Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationMon, 28 Nov 2016 09:34:24 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Nov/28/t1480325680rrteb08kv9l4jh8.htm/, Retrieved Sat, 04 May 2024 09:05:01 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 09:05:01 +0200
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact0
Dataseries X:
99,57
98,97
99
98,88
98,9
98,92
98,8
98,83
98,88
98,88
98,89
98,89
99,05
99,2
99,13
98,92
98,98
98,99
99,08
99,1
99,1
99,06
99,05
99,11
99,75
99,8
99,95
99,69
99,55
99,14
99,05
99
99,03
99,16
99,01
99
99,9
100,18
100,2
100,13
99,85
99,88
99,88
99,89
99,96
100,05
100,04
100,06
99,72
99,7
99,63
99,73
99,77
99,76
99,61
99,61
99,59
99,42
99,52
99,46
100,55
100,4
100,15
100,2
100,16
100,19
100,23
100,08
100,15
100,13
100,26
100,24




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

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

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
199.57NANA0.262479NA
298.97NANA0.302146NA
399NANA0.237146NA
498.88NANA0.138146NA
598.9NANA0.0443125NA
698.92NANA-0.0483542NA
798.898.808998.9292-0.120271-0.00889583
898.8398.778798.9171-0.1383540.0512708
998.8898.798298.9321-0.1338540.0817708
1098.8898.786798.9392-0.1524380.0932708
1198.8998.758298.9442-0.1859370.131771
1298.8998.745498.9504-0.2050210.144604
1399.0599.227598.9650.262479-0.177479
1499.299.290198.98790.302146-0.0900625
1599.1399.245599.00830.237146-0.115479
1698.9299.163199.0250.138146-0.243146
1798.9899.083599.03920.0443125-0.103479
1898.9999.006699.055-0.0483542-0.0166458
1999.0898.973199.0933-0.1202710.106938
2099.199.009199.1475-0.1383540.0908542
2199.199.072899.2067-0.1338540.0271875
2299.0699.120599.2729-0.152438-0.0604792
2399.0599.142899.3287-0.185937-0.0928125
2499.1199.153799.3587-0.205021-0.0437292
2599.7599.626299.36370.2624790.123771
2699.899.660599.35830.3021460.139521
2799.9599.588499.35120.2371460.361604
2899.6999.490699.35250.1381460.199354
2999.5599.399399.3550.04431250.150688
3099.1499.300499.3488-0.0483542-0.160396
3199.0599.230199.3504-0.120271-0.180146
329999.234199.3725-0.138354-0.234146
3399.0399.264999.3988-0.133854-0.234896
3499.1699.275199.4275-0.152438-0.115062
3599.0199.272499.4583-0.185937-0.262396
369999.296699.5017-0.205021-0.296646
3799.999.829699.56710.2624790.0704375
38100.1899.940999.63880.3021460.239104
39100.299.951799.71460.2371460.248271
40100.1399.928699.79040.1381460.201437
4199.8599.914799.87040.0443125-0.0647292
4299.8899.909199.9575-0.0483542-0.0291458
4399.8899.873999.9942-0.1202710.00610417
4499.8999.828399.9667-0.1383540.0616875
4599.9699.789199.9229-0.1338540.170937
46100.0599.730199.8825-0.1524380.319937
47100.0499.676699.8625-0.1859370.363438
48100.0699.649199.8542-0.2050210.410854
4999.72100.199.83790.262479-0.380396
5099.7100.11799.8150.302146-0.417146
5199.63100.02599.78790.237146-0.395062
5299.7399.884499.74630.138146-0.154396
5399.7799.742699.69830.04431250.0273542
5499.7699.603399.6517-0.04835420.156688
5599.6199.54199.6612-0.1202710.0690208
