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Description of Statistical Computation

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Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 04:50:26 -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/12/t13868419859h4ifuaj73p308t.htm/, Retrieved Fri, 19 Apr 2024 05:28:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232239, Retrieved Fri, 19 Apr 2024 05:28:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 09:50:26] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 15,13 
 15,25 
 15,33 
 15,36 
 15,40 
 15,40 
 15,41 
 15,47 
 15,54 
 15,55 
 15,59 
 15,65 
 15,75 
 15,86 
 15,89 
 15,94 
 15,93 
 15,95 
 15,99 
 15,99 
 16,06 
 16,08 
 16,07 
 16,11 
 16,15 
 16,18 
 16,30 
 16,42 
 16,49 
 16,50 
 16,58 
 16,64 
 16,66 
 16,81 
 16,91 
 16,92 
 16,95 
 17,11 
 17,16 
 17,16 
 17,27 
 17,34 
 17,39 
 17,43 
 17,45 
 17,50 
 17,56 
 17,65 
 17,62 
 17,70 
 17,72 
 17,71 
 17,74 
 17,75 
 17,78 
 17,80 
 17,86 
 17,88 
 17,89 
 17,94 
 17,98 
 18,10 
 18,14 
 18,19 
 18,23 
 18,24 
 18,27 
 18,30 
 18,34 
 18,36 
 18,36 
 18,40 
 18,43 
 18,47 
 18,56 
 18,58 
 18,61 
 18,61 
 18,69 
 18,74 
 18,75 
 18,81 
 18,85 
 18,88

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 8 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232239&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232239&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232239&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 time8 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
115.13NANA-0.0269444NA
215.25NANA0.0175694NA
315.33NANA0.0309028NA
415.36NANA0.0243056NA
515.4NANA0.0240278NA
615.4NANA-0.00104167NA
715.4115.448115.4492-0.00111111-0.0380556
815.4715.48915.5004-0.0113889-0.0190278
915.5415.539715.5492-0.009513890.000347222
1015.5515.587415.5967-0.00930556-0.0373611
1115.5915.622315.6429-0.020625-0.0322917
1215.6515.67115.6879-0.016875-0.0210417
1315.7515.708115.735-0.02694440.0419444
1415.8615.798415.78080.01756940.0615972
1515.8915.855115.82420.03090280.0349306
1615.9415.892215.86790.02430560.0477778
1715.9315.93415.910.0240278-0.00402778
1815.9515.948115.9492-0.001041670.001875
1915.9915.983915.985-0.001111110.00611111
2015.9916.003616.015-0.0113889-0.0136111
2116.0616.035916.0454-0.009513890.0240972
2216.0816.073216.0825-0.009305560.00680556
2316.0716.105216.1258-0.020625-0.0352083
2416.1116.155216.1721-0.016875-0.0452083
2516.1516.192616.2196-0.0269444-0.0426389
2616.1816.288816.27120.0175694-0.108819
2716.316.354216.32330.0309028-0.0542361
2816.4216.403116.37870.02430560.0169444
2916.4916.468216.44420.02402780.0218056
3016.516.511916.5129-0.00104167-0.011875
3116.5816.578916.58-0.001111110.00111111
3216.6416.640716.6521-0.0113889-0.000694444
