7[/C][C]14036.9[/C][C]81.7588[/C][C]1314.42[/C][/ROW]
[ROW][C]32[/C][C]12402.6[/C][C]12121.1[/C][C]13698.1[/C][C]-1577[/C][C]281.538[/C][/ROW]
[ROW][C]33[/C][C]15639.8[/C][C]14068.9[/C][C]13392.8[/C][C]676.067[/C][C]1570.94[/C][/ROW]
[ROW][C]34[/C][C]14861.7[/C][C]13859.4[/C][C]13051.7[/C][C]807.709[/C][C]1002.32[/C][/ROW]
[ROW][C]35[/C][C]11699.4[/C][C]12636.2[/C][C]12664.3[/C][C]-28.0941[/C][C]-936.81[/C][/ROW]
[ROW][C]36[/C][C]10651.9[/C][C]10952.7[/C][C]12319.9[/C][C]-1367.21[/C][C]-300.803[/C][/ROW]
[ROW][C]37[/C][C]10086.9[/C][C]11220[/C][C]11992.9[/C][C]-772.888[/C][C]-1133.1[/C][/ROW]
[ROW][C]38[/C][C]10676.9[/C][C]11435.7[/C][C]11713.6[/C][C]-277.939[/C][C]-758.765[/C][/ROW]
[ROW][C]39[/C][C]11332.1[/C][C]12675[/C][C]11475.2[/C][C]1199.77[/C][C]-1342.91[/C][/ROW]
[ROW][C]40[/C][C]10756.1[/C][C]11354.2[/C][C]11244.6[/C][C]109.61[/C][C]-598.089[/C][/ROW]
[ROW][C]41[/C][C]10450.5[/C][C]11455[/C][C]11157.2[/C][C]297.755[/C][C]-1004.5[/C][/ROW]
[ROW][C]42[/C][C]11930.2[/C][C]12065.4[/C][C]11214.9[/C][C]850.459[/C][C]-135.164[/C][/ROW]
[ROW][C]43[/C][C]11419.9[/C][C]11379.8[/C][C]11298[/C][C]81.7588[/C][C]40.1412[/C][/ROW]
[ROW][C]44[/C][C]9713.1[/C][C]9811.99[/C][C]11389[/C][C]-1577[/C][C]-98.891[/C][/ROW]
[ROW][C]45[/C][C]12608.5[/C][C]12236.9[/C][C]11560.8[/C][C]676.067[/C][C]371.638[/C][/ROW]
[ROW][C]46[/C][C]12357.2[/C][C]12596.6[/C][C]11788.9[/C][C]807.709[/C][C]-239.4[/C][/ROW]
[ROW][C]47[/C][C]12107.9[/C][C]11968.1[/C][C]11996.2[/C][C]-28.0941[/C][C]139.832[/C][/ROW]
[ROW][C]48[/C][C]11627.2[/C][C]10856.2[/C][C]12223.4[/C][C]-1367.21[/C][C]771.047[/C][/ROW]
[ROW][C]49[/C][C]11105.9[/C][C]11651.8[/C][C]12424.7[/C][C]-772.888[/C][C]-545.883[/C][/ROW]
[ROW][C]50[/C][C]11841.6[/C][C]12326.3[/C][C]12604.2[/C][C]-277.939[/C][C]-484.665[/C][/ROW]
[ROW][C]51[/C][C]14290.8[/C][C]14008.1[/C][C]12808.3[/C][C]1199.77[/C][C]282.732[/C][/ROW]
[ROW][C]52[/C][C]13271.7[/C][C]13104.2[/C][C]12994.6[/C][C]109.61[/C][C]167.507[/C][/ROW]
[ROW][C]53[/C][C]12909.4[/C][C]13463.2[/C][C]13165.5[/C][C]297.755[/C][C]-553.809[/C][/ROW]
[ROW][C]54[/C][C]14924.1[/C][C]14174.5[/C][C]13324[/C][C]850.459[/C][C]749.624[/C][/ROW]
[ROW][C]55[/C][C]13257.4[/C][C]13608[/C][C]13526.2[/C][C]81.7588[/C][C]-350.596[/C][/ROW]
[ROW][C]56[/C][C]12184.4[/C][C]12210.9[/C][C]13787.9[/C][C]-1577[/C][C]-26.541[/C][/ROW]
[ROW][C]57[/C][C]15035.5[/C][C]14715.8[/C][C]14039.7[/C][C]676.067[/C][C]319.708[/C][/ROW]
[ROW][C]58[/C][C]14401[/C][C]15043.3[/C][C]14235.6[/C][C]807.709[/C][C]-642.33[/C][/ROW]
[ROW][C]59[/C][C]14165[/C][C]14441.7[/C][C]14469.8[/C][C]-28.0941[/C][C]-276.743[/C][/ROW]
[ROW][C]60[/C][C]13375.6[/C][C]13306.7[/C][C]14673.9[/C][C]-1367.21[/C][C]68.868[/C][/ROW]
[ROW][C]61[/C][C]14210.8[/C][C]14037.4[/C][C]14810.3[/C][C]-772.888[/C][C]173.359[/C][/ROW]
[ROW][C]62[/C][C]15017.5[/C][C]14688.3[/C][C]14966.2[/C][C]-277.939[/C][C]329.235[/C][/ROW]
[ROW][C]63[/C][C]17157.8[/C][C]16255.1[/C][C]15055.3[/C][C]1199.77[/C][C]902.694[/C][/ROW]
[ROW][C]64[/C][C]15106.2[/C][C]15220.9[/C][C]15111.2[/C][C]109.61[/C][C]-114.656[/C][/ROW]
[ROW][C]65[/C][C]16696.1[/C][C]15497.9[/C][C]15200.1[/C][C]297.755[/C][C]1198.22[/C][/ROW]
[ROW][C]66[/C][C]16035.9[/C][C]16138.8[/C][C]15288.4[/C][C]850.459[/C][C]-102.934[/C][/ROW]