5699.6199.586699.725-0.1383540.0233542
5799.5999.64299.7758-0.133854-0.0519792
5899.4299.664699.8171-0.152438-0.244646
5999.5299.66799.8529-0.185937-0.146979
6099.4699.682199.8871-0.205021-0.222062
61100.55100.19399.93080.2624790.356688
62100.4100.27899.97620.3021460.121604
63100.15100.256100.0190.237146-0.106312
64100.2100.21100.0720.138146-0.0102292
65100.16100.177100.1320.0443125-0.0168125
66100.19100.147100.196-0.04835420.0425208
67100.23NANA-0.120271NA
68100.08NANA-0.138354NA
69100.15NANA-0.133854NA
70100.13NANA-0.152438NA
71100.26NANA-0.185937NA
72100.24NANA-0.205021NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 99.57 & NA & NA & 0.262479 & NA \tabularnewline
2 & 98.97 & NA & NA & 0.302146 & NA \tabularnewline
3 & 99 & NA & NA & 0.237146 & NA \tabularnewline
4 & 98.88 & NA & NA & 0.138146 & NA \tabularnewline
5 & 98.9 & NA & NA & 0.0443125 & NA \tabularnewline
6 & 98.92 & NA & NA & -0.0483542 & NA \tabularnewline
7 & 98.8 & 98.8089 & 98.9292 & -0.120271 & -0.00889583 \tabularnewline
8 & 98.83 & 98.7787 & 98.9171 & -0.138354 & 0.0512708 \tabularnewline
9 & 98.88 & 98.7982 & 98.9321 & -0.133854 & 0.0817708 \tabularnewline
10 & 98.88 & 98.7867 & 98.9392 & -0.152438 & 0.0932708 \tabularnewline
11 & 98.89 & 98.7582 & 98.9442 & -0.185937 & 0.131771 \tabularnewline
12 & 98.89 & 98.7454 & 98.9504 & -0.205021 & 0.144604 \tabularnewline
13 & 99.05 & 99.2275 & 98.965 & 0.262479 & -0.177479 \tabularnewline
14 & 99.2 & 99.2901 & 98.9879 & 0.302146 & -0.0900625 \tabularnewline
15 & 99.13 & 99.2455 & 99.0083 & 0.237146 & -0.115479 \tabularnewline
16 & 98.92 & 99.1631 & 99.025 & 0.138146 & -0.243146 \tabularnewline
17 & 98.98 & 99.0835 & 99.0392 & 0.0443125 & -0.103479 \tabularnewline
18 & 98.99 & 99.0066 & 99.055 & -0.0483542 & -0.0166458 \tabularnewline
19 & 99.08 & 98.9731 & 99.0933 & -0.120271 & 0.106938 \tabularnewline
20 & 99.1 & 99.0091 & 99.1475 & -0.138354 & 0.0908542 \tabularnewline
21 & 99.1 & 99.0728 & 99.2067 & -0.133854 & 0.0271875 \tabularnewline
22 & 99.06 & 99.1205 & 99.2729 & -0.152438 & -0.0604792 \tabularnewline
23 & 99.05 & 99.1428 & 99.3287 & -0.185937 & -0.0928125 \tabularnewline
24 & 99.11 & 99.1537 & 99.3587 & -0.205021 & -0.0437292 \tabularnewline
25 & 99.75 & 99.6262 & 99.3637 & 0.262479 & 0.123771 \tabularnewline
26 & 99.8 & 99.6605 & 99.3583 & 0.302146 & 0.139521 \tabularnewline
27 & 99.95 & 99.5884 & 99.3512 & 0.237146 & 0.361604 \tabularnewline
28 & 99.69 & 99.4906 & 99.3525 & 0.138146 & 0.199354 \tabularnewline
29 & 99.55 & 99.3993 & 99.355 & 0.0443125 & 0.150688 \tabularnewline
30 & 99.14 & 99.3004 & 99.3488 & -0.0483542 & -0.160396 \tabularnewline
31 & 99.05 & 99.2301 & 99.3504 & -0.120271 & -0.180146 \tabularnewline
32 & 99 & 99.2341 & 99.3725 & -0.138354 & -0.234146 \tabularnewline
33 & 99.03 & 99.2649 & 99.3988 & -0.133854 & -0.234896 \tabularnewline
34 & 99.16 & 99.2751 & 99.4275 & -0.152438 & -0.115062 \tabularnewline
35 & 99.01 & 99.2724 & 99.4583 & -0.185937 & -0.262396 \tabularnewline
