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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 computationWed, 04 Dec 2013 03:58:19 -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/04/t1386147574sv0pdtdualh5x5t.htm/, Retrieved Fri, 19 Apr 2024 16:10:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230441, Retrieved Fri, 19 Apr 2024 16:10:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-04 08:58:19] [6bddb01df32adf96be73fb2a4c89eedb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16,3
16,37
16,38
16,37
16,42
16,43
16,44
16,53
16,55
16,56
16,6
16,61
16,62
16,64
16,61
16,74
16,87
16,89
16,89
16,99
17,06
17,1
17,11
17,17
17,17
17,21
17,37
17,43
17,44
17,46
17,42
17,47
17,45
17,44
17,46
17,47
17,47
17,56
17,61
17,61
17,6
17,57
17,59
17,59
17,68
17,73
17,75
17,75
17,75
17,85
18,06
18,05
18,16
18,2
18,21
18,33
18,36
18,37
18,4
18,47
18,49
18,5
18,53
18,56
18,6
18,61
18,62
18,61
18,65
18,77
18,78
18,78
18,8
18,85
18,85
18,98
19,06
19,08
19,19
19,21
19,29
19,3
19,36
19,36

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230441&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230441&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230441&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 time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
116.3NANA-0.0442303NA
216.37NANA-0.030272NA
316.38NANA0.00208912NA
416.37NANA0.0207002NA
516.42NANA0.0425058NA
616.43NANA0.0175752NA
716.4416.45916.4767-0.0176331-0.0190336
816.5316.507416.50120.00611690.0226331
916.5516.532216.52210.01007520.0178414
1016.5616.558516.54710.01146410.00145255
1116.616.577916.5812-0.003327550.0220775
1216.6116.604116.6192-0.01506370.00589699
1316.6216.612916.6571-0.04423030.00714699
1416.6416.664716.695-0.030272-0.024728
1516.6116.737516.73540.00208912-0.127506
1616.7416.799916.77920.0207002-0.0598669
1716.8716.865416.82290.04250580.00457755
1816.8916.885116.86750.01757520.00492477
1916.8916.896116.9138-0.0176331-0.0061169
2016.9916.966516.96040.00611690.0234664
2117.0617.025917.01580.01007520.0340914
2217.117.087717.07630.01146410.0122859
2317.1117.125417.1288-0.00332755-0.0154225
2417.1717.161217.1762-0.01506370.00881366
2517.1717.177917.2221-0.0442303-0.00785301
2617.2117.233917.2642-0.030272-0.0238947
2717.3717.302517.30040.002089120.0674942
2817.4317.351517.33080.02070020.0784664
2917.4417.402117.35960.04250580.0379109
3017.4617.404217.38670.01757520.0557581
3117.4217.39417.4117-0.01763310.0259664
3217.4717.444917.43880.00611690.0251331
3317.4517.473417.46330.0100752-0.0234086
3417.4417.492317.48080.0114641-0.0522975
3517.4617.491717.495-0.00332755-0.0316725
3617.4717.491217.5062-0.0150637-0.0211863
3717.4717.473717.5179-0.0442303-0.00368634
3817.5617.499717.53-0.0302720.060272