3316.6616.717216.7267-0.00951389-0.0571528
3416.8116.78416.7933-0.009305560.0259722
3516.9116.83616.8567-0.0206250.0739583
3616.9216.907316.9242-0.0168750.0127083
3716.9516.96616.9929-0.0269444-0.0159722
3817.1117.077217.05960.01756940.0328472
3917.1617.156317.12540.03090280.00368056
4017.1617.211417.18710.0243056-0.0513889
4117.2717.266917.24290.02402780.00305556
4217.3417.299417.3004-0.001041670.040625
4317.3917.357617.3588-0.001111110.0323611
4417.4317.399917.4112-0.01138890.0301389
4517.4517.449717.4592-0.009513890.000347222
4617.517.496117.5054-0.009305560.00388889
4717.5617.527317.5479-0.0206250.0327083
4817.6517.567717.5846-0.0168750.0822917
4917.6217.59117.6179-0.02694440.0290278
5017.717.667217.64960.01756940.0328472
5117.7217.71317.68210.03090280.00701389
5217.7117.739317.7150.0243056-0.0293056
5317.7417.768617.74460.0240278-0.0286111
5417.7517.769417.7704-0.00104167-0.019375
5517.7817.796417.7975-0.00111111-0.0163889
5617.817.817817.8292-0.0113889-0.0177778
5717.8617.853817.8633-0.009513890.00618056
5817.8817.891517.9008-0.00930556-0.0115278
5917.8917.920617.9412-0.020625-0.030625
6017.9417.965217.9821-0.016875-0.0252083
6117.9817.99618.0229-0.0269444-0.0159722
6218.118.081718.06420.01756940.0182639
6318.1418.135918.1050.03090280.00409722
6418.1918.169318.1450.02430560.0206944
6518.2318.208618.18460.02402780.0213889
6618.2418.222318.2233-0.001041670.0177083
6718.2718.260118.2612-0.001111110.00986111
6818.318.28418.2954-0.01138890.0159722
6918.3418.318818.3283-0.009513890.0211806
7018.3618.352818.3621-0.009305560.00722222
7118.3618.373518.3942-0.020625-0.0135417
7218.418.408518.4254-0.016875-0.00854167
7318.4318.431418.4583-0.0269444-0.00138889
7418.4718.511718.49420.0175694-0.0417361
7518.5618.560518.52960.0309028-0.000486111
7618.5818.589718.56540.0243056-0.00972222
7718.6118.628618.60460.0240278-0.0186111
7818.6118.64418.645-0.00104167-0.0339583
7918.69NANA-0.00111111NA
8018.74NANA-0.0113889NA
8118.75NANA-0.00951389NA
8218.81NANA-0.00930556NA
8318.85NANA-0.020625NA
8418.88NANA-0.016875NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 15.13 & NA & NA & -0.0269444 & NA \tabularnewline
2 & 15.25 & NA & NA & 0.0175694 & NA \tabularnewline
3 & 15.33 & NA & NA & 0.0309028 & NA \tabularnewline
4 & 15.36 & NA & NA & 0.0243056 & NA \tabularnewline
5 & 15.4 & NA & NA & 0.0240278 & NA \tabularnewline
6 & 15.4 & NA & NA & -0.00104167 & NA \tabularnewline
7 & 15.41 & 15.4481 & 15.4492 & -0.00111111 & -0.0380556 \tabularnewline
8 & 15.47 & 15.489 & 15.5004 & -0.0113889 & -0.0190278 \tabularnewline
9 & 15.54 & 15.5397 & 15.5492 & -0.00951389 & 0.000347222 \tabularnewline
10 & 15.55 & 15.5874 & 15.5967 & -0.00930556 & -0.0373611 \tabularnewline
11 & 15.59 & 15.6223 & 15.6429 & -0.020625 & -0.0322917 \tabularnewline