36 & 99 & 99.2966 & 99.5017 & -0.205021 & -0.296646 \tabularnewline
37 & 99.9 & 99.8296 & 99.5671 & 0.262479 & 0.0704375 \tabularnewline
38 & 100.18 & 99.9409 & 99.6388 & 0.302146 & 0.239104 \tabularnewline
39 & 100.2 & 99.9517 & 99.7146 & 0.237146 & 0.248271 \tabularnewline
40 & 100.13 & 99.9286 & 99.7904 & 0.138146 & 0.201437 \tabularnewline
41 & 99.85 & 99.9147 & 99.8704 & 0.0443125 & -0.0647292 \tabularnewline
42 & 99.88 & 99.9091 & 99.9575 & -0.0483542 & -0.0291458 \tabularnewline
43 & 99.88 & 99.8739 & 99.9942 & -0.120271 & 0.00610417 \tabularnewline
44 & 99.89 & 99.8283 & 99.9667 & -0.138354 & 0.0616875 \tabularnewline
45 & 99.96 & 99.7891 & 99.9229 & -0.133854 & 0.170937 \tabularnewline
46 & 100.05 & 99.7301 & 99.8825 & -0.152438 & 0.319937 \tabularnewline
47 & 100.04 & 99.6766 & 99.8625 & -0.185937 & 0.363438 \tabularnewline
48 & 100.06 & 99.6491 & 99.8542 & -0.205021 & 0.410854 \tabularnewline
49 & 99.72 & 100.1 & 99.8379 & 0.262479 & -0.380396 \tabularnewline
50 & 99.7 & 100.117 & 99.815 & 0.302146 & -0.417146 \tabularnewline
51 & 99.63 & 100.025 & 99.7879 & 0.237146 & -0.395062 \tabularnewline
52 & 99.73 & 99.8844 & 99.7463 & 0.138146 & -0.154396 \tabularnewline
53 & 99.77 & 99.7426 & 99.6983 & 0.0443125 & 0.0273542 \tabularnewline
54 & 99.76 & 99.6033 & 99.6517 & -0.0483542 & 0.156688 \tabularnewline
55 & 99.61 & 99.541 & 99.6612 & -0.120271 & 0.0690208 \tabularnewline
56 & 99.61 & 99.5866 & 99.725 & -0.138354 & 0.0233542 \tabularnewline
57 & 99.59 & 99.642 & 99.7758 & -0.133854 & -0.0519792 \tabularnewline
58 & 99.42 & 99.6646 & 99.8171 & -0.152438 & -0.244646 \tabularnewline
59 & 99.52 & 99.667 & 99.8529 & -0.185937 & -0.146979 \tabularnewline
60 & 99.46 & 99.6821 & 99.8871 & -0.205021 & -0.222062 \tabularnewline
61 & 100.55 & 100.193 & 99.9308 & 0.262479 & 0.356688 \tabularnewline
62 & 100.4 & 100.278 & 99.9762 & 0.302146 & 0.121604 \tabularnewline
63 & 100.15 & 100.256 & 100.019 & 0.237146 & -0.106312 \tabularnewline
64 & 100.2 & 100.21 & 100.072 & 0.138146 & -0.0102292 \tabularnewline
65 & 100.16 & 100.177 & 100.132 & 0.0443125 & -0.0168125 \tabularnewline
66 & 100.19 & 100.147 & 100.196 & -0.0483542 & 0.0425208 \tabularnewline
67 & 100.23 & NA & NA & -0.120271 & NA \tabularnewline
68 & 100.08 & NA & NA & -0.138354 & NA \tabularnewline
69 & 100.15 & NA & NA & -0.133854 & NA \tabularnewline
70 & 100.13 & NA & NA & -0.152438 & NA \tabularnewline
71 & 100.26 & NA & NA & -0.185937 & NA \tabularnewline
72 & 100.24 & NA & NA & -0.205021 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]99.57[/C][C]NA[/C][C]NA[/C][C]0.262479[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.97[/C][C]NA[/C][C]NA[/C][C]0.302146[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99[/C][C]NA[/C][C]NA[/C][C]0.237146[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]98.88[/C][C]NA[/C][C]NA[/C][C]0.138146[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98.9[/C][C]NA[/C][C]NA[/C][C]0.0443125[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]98.92[/C][C]NA[/C][C]NA[/C][C]-0.0483542[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]98.8[/C][C]98.8089[/C][C]98.9292[/C][C]-0.120271[/C][C]-0.00889583[/C][/ROW]