3917.6117.546717.54460.002089120.0633275
4017.6117.58717.56620.02070020.0230498
4117.617.632917.59040.0425058-0.0329225
4217.5717.631717.61420.0175752-0.0617419
4317.5917.619917.6375-0.0176331-0.0298669
4417.5917.667417.66120.0061169-0.0773669
4517.6817.702217.69210.0100752-0.0221586
4617.7317.740617.72920.0114641-0.0106308
4717.7517.767517.7708-0.00332755-0.0175058
4817.7517.805417.8204-0.0150637-0.055353
4917.7517.828317.8725-0.0442303-0.0782697
5017.8517.898917.9292-0.030272-0.0488947
5118.0617.990417.98830.002089120.0695775
5218.0518.06418.04330.0207002-0.0140336
5318.1618.139618.09710.04250580.0204109
5418.218.171718.15420.01757520.0282581
5518.2118.197418.215-0.01763310.0126331
5618.3318.27918.27290.00611690.0509664
5718.3618.329718.31960.01007520.0303414
5818.3718.371918.36040.0114641-0.00188079
5918.418.396718.4-0.003327550.00332755
6018.4718.420418.4354-0.01506370.049647
6118.4918.425418.4696-0.04423030.064647
6218.518.468118.4983-0.0302720.0319387
6318.5318.524218.52210.002089120.00582755
6418.5618.571518.55080.0207002-0.0115336
6518.618.625818.58330.0425058-0.0258391
6618.6118.629718.61210.0175752-0.0196586
6718.6218.620318.6379-0.0176331-0.000283565
6818.6118.671518.66540.0061169-0.0615336
6918.6518.703418.69330.0100752-0.0534086
7018.7718.735618.72420.01146410.0343692
7118.7818.757518.7608-0.003327550.0224942
7218.7818.784518.7996-0.0150637-0.00451968
7318.818.798718.8429-0.04423030.00131366
7418.8518.861418.8917-0.030272-0.0113947
7518.8518.945418.94330.00208912-0.0954225
7618.9819.012818.99210.0207002-0.0327836
7719.0619.080819.03830.0425058-0.0208391
7819.0819.104219.08670.0175752-0.0242419
7919.19NANA-0.0176331NA
8019.21NANA0.0061169NA
8119.29NANA0.0100752NA
8219.3NANA0.0114641NA
8319.36NANA-0.00332755NA
8419.36NANA-0.0150637NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 16.3 & NA & NA & -0.0442303 & NA \tabularnewline
2 & 16.37 & NA & NA & -0.030272 & NA \tabularnewline
3 & 16.38 & NA & NA & 0.00208912 & NA \tabularnewline
4 & 16.37 & NA & NA & 0.0207002 & NA \tabularnewline
5 & 16.42 & NA & NA & 0.0425058 & NA \tabularnewline
6 & 16.43 & NA & NA & 0.0175752 & NA \tabularnewline
7 & 16.44 & 16.459 & 16.4767 & -0.0176331 & -0.0190336 \tabularnewline
8 & 16.53 & 16.5074 & 16.5012 & 0.0061169 & 0.0226331 \tabularnewline
9 & 16.55 & 16.5322 & 16.5221 & 0.0100752 & 0.0178414 \tabularnewline
10 & 16.56 & 16.5585 & 16.5471 & 0.0114641 & 0.00145255 \tabularnewline
11 & 16.6 & 16.5779 & 16.5812 & -0.00332755 & 0.0220775 \tabularnewline
12 & 16.61 & 16.6041 & 16.6192 & -0.0150637 & 0.00589699 \tabularnewline
13 & 16.62 & 16.6129 & 16.6571 & -0.0442303 & 0.00714699 \tabularnewline
14 & 16.64 & 16.6647 & 16.695 & -0.030272 & -0.024728 \tabularnewline