12 & 15.65 & 15.671 & 15.6879 & -0.016875 & -0.0210417 \tabularnewline
13 & 15.75 & 15.7081 & 15.735 & -0.0269444 & 0.0419444 \tabularnewline
14 & 15.86 & 15.7984 & 15.7808 & 0.0175694 & 0.0615972 \tabularnewline
15 & 15.89 & 15.8551 & 15.8242 & 0.0309028 & 0.0349306 \tabularnewline
16 & 15.94 & 15.8922 & 15.8679 & 0.0243056 & 0.0477778 \tabularnewline
17 & 15.93 & 15.934 & 15.91 & 0.0240278 & -0.00402778 \tabularnewline
18 & 15.95 & 15.9481 & 15.9492 & -0.00104167 & 0.001875 \tabularnewline
19 & 15.99 & 15.9839 & 15.985 & -0.00111111 & 0.00611111 \tabularnewline
20 & 15.99 & 16.0036 & 16.015 & -0.0113889 & -0.0136111 \tabularnewline
21 & 16.06 & 16.0359 & 16.0454 & -0.00951389 & 0.0240972 \tabularnewline
22 & 16.08 & 16.0732 & 16.0825 & -0.00930556 & 0.00680556 \tabularnewline
23 & 16.07 & 16.1052 & 16.1258 & -0.020625 & -0.0352083 \tabularnewline
24 & 16.11 & 16.1552 & 16.1721 & -0.016875 & -0.0452083 \tabularnewline
25 & 16.15 & 16.1926 & 16.2196 & -0.0269444 & -0.0426389 \tabularnewline
26 & 16.18 & 16.2888 & 16.2712 & 0.0175694 & -0.108819 \tabularnewline
27 & 16.3 & 16.3542 & 16.3233 & 0.0309028 & -0.0542361 \tabularnewline
28 & 16.42 & 16.4031 & 16.3787 & 0.0243056 & 0.0169444 \tabularnewline
29 & 16.49 & 16.4682 & 16.4442 & 0.0240278 & 0.0218056 \tabularnewline
30 & 16.5 & 16.5119 & 16.5129 & -0.00104167 & -0.011875 \tabularnewline
31 & 16.58 & 16.5789 & 16.58 & -0.00111111 & 0.00111111 \tabularnewline
32 & 16.64 & 16.6407 & 16.6521 & -0.0113889 & -0.000694444 \tabularnewline
33 & 16.66 & 16.7172 & 16.7267 & -0.00951389 & -0.0571528 \tabularnewline
34 & 16.81 & 16.784 & 16.7933 & -0.00930556 & 0.0259722 \tabularnewline
35 & 16.91 & 16.836 & 16.8567 & -0.020625 & 0.0739583 \tabularnewline
36 & 16.92 & 16.9073 & 16.9242 & -0.016875 & 0.0127083 \tabularnewline
37 & 16.95 & 16.966 & 16.9929 & -0.0269444 & -0.0159722 \tabularnewline
38 & 17.11 & 17.0772 & 17.0596 & 0.0175694 & 0.0328472 \tabularnewline
39 & 17.16 & 17.1563 & 17.1254 & 0.0309028 & 0.00368056 \tabularnewline
40 & 17.16 & 17.2114 & 17.1871 & 0.0243056 & -0.0513889 \tabularnewline
41 & 17.27 & 17.2669 & 17.2429 & 0.0240278 & 0.00305556 \tabularnewline
42 & 17.34 & 17.2994 & 17.3004 & -0.00104167 & 0.040625 \tabularnewline
43 & 17.39 & 17.3576 & 17.3588 & -0.00111111 & 0.0323611 \tabularnewline
44 & 17.43 & 17.3999 & 17.4112 & -0.0113889 & 0.0301389 \tabularnewline
45 & 17.45 & 17.4497 & 17.4592 & -0.00951389 & 0.000347222 \tabularnewline
46 & 17.5 & 17.4961 & 17.5054 & -0.00930556 & 0.00388889 \tabularnewline
47 & 17.56 & 17.5273 & 17.5479 & -0.020625 & 0.0327083 \tabularnewline
48 & 17.65 & 17.5677 & 17.5846 & -0.016875 & 0.0822917 \tabularnewline
49 & 17.62 & 17.591 & 17.6179 & -0.0269444 & 0.0290278 \tabularnewline
50 & 17.7 & 17.6672 & 17.6496 & 0.0175694 & 0.0328472 \tabularnewline