[ROW][C]8[/C][C]98.83[/C][C]98.7787[/C][C]98.9171[/C][C]-0.138354[/C][C]0.0512708[/C][/ROW]
[ROW][C]9[/C][C]98.88[/C][C]98.7982[/C][C]98.9321[/C][C]-0.133854[/C][C]0.0817708[/C][/ROW]
[ROW][C]10[/C][C]98.88[/C][C]98.7867[/C][C]98.9392[/C][C]-0.152438[/C][C]0.0932708[/C][/ROW]
[ROW][C]11[/C][C]98.89[/C][C]98.7582[/C][C]98.9442[/C][C]-0.185937[/C][C]0.131771[/C][/ROW]
[ROW][C]12[/C][C]98.89[/C][C]98.7454[/C][C]98.9504[/C][C]-0.205021[/C][C]0.144604[/C][/ROW]
[ROW][C]13[/C][C]99.05[/C][C]99.2275[/C][C]98.965[/C][C]0.262479[/C][C]-0.177479[/C][/ROW]
[ROW][C]14[/C][C]99.2[/C][C]99.2901[/C][C]98.9879[/C][C]0.302146[/C][C]-0.0900625[/C][/ROW]
[ROW][C]15[/C][C]99.13[/C][C]99.2455[/C][C]99.0083[/C][C]0.237146[/C][C]-0.115479[/C][/ROW]
[ROW][C]16[/C][C]98.92[/C][C]99.1631[/C][C]99.025[/C][C]0.138146[/C][C]-0.243146[/C][/ROW]
[ROW][C]17[/C][C]98.98[/C][C]99.0835[/C][C]99.0392[/C][C]0.0443125[/C][C]-0.103479[/C][/ROW]
[ROW][C]18[/C][C]98.99[/C][C]99.0066[/C][C]99.055[/C][C]-0.0483542[/C][C]-0.0166458[/C][/ROW]
[ROW][C]19[/C][C]99.08[/C][C]98.9731[/C][C]99.0933[/C][C]-0.120271[/C][C]0.106938[/C][/ROW]
[ROW][C]20[/C][C]99.1[/C][C]99.0091[/C][C]99.1475[/C][C]-0.138354[/C][C]0.0908542[/C][/ROW]
[ROW][C]21[/C][C]99.1[/C][C]99.0728[/C][C]99.2067[/C][C]-0.133854[/C][C]0.0271875[/C][/ROW]
[ROW][C]22[/C][C]99.06[/C][C]99.1205[/C][C]99.2729[/C][C]-0.152438[/C][C]-0.0604792[/C][/ROW]
[ROW][C]23[/C][C]99.05[/C][C]99.1428[/C][C]99.3287[/C][C]-0.185937[/C][C]-0.0928125[/C][/ROW]
[ROW][C]24[/C][C]99.11[/C][C]99.1537[/C][C]99.3587[/C][C]-0.205021[/C][C]-0.0437292[/C][/ROW]
[ROW][C]25[/C][C]99.75[/C][C]99.6262[/C][C]99.3637[/C][C]0.262479[/C][C]0.123771[/C][/ROW]
[ROW][C]26[/C][C]99.8[/C][C]99.6605[/C][C]99.3583[/C][C]0.302146[/C][C]0.139521[/C][/ROW]
[ROW][C]27[/C][C]99.95[/C][C]99.5884[/C][C]99.3512[/C][C]0.237146[/C][C]0.361604[/C][/ROW]
[ROW][C]28[/C][C]99.69[/C][C]99.4906[/C][C]99.3525[/C][C]0.138146[/C][C]0.199354[/C][/ROW]
[ROW][C]29[/C][C]99.55[/C][C]99.3993[/C][C]99.355[/C][C]0.0443125[/C][C]0.150688[/C][/ROW]
[ROW][C]30[/C][C]99.14[/C][C]99.3004[/C][C]99.3488[/C][C]-0.0483542[/C][C]-0.160396[/C][/ROW]
[ROW][C]31[/C][C]99.05[/C][C]99.2301[/C][C]99.3504[/C][C]-0.120271[/C][C]-0.180146[/C][/ROW]
[ROW][C]32[/C][C]99[/C][C]99.2341[/C][C]99.3725[/C][C]-0.138354[/C][C]-0.234146[/C][/ROW]
[ROW][C]33[/C][C]99.03[/C][C]99.2649[/C][C]99.3988[/C][C]-0.133854[/C][C]-0.234896[/C][/ROW]
[ROW][C]34[/C][C]99.16[/C][C]99.2751[/C][C]99.4275[/C][C]-0.152438[/C][C]-0.115062[/C][/ROW]
[ROW][C]35[/C][C]99.01[/C][C]99.2724[/C][C]99.4583[/C][C]-0.185937[/C][C]-0.262396[/C][/ROW]
[ROW][C]36[/C][C]99[/C][C]99.2966[/C][C]99.5017[/C][C]-0.205021[/C][C]-0.296646[/C][/ROW]
[ROW][C]37[/C][C]99.9[/C][C]99.8296[/C][C]99.5671[/C][C]0.262479[/C][C]0.0704375[/C][/ROW]