15 & 16.61 & 16.7375 & 16.7354 & 0.00208912 & -0.127506 \tabularnewline
16 & 16.74 & 16.7999 & 16.7792 & 0.0207002 & -0.0598669 \tabularnewline
17 & 16.87 & 16.8654 & 16.8229 & 0.0425058 & 0.00457755 \tabularnewline
18 & 16.89 & 16.8851 & 16.8675 & 0.0175752 & 0.00492477 \tabularnewline
19 & 16.89 & 16.8961 & 16.9138 & -0.0176331 & -0.0061169 \tabularnewline
20 & 16.99 & 16.9665 & 16.9604 & 0.0061169 & 0.0234664 \tabularnewline
21 & 17.06 & 17.0259 & 17.0158 & 0.0100752 & 0.0340914 \tabularnewline
22 & 17.1 & 17.0877 & 17.0763 & 0.0114641 & 0.0122859 \tabularnewline
23 & 17.11 & 17.1254 & 17.1288 & -0.00332755 & -0.0154225 \tabularnewline
24 & 17.17 & 17.1612 & 17.1762 & -0.0150637 & 0.00881366 \tabularnewline
25 & 17.17 & 17.1779 & 17.2221 & -0.0442303 & -0.00785301 \tabularnewline
26 & 17.21 & 17.2339 & 17.2642 & -0.030272 & -0.0238947 \tabularnewline
27 & 17.37 & 17.3025 & 17.3004 & 0.00208912 & 0.0674942 \tabularnewline
28 & 17.43 & 17.3515 & 17.3308 & 0.0207002 & 0.0784664 \tabularnewline
29 & 17.44 & 17.4021 & 17.3596 & 0.0425058 & 0.0379109 \tabularnewline
30 & 17.46 & 17.4042 & 17.3867 & 0.0175752 & 0.0557581 \tabularnewline
31 & 17.42 & 17.394 & 17.4117 & -0.0176331 & 0.0259664 \tabularnewline
32 & 17.47 & 17.4449 & 17.4388 & 0.0061169 & 0.0251331 \tabularnewline
33 & 17.45 & 17.4734 & 17.4633 & 0.0100752 & -0.0234086 \tabularnewline
34 & 17.44 & 17.4923 & 17.4808 & 0.0114641 & -0.0522975 \tabularnewline
35 & 17.46 & 17.4917 & 17.495 & -0.00332755 & -0.0316725 \tabularnewline
36 & 17.47 & 17.4912 & 17.5062 & -0.0150637 & -0.0211863 \tabularnewline
37 & 17.47 & 17.4737 & 17.5179 & -0.0442303 & -0.00368634 \tabularnewline
38 & 17.56 & 17.4997 & 17.53 & -0.030272 & 0.060272 \tabularnewline
39 & 17.61 & 17.5467 & 17.5446 & 0.00208912 & 0.0633275 \tabularnewline
40 & 17.61 & 17.587 & 17.5662 & 0.0207002 & 0.0230498 \tabularnewline
41 & 17.6 & 17.6329 & 17.5904 & 0.0425058 & -0.0329225 \tabularnewline
42 & 17.57 & 17.6317 & 17.6142 & 0.0175752 & -0.0617419 \tabularnewline
43 & 17.59 & 17.6199 & 17.6375 & -0.0176331 & -0.0298669 \tabularnewline
44 & 17.59 & 17.6674 & 17.6612 & 0.0061169 & -0.0773669 \tabularnewline
45 & 17.68 & 17.7022 & 17.6921 & 0.0100752 & -0.0221586 \tabularnewline
46 & 17.73 & 17.7406 & 17.7292 & 0.0114641 & -0.0106308 \tabularnewline
47 & 17.75 & 17.7675 & 17.7708 & -0.00332755 & -0.0175058 \tabularnewline
48 & 17.75 & 17.8054 & 17.8204 & -0.0150637 & -0.055353 \tabularnewline
49 & 17.75 & 17.8283 & 17.8725 & -0.0442303 & -0.0782697 \tabularnewline
50 & 17.85 & 17.8989 & 17.9292 & -0.030272 & -0.0488947 \tabularnewline
51 & 18.06 & 17.9904 & 17.9883 & 0.00208912 & 0.0695775 \tabularnewline
52 & 18.05 & 18.064 & 18.0433 & 0.0207002 & -0.0140336 \tabularnewline