51 & 17.72 & 17.713 & 17.6821 & 0.0309028 & 0.00701389 \tabularnewline
52 & 17.71 & 17.7393 & 17.715 & 0.0243056 & -0.0293056 \tabularnewline
53 & 17.74 & 17.7686 & 17.7446 & 0.0240278 & -0.0286111 \tabularnewline
54 & 17.75 & 17.7694 & 17.7704 & -0.00104167 & -0.019375 \tabularnewline
55 & 17.78 & 17.7964 & 17.7975 & -0.00111111 & -0.0163889 \tabularnewline
56 & 17.8 & 17.8178 & 17.8292 & -0.0113889 & -0.0177778 \tabularnewline
57 & 17.86 & 17.8538 & 17.8633 & -0.00951389 & 0.00618056 \tabularnewline
58 & 17.88 & 17.8915 & 17.9008 & -0.00930556 & -0.0115278 \tabularnewline
59 & 17.89 & 17.9206 & 17.9412 & -0.020625 & -0.030625 \tabularnewline
60 & 17.94 & 17.9652 & 17.9821 & -0.016875 & -0.0252083 \tabularnewline
61 & 17.98 & 17.996 & 18.0229 & -0.0269444 & -0.0159722 \tabularnewline
62 & 18.1 & 18.0817 & 18.0642 & 0.0175694 & 0.0182639 \tabularnewline
63 & 18.14 & 18.1359 & 18.105 & 0.0309028 & 0.00409722 \tabularnewline
64 & 18.19 & 18.1693 & 18.145 & 0.0243056 & 0.0206944 \tabularnewline
65 & 18.23 & 18.2086 & 18.1846 & 0.0240278 & 0.0213889 \tabularnewline
66 & 18.24 & 18.2223 & 18.2233 & -0.00104167 & 0.0177083 \tabularnewline
67 & 18.27 & 18.2601 & 18.2612 & -0.00111111 & 0.00986111 \tabularnewline
68 & 18.3 & 18.284 & 18.2954 & -0.0113889 & 0.0159722 \tabularnewline
69 & 18.34 & 18.3188 & 18.3283 & -0.00951389 & 0.0211806 \tabularnewline
70 & 18.36 & 18.3528 & 18.3621 & -0.00930556 & 0.00722222 \tabularnewline
71 & 18.36 & 18.3735 & 18.3942 & -0.020625 & -0.0135417 \tabularnewline
72 & 18.4 & 18.4085 & 18.4254 & -0.016875 & -0.00854167 \tabularnewline
73 & 18.43 & 18.4314 & 18.4583 & -0.0269444 & -0.00138889 \tabularnewline
74 & 18.47 & 18.5117 & 18.4942 & 0.0175694 & -0.0417361 \tabularnewline
75 & 18.56 & 18.5605 & 18.5296 & 0.0309028 & -0.000486111 \tabularnewline
76 & 18.58 & 18.5897 & 18.5654 & 0.0243056 & -0.00972222 \tabularnewline
77 & 18.61 & 18.6286 & 18.6046 & 0.0240278 & -0.0186111 \tabularnewline
78 & 18.61 & 18.644 & 18.645 & -0.00104167 & -0.0339583 \tabularnewline
79 & 18.69 & NA & NA & -0.00111111 & NA \tabularnewline
80 & 18.74 & NA & NA & -0.0113889 & NA \tabularnewline
81 & 18.75 & NA & NA & -0.00951389 & NA \tabularnewline
82 & 18.81 & NA & NA & -0.00930556 & NA \tabularnewline
83 & 18.85 & NA & NA & -0.020625 & NA \tabularnewline
84 & 18.88 & NA & NA & -0.016875 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232239&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]15.13[/C][C]NA[/C][C]NA[/C][C]-0.0269444[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]15.25[/C][C]NA[/C][C]NA[/C][C]0.0175694[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]15.33[/C][C]NA[/C][C]NA[/C][C]0.0309028[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]15.36[/C][C]NA[/C][C]NA[/C][C]0.0243056[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]15.4[/C][C]NA[/C][C]NA[/C][C]0.0240278[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]15.4[/C][C]NA[/C][C]NA[/C][C]-0.00104167[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]15.41[/C][C]15.4481[/C][C]15.4492[/C][C]-0.00111111[/C][C]-0.0380556[/C][/ROW]