[ROW][C]67[/C][C]15418.9[/C][C]15435.5[/C][C]15353.8[/C][C]81.7588[/C][C]-16.613[/C][/ROW]
[ROW][C]68[/C][C]13763.9[/C][C]13863.3[/C][C]15440.3[/C][C]-1577[/C][C]-99.4243[/C][/ROW]
[ROW][C]69[/C][C]15595.2[/C][C]16195.1[/C][C]15519[/C][C]676.067[/C][C]-599.908[/C][/ROW]
[ROW][C]70[/C][C]15183.1[/C][C]16372.2[/C][C]15564.5[/C][C]807.709[/C][C]-1189.08[/C][/ROW]
[ROW][C]71[/C][C]15515.9[/C][C]15529.3[/C][C]15557.4[/C][C]-28.0941[/C][C]-13.4059[/C][/ROW]
[ROW][C]72[/C][C]14142.8[/C][C]14166.2[/C][C]15533.4[/C][C]-1367.21[/C][C]-23.3779[/C][/ROW]
[ROW][C]73[/C][C]15012.7[/C][C]14771.9[/C][C]15544.8[/C][C]-772.888[/C][C]240.759[/C][/ROW]
[ROW][C]74[/C][C]16293.2[/C][C]15295.9[/C][C]15573.8[/C][C]-277.939[/C][C]997.322[/C][/ROW]
[ROW][C]75[/C][C]17771.4[/C][C]16780.4[/C][C]15580.6[/C][C]1199.77[/C][C]991.04[/C][/ROW]
[ROW][C]76[/C][C]15582.8[/C][C]15738.5[/C][C]15628.9[/C][C]109.61[/C][C]-155.714[/C][/ROW]
[ROW][C]77[/C][C]16049.9[/C][C]15994.9[/C][C]15697.1[/C][C]297.755[/C][C]55.0156[/C][/ROW]
[ROW][C]78[/C][C]16105.8[/C][C]16545.8[/C][C]15695.3[/C][C]850.459[/C][C]-439.964[/C][/ROW]
[ROW][C]79[/C][C]15623.6[/C][C]15774.6[/C][C]15692.8[/C][C]81.7588[/C][C]-151[/C][/ROW]
[ROW][C]80[/C][C]14254.9[/C][C]14074.8[/C][C]15651.8[/C][C]-1577[/C][C]180.142[/C][/ROW]
[ROW][C]81[/C][C]15266.8[/C][C]16248.2[/C][C]15572.2[/C][C]676.067[/C][C]-981.425[/C][/ROW]
[ROW][C]82[/C][C]16671[/C][C]16387.4[/C][C]15579.7[/C][C]807.709[/C][C]283.591[/C][/ROW]
[ROW][C]83[/C][C]15665.4[/C][C]15608.3[/C][C]15636.4[/C][C]-28.0941[/C][C]57.1441[/C][/ROW]
[ROW][C]84[/C][C]13949.5[/C][C]14276.6[/C][C]15643.8[/C][C]-1367.21[/C][C]-327.053[/C][/ROW]
[ROW][C]85[/C][C]15146.9[/C][C]14919[/C][C]15691.9[/C][C]-772.888[/C][C]227.913[/C][/ROW]
[ROW][C]86[/C][C]15172.9[/C][C]15452[/C][C]15730[/C][C]-277.939[/C][C]-279.12[/C][/ROW]
[ROW][C]87[/C][C]16981.4[/C][C]16969.7[/C][C]15770[/C][C]1199.77[/C][C]11.6691[/C][/ROW]
[ROW][C]88[/C][C]16553.8[/C][C]15965.2[/C][C]15855.6[/C][C]109.61[/C][C]588.577[/C][/ROW]
[ROW][C]89[/C][C]16438.5[/C][C]16189.8[/C][C]15892[/C][C]297.755[/C][C]248.711[/C][/ROW]
[ROW][C]90[/C][C]15895.1[/C][C]16792.2[/C][C]15941.7[/C][C]850.459[/C][C]-897.084[/C][/ROW]
[ROW][C]91[/C][C]16989[/C][C]NA[/C][C]NA[/C][C]81.7588[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]13803.5[/C][C]NA[/C][C]NA[/C][C]-1577[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]16678.3[/C][C]NA[/C][C]NA[/C][C]676.067[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]17315.1[/C][C]NA[/C][C]NA[/C][C]807.709[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]15895.4[/C][C]NA[/C][C]NA[/C][C]-28.0941[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]14912.1[/C][C]NA[/C][C]NA[/C][C]-1367.21[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278664&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278664&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
112374.6NANA-772.888NA
212864.7NANA-277.939NA
314905.8NANA1199.77NA
412259.7NANA109.61NA
514088.9NANA297.755NA
614243.7NANA850.459NA
712732.813547.81346681.7588-814.971
81161211981.813558.8-1577-369.762
914176.614299.813623.7676.067-123.154
1014452.614518.413710.6807.709-65.7505
1114512.713755.513783.6-28.0941757.202