53 & 18.16 & 18.1396 & 18.0971 & 0.0425058 & 0.0204109 \tabularnewline
54 & 18.2 & 18.1717 & 18.1542 & 0.0175752 & 0.0282581 \tabularnewline
55 & 18.21 & 18.1974 & 18.215 & -0.0176331 & 0.0126331 \tabularnewline
56 & 18.33 & 18.279 & 18.2729 & 0.0061169 & 0.0509664 \tabularnewline
57 & 18.36 & 18.3297 & 18.3196 & 0.0100752 & 0.0303414 \tabularnewline
58 & 18.37 & 18.3719 & 18.3604 & 0.0114641 & -0.00188079 \tabularnewline
59 & 18.4 & 18.3967 & 18.4 & -0.00332755 & 0.00332755 \tabularnewline
60 & 18.47 & 18.4204 & 18.4354 & -0.0150637 & 0.049647 \tabularnewline
61 & 18.49 & 18.4254 & 18.4696 & -0.0442303 & 0.064647 \tabularnewline
62 & 18.5 & 18.4681 & 18.4983 & -0.030272 & 0.0319387 \tabularnewline
63 & 18.53 & 18.5242 & 18.5221 & 0.00208912 & 0.00582755 \tabularnewline
64 & 18.56 & 18.5715 & 18.5508 & 0.0207002 & -0.0115336 \tabularnewline
65 & 18.6 & 18.6258 & 18.5833 & 0.0425058 & -0.0258391 \tabularnewline
66 & 18.61 & 18.6297 & 18.6121 & 0.0175752 & -0.0196586 \tabularnewline
67 & 18.62 & 18.6203 & 18.6379 & -0.0176331 & -0.000283565 \tabularnewline
68 & 18.61 & 18.6715 & 18.6654 & 0.0061169 & -0.0615336 \tabularnewline
69 & 18.65 & 18.7034 & 18.6933 & 0.0100752 & -0.0534086 \tabularnewline
70 & 18.77 & 18.7356 & 18.7242 & 0.0114641 & 0.0343692 \tabularnewline
71 & 18.78 & 18.7575 & 18.7608 & -0.00332755 & 0.0224942 \tabularnewline
72 & 18.78 & 18.7845 & 18.7996 & -0.0150637 & -0.00451968 \tabularnewline
73 & 18.8 & 18.7987 & 18.8429 & -0.0442303 & 0.00131366 \tabularnewline
74 & 18.85 & 18.8614 & 18.8917 & -0.030272 & -0.0113947 \tabularnewline
75 & 18.85 & 18.9454 & 18.9433 & 0.00208912 & -0.0954225 \tabularnewline
76 & 18.98 & 19.0128 & 18.9921 & 0.0207002 & -0.0327836 \tabularnewline
77 & 19.06 & 19.0808 & 19.0383 & 0.0425058 & -0.0208391 \tabularnewline
78 & 19.08 & 19.1042 & 19.0867 & 0.0175752 & -0.0242419 \tabularnewline
79 & 19.19 & NA & NA & -0.0176331 & NA \tabularnewline
80 & 19.21 & NA & NA & 0.0061169 & NA \tabularnewline
81 & 19.29 & NA & NA & 0.0100752 & NA \tabularnewline
82 & 19.3 & NA & NA & 0.0114641 & NA \tabularnewline
83 & 19.36 & NA & NA & -0.00332755 & NA \tabularnewline
84 & 19.36 & NA & NA & -0.0150637 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230441&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]16.3[/C][C]NA[/C][C]NA[/C][C]-0.0442303[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]16.37[/C][C]NA[/C][C]NA[/C][C]-0.030272[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]16.38[/C][C]NA[/C][C]NA[/C][C]0.00208912[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]16.37[/C][C]NA[/C][C]NA[/C][C]0.0207002[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]16.42[/C][C]NA[/C][C]NA[/C][C]0.0425058[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]16.43[/C][C]NA[/C][C]NA[/C][C]0.0175752[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]16.44[/C][C]16.459[/C][C]16.4767[/C][C]-0.0176331[/C][C]-0.0190336[/C][/ROW]