[ROW][C]8[/C][C]15.47[/C][C]15.489[/C][C]15.5004[/C][C]-0.0113889[/C][C]-0.0190278[/C][/ROW]
[ROW][C]9[/C][C]15.54[/C][C]15.5397[/C][C]15.5492[/C][C]-0.00951389[/C][C]0.000347222[/C][/ROW]
[ROW][C]10[/C][C]15.55[/C][C]15.5874[/C][C]15.5967[/C][C]-0.00930556[/C][C]-0.0373611[/C][/ROW]
[ROW][C]11[/C][C]15.59[/C][C]15.6223[/C][C]15.6429[/C][C]-0.020625[/C][C]-0.0322917[/C][/ROW]
[ROW][C]12[/C][C]15.65[/C][C]15.671[/C][C]15.6879[/C][C]-0.016875[/C][C]-0.0210417[/C][/ROW]
[ROW][C]13[/C][C]15.75[/C][C]15.7081[/C][C]15.735[/C][C]-0.0269444[/C][C]0.0419444[/C][/ROW]
[ROW][C]14[/C][C]15.86[/C][C]15.7984[/C][C]15.7808[/C][C]0.0175694[/C][C]0.0615972[/C][/ROW]
[ROW][C]15[/C][C]15.89[/C][C]15.8551[/C][C]15.8242[/C][C]0.0309028[/C][C]0.0349306[/C][/ROW]
[ROW][C]16[/C][C]15.94[/C][C]15.8922[/C][C]15.8679[/C][C]0.0243056[/C][C]0.0477778[/C][/ROW]
[ROW][C]17[/C][C]15.93[/C][C]15.934[/C][C]15.91[/C][C]0.0240278[/C][C]-0.00402778[/C][/ROW]
[ROW][C]18[/C][C]15.95[/C][C]15.9481[/C][C]15.9492[/C][C]-0.00104167[/C][C]0.001875[/C][/ROW]
[ROW][C]19[/C][C]15.99[/C][C]15.9839[/C][C]15.985[/C][C]-0.00111111[/C][C]0.00611111[/C][/ROW]
[ROW][C]20[/C][C]15.99[/C][C]16.0036[/C][C]16.015[/C][C]-0.0113889[/C][C]-0.0136111[/C][/ROW]
[ROW][C]21[/C][C]16.06[/C][C]16.0359[/C][C]16.0454[/C][C]-0.00951389[/C][C]0.0240972[/C][/ROW]
[ROW][C]22[/C][C]16.08[/C][C]16.0732[/C][C]16.0825[/C][C]-0.00930556[/C][C]0.00680556[/C][/ROW]
[ROW][C]23[/C][C]16.07[/C][C]16.1052[/C][C]16.1258[/C][C]-0.020625[/C][C]-0.0352083[/C][/ROW]
[ROW][C]24[/C][C]16.11[/C][C]16.1552[/C][C]16.1721[/C][C]-0.016875[/C][C]-0.0452083[/C][/ROW]
[ROW][C]25[/C][C]16.15[/C][C]16.1926[/C][C]16.2196[/C][C]-0.0269444[/C][C]-0.0426389[/C][/ROW]
[ROW][C]26[/C][C]16.18[/C][C]16.2888[/C][C]16.2712[/C][C]0.0175694[/C][C]-0.108819[/C][/ROW]
[ROW][C]27[/C][C]16.3[/C][C]16.3542[/C][C]16.3233[/C][C]0.0309028[/C][C]-0.0542361[/C][/ROW]
[ROW][C]28[/C][C]16.42[/C][C]16.4031[/C][C]16.3787[/C][C]0.0243056[/C][C]0.0169444[/C][/ROW]
[ROW][C]29[/C][C]16.49[/C][C]16.4682[/C][C]16.4442[/C][C]0.0240278[/C][C]0.0218056[/C][/ROW]
[ROW][C]30[/C][C]16.5[/C][C]16.5119[/C][C]16.5129[/C][C]-0.00104167[/C][C]-0.011875[/C][/ROW]
[ROW][C]31[/C][C]16.58[/C][C]16.5789[/C][C]16.58[/C][C]-0.00111111[/C][C]0.00111111[/C][/ROW]
[ROW][C]32[/C][C]16.64[/C][C]16.6407[/C][C]16.6521[/C][C]-0.0113889[/C][C]-0.000694444[/C][/ROW]
[ROW][C]33[/C][C]16.66[/C][C]16.7172[/C][C]16.7267[/C][C]-0.00951389[/C][C]-0.0571528[/C][/ROW]