[ROW][C]38[/C][C]100.18[/C][C]99.9409[/C][C]99.6388[/C][C]0.302146[/C][C]0.239104[/C][/ROW]
[ROW][C]39[/C][C]100.2[/C][C]99.9517[/C][C]99.7146[/C][C]0.237146[/C][C]0.248271[/C][/ROW]
[ROW][C]40[/C][C]100.13[/C][C]99.9286[/C][C]99.7904[/C][C]0.138146[/C][C]0.201437[/C][/ROW]
[ROW][C]41[/C][C]99.85[/C][C]99.9147[/C][C]99.8704[/C][C]0.0443125[/C][C]-0.0647292[/C][/ROW]
[ROW][C]42[/C][C]99.88[/C][C]99.9091[/C][C]99.9575[/C][C]-0.0483542[/C][C]-0.0291458[/C][/ROW]
[ROW][C]43[/C][C]99.88[/C][C]99.8739[/C][C]99.9942[/C][C]-0.120271[/C][C]0.00610417[/C][/ROW]
[ROW][C]44[/C][C]99.89[/C][C]99.8283[/C][C]99.9667[/C][C]-0.138354[/C][C]0.0616875[/C][/ROW]
[ROW][C]45[/C][C]99.96[/C][C]99.7891[/C][C]99.9229[/C][C]-0.133854[/C][C]0.170937[/C][/ROW]
[ROW][C]46[/C][C]100.05[/C][C]99.7301[/C][C]99.8825[/C][C]-0.152438[/C][C]0.319937[/C][/ROW]
[ROW][C]47[/C][C]100.04[/C][C]99.6766[/C][C]99.8625[/C][C]-0.185937[/C][C]0.363438[/C][/ROW]
[ROW][C]48[/C][C]100.06[/C][C]99.6491[/C][C]99.8542[/C][C]-0.205021[/C][C]0.410854[/C][/ROW]
[ROW][C]49[/C][C]99.72[/C][C]100.1[/C][C]99.8379[/C][C]0.262479[/C][C]-0.380396[/C][/ROW]
[ROW][C]50[/C][C]99.7[/C][C]100.117[/C][C]99.815[/C][C]0.302146[/C][C]-0.417146[/C][/ROW]
[ROW][C]51[/C][C]99.63[/C][C]100.025[/C][C]99.7879[/C][C]0.237146[/C][C]-0.395062[/C][/ROW]
[ROW][C]52[/C][C]99.73[/C][C]99.8844[/C][C]99.7463[/C][C]0.138146[/C][C]-0.154396[/C][/ROW]
[ROW][C]53[/C][C]99.77[/C][C]99.7426[/C][C]99.6983[/C][C]0.0443125[/C][C]0.0273542[/C][/ROW]
[ROW][C]54[/C][C]99.76[/C][C]99.6033[/C][C]99.6517[/C][C]-0.0483542[/C][C]0.156688[/C][/ROW]
[ROW][C]55[/C][C]99.61[/C][C]99.541[/C][C]99.6612[/C][C]-0.120271[/C][C]0.0690208[/C][/ROW]
[ROW][C]56[/C][C]99.61[/C][C]99.5866[/C][C]99.725[/C][C]-0.138354[/C][C]0.0233542[/C][/ROW]
[ROW][C]57[/C][C]99.59[/C][C]99.642[/C][C]99.7758[/C][C]-0.133854[/C][C]-0.0519792[/C][/ROW]
[ROW][C]58[/C][C]99.42[/C][C]99.6646[/C][C]99.8171[/C][C]-0.152438[/C][C]-0.244646[/C][/ROW]
[ROW][C]59[/C][C]99.52[/C][C]99.667[/C][C]99.8529[/C][C]-0.185937[/C][C]-0.146979[/C][/ROW]
[ROW][C]60[/C][C]99.46[/C][C]99.6821[/C][C]99.8871[/C][C]-0.205021[/C][C]-0.222062[/C][/ROW]
[ROW][C]61[/C][C]100.55[/C][C]100.193[/C][C]99.9308[/C][C]0.262479[/C][C]0.356688[/C][/ROW]
[ROW][C]62[/C][C]100.4[/C][C]100.278[/C][C]99.9762[/C][C]0.302146[/C][C]0.121604[/C][/ROW]
[ROW][C]63[/C][C]100.15[/C][C]100.256[/C][C]100.019[/C][C]0.237146[/C][C]-0.106312[/C][/ROW]
[ROW][C]64[/C][C]100.2[/C][C]100.21[/C][C]100.072[/C][C]0.138146[/C][C]-0.0102292[/C][/ROW]
[ROW][C]65[/C][C]100.16[/C][C]100.177[/C][C]100.132[/C][C]0.0443125[/C][C]-0.0168125[/C][/ROW]
[ROW][C]66[/C][C]100.19[/C][C]100.147[/C][C]100.196[/C][C]-0.0483542[/C][C]0.0425208[/C][/ROW]
[ROW][C]67[/C][C]100.23[/C][C]NA[/C][C]NA[/C][C]-0.120271[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]100.08[/C][C]NA[/C][C]NA[/C][C]-0.138354[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.15[/C][C]NA[/C][C]NA[/C][C]-0.133854[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]100.13[/C][C]NA[/C][C]NA[/C][C]-0.152438[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]100.26[/C][C]NA[/C][C]NA[/C][C]-0.185937[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]100.24[/C][C]NA[/C][C]NA[/C][C]-0.205021[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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