[ROW][C]8[/C][C]16.53[/C][C]16.5074[/C][C]16.5012[/C][C]0.0061169[/C][C]0.0226331[/C][/ROW]
[ROW][C]9[/C][C]16.55[/C][C]16.5322[/C][C]16.5221[/C][C]0.0100752[/C][C]0.0178414[/C][/ROW]
[ROW][C]10[/C][C]16.56[/C][C]16.5585[/C][C]16.5471[/C][C]0.0114641[/C][C]0.00145255[/C][/ROW]
[ROW][C]11[/C][C]16.6[/C][C]16.5779[/C][C]16.5812[/C][C]-0.00332755[/C][C]0.0220775[/C][/ROW]
[ROW][C]12[/C][C]16.61[/C][C]16.6041[/C][C]16.6192[/C][C]-0.0150637[/C][C]0.00589699[/C][/ROW]
[ROW][C]13[/C][C]16.62[/C][C]16.6129[/C][C]16.6571[/C][C]-0.0442303[/C][C]0.00714699[/C][/ROW]
[ROW][C]14[/C][C]16.64[/C][C]16.6647[/C][C]16.695[/C][C]-0.030272[/C][C]-0.024728[/C][/ROW]
[ROW][C]15[/C][C]16.61[/C][C]16.7375[/C][C]16.7354[/C][C]0.00208912[/C][C]-0.127506[/C][/ROW]
[ROW][C]16[/C][C]16.74[/C][C]16.7999[/C][C]16.7792[/C][C]0.0207002[/C][C]-0.0598669[/C][/ROW]
[ROW][C]17[/C][C]16.87[/C][C]16.8654[/C][C]16.8229[/C][C]0.0425058[/C][C]0.00457755[/C][/ROW]
[ROW][C]18[/C][C]16.89[/C][C]16.8851[/C][C]16.8675[/C][C]0.0175752[/C][C]0.00492477[/C][/ROW]
[ROW][C]19[/C][C]16.89[/C][C]16.8961[/C][C]16.9138[/C][C]-0.0176331[/C][C]-0.0061169[/C][/ROW]
[ROW][C]20[/C][C]16.99[/C][C]16.9665[/C][C]16.9604[/C][C]0.0061169[/C][C]0.0234664[/C][/ROW]
[ROW][C]21[/C][C]17.06[/C][C]17.0259[/C][C]17.0158[/C][C]0.0100752[/C][C]0.0340914[/C][/ROW]
[ROW][C]22[/C][C]17.1[/C][C]17.0877[/C][C]17.0763[/C][C]0.0114641[/C][C]0.0122859[/C][/ROW]
[ROW][C]23[/C][C]17.11[/C][C]17.1254[/C][C]17.1288[/C][C]-0.00332755[/C][C]-0.0154225[/C][/ROW]
[ROW][C]24[/C][C]17.17[/C][C]17.1612[/C][C]17.1762[/C][C]-0.0150637[/C][C]0.00881366[/C][/ROW]
[ROW][C]25[/C][C]17.17[/C][C]17.1779[/C][C]17.2221[/C][C]-0.0442303[/C][C]-0.00785301[/C][/ROW]
[ROW][C]26[/C][C]17.21[/C][C]17.2339[/C][C]17.2642[/C][C]-0.030272[/C][C]-0.0238947[/C][/ROW]
[ROW][C]27[/C][C]17.37[/C][C]17.3025[/C][C]17.3004[/C][C]0.00208912[/C][C]0.0674942[/C][/ROW]
[ROW][C]28[/C][C]17.43[/C][C]17.3515[/C][C]17.3308[/C][C]0.0207002[/C][C]0.0784664[/C][/ROW]
[ROW][C]29[/C][C]17.44[/C][C]17.4021[/C][C]17.3596[/C][C]0.0425058[/C][C]0.0379109[/C][/ROW]
[ROW][C]30[/C][C]17.46[/C][C]17.4042[/C][C]17.3867[/C][C]0.0175752[/C][C]0.0557581[/C][/ROW]
[ROW][C]31[/C][C]17.42[/C][C]17.394[/C][C]17.4117[/C][C]-0.0176331[/C][C]0.0259664[/C][/ROW]
[ROW][C]32[/C][C]17.47[/C][C]17.4449[/C][C]17.4388[/C][C]0.0061169[/C][C]0.0251331[/C][/ROW]
[ROW][C]33[/C][C]17.45[/C][C]17.4734[/C][C]17.4633[/C][C]0.0100752[/C][C]-0.0234086[/C][/ROW]
[ROW][C]34[/C][C]17.44[/C][C]17.4923[/C][C]17.4808[/C][C]0.0114641[/C][C]-0.0522975[/C][/ROW]