[ROW][C]34[/C][C]16.81[/C][C]16.784[/C][C]16.7933[/C][C]-0.00930556[/C][C]0.0259722[/C][/ROW]
[ROW][C]35[/C][C]16.91[/C][C]16.836[/C][C]16.8567[/C][C]-0.020625[/C][C]0.0739583[/C][/ROW]
[ROW][C]36[/C][C]16.92[/C][C]16.9073[/C][C]16.9242[/C][C]-0.016875[/C][C]0.0127083[/C][/ROW]
[ROW][C]37[/C][C]16.95[/C][C]16.966[/C][C]16.9929[/C][C]-0.0269444[/C][C]-0.0159722[/C][/ROW]
[ROW][C]38[/C][C]17.11[/C][C]17.0772[/C][C]17.0596[/C][C]0.0175694[/C][C]0.0328472[/C][/ROW]
[ROW][C]39[/C][C]17.16[/C][C]17.1563[/C][C]17.1254[/C][C]0.0309028[/C][C]0.00368056[/C][/ROW]
[ROW][C]40[/C][C]17.16[/C][C]17.2114[/C][C]17.1871[/C][C]0.0243056[/C][C]-0.0513889[/C][/ROW]
[ROW][C]41[/C][C]17.27[/C][C]17.2669[/C][C]17.2429[/C][C]0.0240278[/C][C]0.00305556[/C][/ROW]
[ROW][C]42[/C][C]17.34[/C][C]17.2994[/C][C]17.3004[/C][C]-0.00104167[/C][C]0.040625[/C][/ROW]
[ROW][C]43[/C][C]17.39[/C][C]17.3576[/C][C]17.3588[/C][C]-0.00111111[/C][C]0.0323611[/C][/ROW]
[ROW][C]44[/C][C]17.43[/C][C]17.3999[/C][C]17.4112[/C][C]-0.0113889[/C][C]0.0301389[/C][/ROW]
[ROW][C]45[/C][C]17.45[/C][C]17.4497[/C][C]17.4592[/C][C]-0.00951389[/C][C]0.000347222[/C][/ROW]
[ROW][C]46[/C][C]17.5[/C][C]17.4961[/C][C]17.5054[/C][C]-0.00930556[/C][C]0.00388889[/C][/ROW]
[ROW][C]47[/C][C]17.56[/C][C]17.5273[/C][C]17.5479[/C][C]-0.020625[/C][C]0.0327083[/C][/ROW]
[ROW][C]48[/C][C]17.65[/C][C]17.5677[/C][C]17.5846[/C][C]-0.016875[/C][C]0.0822917[/C][/ROW]
[ROW][C]49[/C][C]17.62[/C][C]17.591[/C][C]17.6179[/C][C]-0.0269444[/C][C]0.0290278[/C][/ROW]
[ROW][C]50[/C][C]17.7[/C][C]17.6672[/C][C]17.6496[/C][C]0.0175694[/C][C]0.0328472[/C][/ROW]
[ROW][C]51[/C][C]17.72[/C][C]17.713[/C][C]17.6821[/C][C]0.0309028[/C][C]0.00701389[/C][/ROW]
[ROW][C]52[/C][C]17.71[/C][C]17.7393[/C][C]17.715[/C][C]0.0243056[/C][C]-0.0293056[/C][/ROW]
[ROW][C]53[/C][C]17.74[/C][C]17.7686[/C][C]17.7446[/C][C]0.0240278[/C][C]-0.0286111[/C][/ROW]
[ROW][C]54[/C][C]17.75[/C][C]17.7694[/C][C]17.7704[/C][C]-0.00104167[/C][C]-0.019375[/C][/ROW]
[ROW][C]55[/C][C]17.78[/C][C]17.7964[/C][C]17.7975[/C][C]-0.00111111[/C][C]-0.0163889[/C][/ROW]
[ROW][C]56[/C][C]17.8[/C][C]17.8178[/C][C]17.8292[/C][C]-0.0113889[/C][C]-0.0177778[/C][/ROW]
[ROW][C]57[/C][C]17.86[/C][C]17.8538[/C][C]17.8633[/C][C]-0.00951389[/C][C]0.00618056[/C][/ROW]
[ROW][C]58[/C][C]17.88[/C][C]17.8915[/C][C]17.9008[/C][C]-0.00930556[/C][C]-0.0115278[/C][/ROW]
[ROW][C]59[/C][C]17.89[/C][C]17.9206[/C][C]17.9412[/C][C]-0.020625[/C][C]-0.030625[/C][/ROW]
[ROW][C]60[/C][C]17.94[/C][C]17.9652[/C][C]17.9821[/C][C]-0.016875[/C][C]-0.0252083[/C][/ROW]
[ROW][C]61[/C][C]17.98[/C][C]17.996[/C][C]18.0229[/C][C]-0.0269444[/C][C]-0.0159722[/C][/ROW]
[ROW][C]62[/C][C]18.1[/C][C]18.0817[/C][C]18.0642[/C][C]0.0175694[/C][C]0.0182639[/C][/ROW]