199.57NANA0.262479NA
298.97NANA0.302146NA
399NANA0.237146NA
498.88NANA0.138146NA
598.9NANA0.0443125NA
698.92NANA-0.0483542NA
798.898.808998.9292-0.120271-0.00889583
898.8398.778798.9171-0.1383540.0512708
998.8898.798298.9321-0.1338540.0817708
1098.8898.786798.9392-0.1524380.0932708
1198.8998.758298.9442-0.1859370.131771
1298.8998.745498.9504-0.2050210.144604
1399.0599.227598.9650.262479-0.177479
1499.299.290198.98790.302146-0.0900625
1599.1399.245599.00830.237146-0.115479
1698.9299.163199.0250.138146-0.243146
1798.9899.083599.03920.0443125-0.103479
1898.9999.006699.055-0.0483542-0.0166458
1999.0898.973199.0933-0.1202710.106938
2099.199.009199.1475-0.1383540.0908542
2199.199.072899.2067-0.1338540.0271875
2299.0699.120599.2729-0.152438-0.0604792
2399.0599.142899.3287-0.185937-0.0928125
2499.1199.153799.3587-0.205021-0.0437292
2599.7599.626299.36370.2624790.123771
2699.899.660599.35830.3021460.139521
2799.9599.588499.35120.2371460.361604
2899.6999.490699.35250.1381460.199354
2999.5599.399399.3550.04431250.150688
3099.1499.300499.3488-0.0483542-0.160396
3199.0599.230199.3504-0.120271-0.180146
329999.234199.3725-0.138354-0.234146
3399.0399.264999.3988-0.133854-0.234896
3499.1699.275199.4275-0.152438-0.115062
3599.0199.272499.4583-0.185937-0.262396
369999.296699.5017-0.205021-0.296646
3799.999.829699.56710.2624790.0704375
38100.1899.940999.63880.3021460.239104
39100.299.951799.71460.2371460.248271
40100.1399.928699.79040.1381460.201437
4199.8599.914799.87040.0443125-0.0647292
4299.8899.909199.9575-0.0483542-0.0291458
4399.8899.873999.9942-0.1202710.00610417
4499.8999.828399.9667-0.1383540.0616875
4599.9699.789199.9229-0.1338540.170937
46100.0599.730199.8825-0.1524380.319937
47100.0499.676699.8625-0.1859370.363438
48100.0699.649199.8542-0.2050210.410854
4999.72100.199.83790.262479-0.380396
5099.7100.11799.8150.302146-0.417146
5199.63100.02599.78790.237146-0.395062
5299.7399.884499.74630.138146-0.154396
5399.7799.742699.69830.04431250.0273542
5499.7699.603399.6517-0.04835420.156688
5599.6199.54199.6612-0.1202710.0690208
5699.6199.586699.725-0.1383540.0233542
5799.5999.64299.7758-0.133854-0.0519792
5899.4299.664699.8171-0.152438-0.244646
5999.5299.66799.8529-0.185937-0.146979
6099.4699.682199.8871-0.205021-0.222062
61100.55100.19399.93080.2624790.356688
62100.4100.27899.97620.3021460.121604
63100.15100.256100.0190.237146-0.106312
64100.2100.21100.0720.138146-0.0102292
65100.16100.177100.1320.0443125-0.0168125
66100.19100.147100.196-0.04835420.0425208
67100.23NANA-0.120271NA
68100.08NANA-0.138354NA
69100.15NANA-0.133854NA
70100.13NANA-0.152438NA
71100.26NANA-0.185937NA
72100.24NANA-0.205021NA



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')