[ROW][C]35[/C][C]17.46[/C][C]17.4917[/C][C]17.495[/C][C]-0.00332755[/C][C]-0.0316725[/C][/ROW]
[ROW][C]36[/C][C]17.47[/C][C]17.4912[/C][C]17.5062[/C][C]-0.0150637[/C][C]-0.0211863[/C][/ROW]
[ROW][C]37[/C][C]17.47[/C][C]17.4737[/C][C]17.5179[/C][C]-0.0442303[/C][C]-0.00368634[/C][/ROW]
[ROW][C]38[/C][C]17.56[/C][C]17.4997[/C][C]17.53[/C][C]-0.030272[/C][C]0.060272[/C][/ROW]
[ROW][C]39[/C][C]17.61[/C][C]17.5467[/C][C]17.5446[/C][C]0.00208912[/C][C]0.0633275[/C][/ROW]
[ROW][C]40[/C][C]17.61[/C][C]17.587[/C][C]17.5662[/C][C]0.0207002[/C][C]0.0230498[/C][/ROW]
[ROW][C]41[/C][C]17.6[/C][C]17.6329[/C][C]17.5904[/C][C]0.0425058[/C][C]-0.0329225[/C][/ROW]
[ROW][C]42[/C][C]17.57[/C][C]17.6317[/C][C]17.6142[/C][C]0.0175752[/C][C]-0.0617419[/C][/ROW]
[ROW][C]43[/C][C]17.59[/C][C]17.6199[/C][C]17.6375[/C][C]-0.0176331[/C][C]-0.0298669[/C][/ROW]
[ROW][C]44[/C][C]17.59[/C][C]17.6674[/C][C]17.6612[/C][C]0.0061169[/C][C]-0.0773669[/C][/ROW]
[ROW][C]45[/C][C]17.68[/C][C]17.7022[/C][C]17.6921[/C][C]0.0100752[/C][C]-0.0221586[/C][/ROW]
[ROW][C]46[/C][C]17.73[/C][C]17.7406[/C][C]17.7292[/C][C]0.0114641[/C][C]-0.0106308[/C][/ROW]
[ROW][C]47[/C][C]17.75[/C][C]17.7675[/C][C]17.7708[/C][C]-0.00332755[/C][C]-0.0175058[/C][/ROW]
[ROW][C]48[/C][C]17.75[/C][C]17.8054[/C][C]17.8204[/C][C]-0.0150637[/C][C]-0.055353[/C][/ROW]
[ROW][C]49[/C][C]17.75[/C][C]17.8283[/C][C]17.8725[/C][C]-0.0442303[/C][C]-0.0782697[/C][/ROW]
[ROW][C]50[/C][C]17.85[/C][C]17.8989[/C][C]17.9292[/C][C]-0.030272[/C][C]-0.0488947[/C][/ROW]
[ROW][C]51[/C][C]18.06[/C][C]17.9904[/C][C]17.9883[/C][C]0.00208912[/C][C]0.0695775[/C][/ROW]
[ROW][C]52[/C][C]18.05[/C][C]18.064[/C][C]18.0433[/C][C]0.0207002[/C][C]-0.0140336[/C][/ROW]
[ROW][C]53[/C][C]18.16[/C][C]18.1396[/C][C]18.0971[/C][C]0.0425058[/C][C]0.0204109[/C][/ROW]
[ROW][C]54[/C][C]18.2[/C][C]18.1717[/C][C]18.1542[/C][C]0.0175752[/C][C]0.0282581[/C][/ROW]
[ROW][C]55[/C][C]18.21[/C][C]18.1974[/C][C]18.215[/C][C]-0.0176331[/C][C]0.0126331[/C][/ROW]
[ROW][C]56[/C][C]18.33[/C][C]18.279[/C][C]18.2729[/C][C]0.0061169[/C][C]0.0509664[/C][/ROW]
[ROW][C]57[/C][C]18.36[/C][C]18.3297[/C][C]18.3196[/C][C]0.0100752[/C][C]0.0303414[/C][/ROW]
[ROW][C]58[/C][C]18.37[/C][C]18.3719[/C][C]18.3604[/C][C]0.0114641[/C][C]-0.00188079[/C][/ROW]
[ROW][C]59[/C][C]18.4[/C][C]18.3967[/C][C]18.4[/C][C]-0.00332755[/C][C]0.00332755[/C][/ROW]
[ROW][C]60[/C][C]18.47[/C][C]18.4204[/C][C]18.4354[/C][C]-0.0150637[/C][C]0.049647[/C][/ROW]
[ROW][C]61[/C][C]18.49[/C][C]18.4254[/C][C]18.4696[/C][C]-0.0442303[/C][C]0.064647[/C][/ROW]
[ROW][C]62[/C][C]18.5[/C][C]18.4681[/C][C]18.4983[/C][C]-0.030272[/C][C]0.0319387[/C][/ROW]
[ROW][C]63[/C][C]18.53[/C][C]18.5242[/C][C]18.5221[/C][C]0.00208912[/C][C]0.00582755[/C][/ROW]