[ROW][C]63[/C][C]18.14[/C][C]18.1359[/C][C]18.105[/C][C]0.0309028[/C][C]0.00409722[/C][/ROW]
[ROW][C]64[/C][C]18.19[/C][C]18.1693[/C][C]18.145[/C][C]0.0243056[/C][C]0.0206944[/C][/ROW]
[ROW][C]65[/C][C]18.23[/C][C]18.2086[/C][C]18.1846[/C][C]0.0240278[/C][C]0.0213889[/C][/ROW]
[ROW][C]66[/C][C]18.24[/C][C]18.2223[/C][C]18.2233[/C][C]-0.00104167[/C][C]0.0177083[/C][/ROW]
[ROW][C]67[/C][C]18.27[/C][C]18.2601[/C][C]18.2612[/C][C]-0.00111111[/C][C]0.00986111[/C][/ROW]
[ROW][C]68[/C][C]18.3[/C][C]18.284[/C][C]18.2954[/C][C]-0.0113889[/C][C]0.0159722[/C][/ROW]
[ROW][C]69[/C][C]18.34[/C][C]18.3188[/C][C]18.3283[/C][C]-0.00951389[/C][C]0.0211806[/C][/ROW]
[ROW][C]70[/C][C]18.36[/C][C]18.3528[/C][C]18.3621[/C][C]-0.00930556[/C][C]0.00722222[/C][/ROW]
[ROW][C]71[/C][C]18.36[/C][C]18.3735[/C][C]18.3942[/C][C]-0.020625[/C][C]-0.0135417[/C][/ROW]
[ROW][C]72[/C][C]18.4[/C][C]18.4085[/C][C]18.4254[/C][C]-0.016875[/C][C]-0.00854167[/C][/ROW]
[ROW][C]73[/C][C]18.43[/C][C]18.4314[/C][C]18.4583[/C][C]-0.0269444[/C][C]-0.00138889[/C][/ROW]
[ROW][C]74[/C][C]18.47[/C][C]18.5117[/C][C]18.4942[/C][C]0.0175694[/C][C]-0.0417361[/C][/ROW]
[ROW][C]75[/C][C]18.56[/C][C]18.5605[/C][C]18.5296[/C][C]0.0309028[/C][C]-0.000486111[/C][/ROW]
[ROW][C]76[/C][C]18.58[/C][C]18.5897[/C][C]18.5654[/C][C]0.0243056[/C][C]-0.00972222[/C][/ROW]
[ROW][C]77[/C][C]18.61[/C][C]18.6286[/C][C]18.6046[/C][C]0.0240278[/C][C]-0.0186111[/C][/ROW]
[ROW][C]78[/C][C]18.61[/C][C]18.644[/C][C]18.645[/C][C]-0.00104167[/C][C]-0.0339583[/C][/ROW]
[ROW][C]79[/C][C]18.69[/C][C]NA[/C][C]NA[/C][C]-0.00111111[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]18.74[/C][C]NA[/C][C]NA[/C][C]-0.0113889[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]18.75[/C][C]NA[/C][C]NA[/C][C]-0.00951389[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]18.81[/C][C]NA[/C][C]NA[/C][C]-0.00930556[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]18.85[/C][C]NA[/C][C]NA[/C][C]-0.020625[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]18.88[/C][C]NA[/C][C]NA[/C][C]-0.016875[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232239&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232239&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
115.13NANA-0.0269444NA
215.25NANA0.0175694NA
315.33NANA0.0309028NA
415.36NANA0.0243056NA
515.4NANA0.0240278NA
615.4NANA-0.00104167NA
715.4115.448115.4492-0.00111111-0.0380556
815.4715.48915.5004-0.0113889-0.0190278
915.5415.539715.5492-0.009513890.000347222
1015.5515.587415.5967-0.00930556-0.0373611
1115.5915.622315.6429-0.020625-0.0322917
1215.6515.67115.6879-0.016875-0.0210417
1315.7515.708115.735-0.02694440.0419444
1415.8615.798415.78080.01756940.0615972
1515.8915.855115.82420.03090280.0349306
1615.9415.892215.86790.02430560.0477778
1715.9315.93415.910.0240278-0.00402778