1212645.112479.713846.9-1367.21165.443
1313820.51318613958.9-772.888634.53
1413644.713801.714079.6-277.939-157.003
1515684.115344.914145.21199.77339.157
1613568.31433314223.4109.61-764.714
1714531.114596.614298.8297.755-65.5011
1815320.115164.814314.3850.459155.307
1914344.214418.814337.181.7588-74.6338
2012899.412819.714396.7-157779.6882
21144621507314397676.067-611.046
2216044.715247.314439.6807.709797.4
2314731.214511.714539.8-28.0941219.532
2412798.313205.714572.9-1367.21-407.374
2514213.113863.914636.8-772.888349.167
2614683.314383.614661.5-277.939299.747
271465215889.614689.91199.77-1237.64
2815623.114799.314689.6109.61823.84
2914880.414811.814514297.75568.6114
3015765.715148.714298.3850.459616.966
3115433.114118.714036.981.75881314.42
3212402.612121.113698.1-1577281.538
3315639.814068.913392.8676.0671570.94
3414861.713859.413051.7807.7091002.32
3511699.412636.212664.3-28.0941-936.81
3610651.910952.712319.9-1367.21-300.803
3710086.91122011992.9-772.888-1133.1
3810676.911435.711713.6-277.939-758.765
3911332.11267511475.21199.77-1342.91
4010756.111354.211244.6109.61-598.089
4110450.51145511157.2297.755-1004.5
4211930.212065.411214.9850.459-135.164
4311419.911379.81129881.758840.1412
449713.19811.9911389-1577-98.891
4512608.512236.911560.8676.067371.638
4612357.212596.611788.9807.709-239.4
4712107.911968.111996.2-28.0941139.832
4811627.210856.212223.4-1367.21771.047
4911105.911651.812424.7-772.888-545.883
5011841.612326.312604.2-277.939-484.665
5114290.814008.112808.31199.77282.732
5213271.713104.212994.6109.61167.507
5312909.413463.213165.5297.755-553.809
5414924.114174.513324850.459749.624
5513257.41360813526.281.7588-350.596
5612184.412210.913787.9-1577-26.541
5715035.514715.814039.7676.067319.708
581440115043.314235.6807.709-642.33
591416514441.714469.8-28.0941-276.743
6013375.613306.714673.9-1367.2168.868
6114210.814037.414810.3-772.888173.359
6215017.514688.314966.2-277.939329.235
6317157.816255.115055.31199.77902.694
6415106.215220.915111.2109.61-114.656
6516696.115497.915200.1297.7551198.22
6616035.916138.815288.4850.459-102.934
6715418.915435.515353.881.7588-16.613
6813763.913863.315440.3-1577-99.4243
6915595.216195.115519676.067-599.908
7015183.116372.215564.5807.709-1189.08
7115515.915529.315557.4-28.0941-13.4059
7214142.814166.215533.4-1367.21-23.3779
7315012.714771.915544.8-772.888240.759
7416293.215295.915573.8-277.939997.322
7517771.416780.415580.61199.77991.04
7615582.815738.515628.9109.61-155.714
7716049.915994.915697.1297.75555.0156
7816105.816545.815695.3850.459-439.964
7915623.615774.615692.881.7588-151
8014254.914074.815651.8-1577180.142
8115266.816248.215572.2676.067-981.425
821667116387.415579.7807.709283.591
8315665.415608.315636.4-28.094157.1441
8413949.514276.615643.8-1367.21-327.053
8515146.91491915691.9-772.888227.913
8615172.91545215730-277.939-279.12
8716981.416969.7157701199.7711.6691
8816553.815965.215855.6109.61588.577
8916438.516189.815892297.755248.711
9015895.116792.215941.7850.459-897.084
9116989NANA81.7588NA
9213803.5NANA-1577NA
9316678.3NANA676.067NA
9417315.1NANA807.709NA
9515895.4NANA-28.0941NA
9614912.1NANA-1367.21NA


Figures (Output of Computation)

Input Parameters & R Code

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')