[ROW][C]64[/C][C]18.56[/C][C]18.5715[/C][C]18.5508[/C][C]0.0207002[/C][C]-0.0115336[/C][/ROW]
[ROW][C]65[/C][C]18.6[/C][C]18.6258[/C][C]18.5833[/C][C]0.0425058[/C][C]-0.0258391[/C][/ROW]
[ROW][C]66[/C][C]18.61[/C][C]18.6297[/C][C]18.6121[/C][C]0.0175752[/C][C]-0.0196586[/C][/ROW]
[ROW][C]67[/C][C]18.62[/C][C]18.6203[/C][C]18.6379[/C][C]-0.0176331[/C][C]-0.000283565[/C][/ROW]
[ROW][C]68[/C][C]18.61[/C][C]18.6715[/C][C]18.6654[/C][C]0.0061169[/C][C]-0.0615336[/C][/ROW]
[ROW][C]69[/C][C]18.65[/C][C]18.7034[/C][C]18.6933[/C][C]0.0100752[/C][C]-0.0534086[/C][/ROW]
[ROW][C]70[/C][C]18.77[/C][C]18.7356[/C][C]18.7242[/C][C]0.0114641[/C][C]0.0343692[/C][/ROW]
[ROW][C]71[/C][C]18.78[/C][C]18.7575[/C][C]18.7608[/C][C]-0.00332755[/C][C]0.0224942[/C][/ROW]
[ROW][C]72[/C][C]18.78[/C][C]18.7845[/C][C]18.7996[/C][C]-0.0150637[/C][C]-0.00451968[/C][/ROW]
[ROW][C]73[/C][C]18.8[/C][C]18.7987[/C][C]18.8429[/C][C]-0.0442303[/C][C]0.00131366[/C][/ROW]
[ROW][C]74[/C][C]18.85[/C][C]18.8614[/C][C]18.8917[/C][C]-0.030272[/C][C]-0.0113947[/C][/ROW]
[ROW][C]75[/C][C]18.85[/C][C]18.9454[/C][C]18.9433[/C][C]0.00208912[/C][C]-0.0954225[/C][/ROW]
[ROW][C]76[/C][C]18.98[/C][C]19.0128[/C][C]18.9921[/C][C]0.0207002[/C][C]-0.0327836[/C][/ROW]
[ROW][C]77[/C][C]19.06[/C][C]19.0808[/C][C]19.0383[/C][C]0.0425058[/C][C]-0.0208391[/C][/ROW]
[ROW][C]78[/C][C]19.08[/C][C]19.1042[/C][C]19.0867[/C][C]0.0175752[/C][C]-0.0242419[/C][/ROW]
[ROW][C]79[/C][C]19.19[/C][C]NA[/C][C]NA[/C][C]-0.0176331[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]19.21[/C][C]NA[/C][C]NA[/C][C]0.0061169[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]19.29[/C][C]NA[/C][C]NA[/C][C]0.0100752[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]19.3[/C][C]NA[/C][C]NA[/C][C]0.0114641[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]19.36[/C][C]NA[/C][C]NA[/C][C]-0.00332755[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]19.36[/C][C]NA[/C][C]NA[/C][C]-0.0150637[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230441&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230441&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
116.3NANA-0.0442303NA
216.37NANA-0.030272NA
316.38NANA0.00208912NA
416.37NANA0.0207002NA
516.42NANA0.0425058NA
616.43NANA0.0175752NA
716.4416.45916.4767-0.0176331-0.0190336
816.5316.507416.50120.00611690.0226331
916.5516.532216.52210.01007520.0178414
1016.5616.558516.54710.01146410.00145255
1116.616.577916.5812-0.003327550.0220775
1216.6116.604116.6192-0.01506370.00589699
1316.6216.612916.6571-0.04423030.00714699
1416.6416.664716.695-0.030272-0.024728
1516.6116.737516.73540.00208912-0.127506
1616.7416.799916.77920.0207002-0.0598669
1716.8716.865416.82290.04250580.00457755
1816.8916.885116.86750.01757520.00492477