1815.9515.948115.9492-0.001041670.001875
1915.9915.983915.985-0.001111110.00611111
2015.9916.003616.015-0.0113889-0.0136111
2116.0616.035916.0454-0.009513890.0240972
2216.0816.073216.0825-0.009305560.00680556
2316.0716.105216.1258-0.020625-0.0352083
2416.1116.155216.1721-0.016875-0.0452083
2516.1516.192616.2196-0.0269444-0.0426389
2616.1816.288816.27120.0175694-0.108819
2716.316.354216.32330.0309028-0.0542361
2816.4216.403116.37870.02430560.0169444
2916.4916.468216.44420.02402780.0218056
3016.516.511916.5129-0.00104167-0.011875
3116.5816.578916.58-0.001111110.00111111
3216.6416.640716.6521-0.0113889-0.000694444
3316.6616.717216.7267-0.00951389-0.0571528
3416.8116.78416.7933-0.009305560.0259722
3516.9116.83616.8567-0.0206250.0739583
3616.9216.907316.9242-0.0168750.0127083
3716.9516.96616.9929-0.0269444-0.0159722
3817.1117.077217.05960.01756940.0328472
3917.1617.156317.12540.03090280.00368056
4017.1617.211417.18710.0243056-0.0513889
4117.2717.266917.24290.02402780.00305556
4217.3417.299417.3004-0.001041670.040625
4317.3917.357617.3588-0.001111110.0323611
4417.4317.399917.4112-0.01138890.0301389
4517.4517.449717.4592-0.009513890.000347222
4617.517.496117.5054-0.009305560.00388889
4717.5617.527317.5479-0.0206250.0327083
4817.6517.567717.5846-0.0168750.0822917
4917.6217.59117.6179-0.02694440.0290278
5017.717.667217.64960.01756940.0328472
5117.7217.71317.68210.03090280.00701389
5217.7117.739317.7150.0243056-0.0293056
5317.7417.768617.74460.0240278-0.0286111
5417.7517.769417.7704-0.00104167-0.019375
5517.7817.796417.7975-0.00111111-0.0163889
5617.817.817817.8292-0.0113889-0.0177778
5717.8617.853817.8633-0.009513890.00618056
5817.8817.891517.9008-0.00930556-0.0115278
5917.8917.920617.9412-0.020625-0.030625
6017.9417.965217.9821-0.016875-0.0252083
6117.9817.99618.0229-0.0269444-0.0159722
6218.118.081718.06420.01756940.0182639
6318.1418.135918.1050.03090280.00409722
6418.1918.169318.1450.02430560.0206944
6518.2318.208618.18460.02402780.0213889
6618.2418.222318.2233-0.001041670.0177083
6718.2718.260118.2612-0.001111110.00986111
6818.318.28418.2954-0.01138890.0159722
6918.3418.318818.3283-0.009513890.0211806
7018.3618.352818.3621-0.009305560.00722222
7118.3618.373518.3942-0.020625-0.0135417
7218.418.408518.4254-0.016875-0.00854167
7318.4318.431418.4583-0.0269444-0.00138889
7418.4718.511718.49420.0175694-0.0417361
7518.5618.560518.52960.0309028-0.000486111
7618.5818.589718.56540.0243056-0.00972222
7718.6118.628618.60460.0240278-0.0186111
7818.6118.64418.645-0.00104167-0.0339583
7918.69NANA-0.00111111NA
8018.74NANA-0.0113889NA
8118.75NANA-0.00951389NA
8218.81NANA-0.00930556NA
8318.85NANA-0.020625NA
8418.88NANA-0.016875NA


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 <- 'additive'
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')