1916.8916.896116.9138-0.0176331-0.0061169
2016.9916.966516.96040.00611690.0234664
2117.0617.025917.01580.01007520.0340914
2217.117.087717.07630.01146410.0122859
2317.1117.125417.1288-0.00332755-0.0154225
2417.1717.161217.1762-0.01506370.00881366
2517.1717.177917.2221-0.0442303-0.00785301
2617.2117.233917.2642-0.030272-0.0238947
2717.3717.302517.30040.002089120.0674942
2817.4317.351517.33080.02070020.0784664
2917.4417.402117.35960.04250580.0379109
3017.4617.404217.38670.01757520.0557581
3117.4217.39417.4117-0.01763310.0259664
3217.4717.444917.43880.00611690.0251331
3317.4517.473417.46330.0100752-0.0234086
3417.4417.492317.48080.0114641-0.0522975
3517.4617.491717.495-0.00332755-0.0316725
3617.4717.491217.5062-0.0150637-0.0211863
3717.4717.473717.5179-0.0442303-0.00368634
3817.5617.499717.53-0.0302720.060272
3917.6117.546717.54460.002089120.0633275
4017.6117.58717.56620.02070020.0230498
4117.617.632917.59040.0425058-0.0329225
4217.5717.631717.61420.0175752-0.0617419
4317.5917.619917.6375-0.0176331-0.0298669
4417.5917.667417.66120.0061169-0.0773669
4517.6817.702217.69210.0100752-0.0221586
4617.7317.740617.72920.0114641-0.0106308
4717.7517.767517.7708-0.00332755-0.0175058
4817.7517.805417.8204-0.0150637-0.055353
4917.7517.828317.8725-0.0442303-0.0782697
5017.8517.898917.9292-0.030272-0.0488947
5118.0617.990417.98830.002089120.0695775
5218.0518.06418.04330.0207002-0.0140336
5318.1618.139618.09710.04250580.0204109
5418.218.171718.15420.01757520.0282581
5518.2118.197418.215-0.01763310.0126331
5618.3318.27918.27290.00611690.0509664
5718.3618.329718.31960.01007520.0303414
5818.3718.371918.36040.0114641-0.00188079
5918.418.396718.4-0.003327550.00332755
6018.4718.420418.4354-0.01506370.049647
6118.4918.425418.4696-0.04423030.064647
6218.518.468118.4983-0.0302720.0319387
6318.5318.524218.52210.002089120.00582755
6418.5618.571518.55080.0207002-0.0115336
6518.618.625818.58330.0425058-0.0258391
6618.6118.629718.61210.0175752-0.0196586
6718.6218.620318.6379-0.0176331-0.000283565
6818.6118.671518.66540.0061169-0.0615336
6918.6518.703418.69330.0100752-0.0534086
7018.7718.735618.72420.01146410.0343692
7118.7818.757518.7608-0.003327550.0224942
7218.7818.784518.7996-0.0150637-0.00451968
7318.818.798718.8429-0.04423030.00131366
7418.8518.861418.8917-0.030272-0.0113947
7518.8518.945418.94330.00208912-0.0954225
7618.9819.012818.99210.0207002-0.0327836
7719.0619.080819.03830.0425058-0.0208391
7819.0819.104219.08670.0175752-0.0242419
7919.19NANA-0.0176331NA
8019.21NANA0.0061169NA
8119.29NANA0.0100752NA
8219.3NANA0.0114641NA
8319.36NANA-0.00332755NA
8419.36NANA-0.0150637NA


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 <- '12'
par1 <- 'multiplicative'
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')