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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 05:40:18 -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/t138684483225ppu1y4veifn6b.htm/, Retrieved Tue, 07 Dec 2021 11:10:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232242, Retrieved Tue, 07 Dec 2021 11:10:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 10:40:18] [626ac9e5ebaea65a3a0a76f5178dd51c] [Current]
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Dataseries X:
79.57
77.45
75.79
74.88
74.5
74.59
74.59
73.57
73.3
73.23
73
72.31
72.31
71.24
70.82
70.66
69.94
69.87
69.87
68.88
68.09
68.38
66.78
67.2
67.2
66.67
65.86
66.05
66.31
66.39
66.39
65.72
65.52
64.93
65.27
65.04
65.02
64.72
64.68
64.41
64.79
64.71
64.71
64.83
64.77
64.19
64.27
64.23
64.23
63.03
62.85
62.15
61.69
62.1
62.1
61.81
61.28
61.05
61.08
60.98
60.98
61.11
60.58
60.37
59.44
59.29
59.29
59.33
59.06
58.75
58.92
58.73
58.73
58.46
58.18
58.02
56.97
57.22
57.19
57.06
57.08
56.59
56.91
56.54




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=232242&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=232242&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232242&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
179.57NANA0.321823NA
277.45NANA0.017309NA
375.79NANA-0.132066NA
474.88NANA-0.122205NA
574.5NANA-0.314913NA
674.59NANA-0.0203299NA
774.5974.671574.42920.242378-0.0815451
873.5773.918673.86790.0506424-0.348559
973.373.353673.4021-0.0485243-0.053559
1073.2372.961773.0192-0.05748260.268316
117372.63372.6533-0.02032990.366997
1272.3172.350472.26670.0836979-0.0403646
1372.3172.195271.87330.3218230.114844
1471.2471.498671.48120.017309-0.258559
1570.8270.936771.0688-0.132066-0.116684
1670.6670.527470.6496-0.1222050.132622
1769.9469.873470.1883-0.3149130.0665799
1869.8769.695969.7162-0.02032990.17408
1969.8769.532869.29040.2423780.337205
2068.8868.937768.88710.0506424-0.0577257
2168.0968.441568.49-0.0485243-0.351476
2268.3868.033868.0912-0.05748260.346233
2366.7867.727667.7479-0.0203299-0.947587
2467.267.535467.45170.0836979-0.335365
2567.267.483567.16170.321823-0.28349
2666.6766.902366.8850.017309-0.232309
2765.8666.514266.6462-0.132066-0.654184
2866.0566.273266.3954-0.122205-0.223212
2966.3165.873866.1888-0.3149130.436163
3066.3966.015566.0358-0.02032990.374497
3166.3966.097465.8550.2423780.292622
3265.7265.733665.68290.0506424-0.013559
3365.5265.50465.5525-0.04852430.0160243
3464.9365.377565.435-0.0574826-0.447517
3565.2765.28365.3033-0.0203299-0.0130035
3665.0465.253765.170.0836979-0.213698
3765.0265.351865.030.321823-0.331823
3864.7264.940264.92290.017309-0.220226
3964.6864.722564.8546-0.132066-0.0425174
4064.4164.670364.7925-0.122205-0.260295
4164.7964.405164.72-0.3149130.384913
4264.7164.624364.6446-0.02032990.0857465
4364.7164.820364.57790.242378-0.110295
4464.8364.525264.47460.05064240.304774
4564.7764.279464.3279-0.04852430.490608
4664.1964.164.1575-0.05748260.0899826
4764.2763.913863.9342-0.02032990.356163
4864.2363.779963.69620.08369790.450052
4964.2363.800663.47880.3218230.429427
5063.0363.261563.24420.017309-0.231476
5162.8562.840962.9729-0.1320660.00914931
5262.1562.574562.6967-0.122205-0.424462
5361.6962.11862.4329-0.314913-0.428003
5462.162.144362.1646-0.0203299-0.0442535
5562.162.136161.89370.242378-0.0361285
5661.8161.72961.67830.05064240.0810243
5761.2861.455261.5037-0.0485243-0.175226
5861.0561.277561.335-0.0574826-0.227517
5961.0861.146861.1671-0.0203299-0.0667535
6060.9861.039960.95620.0836979-0.0599479
6160.9861.043960.72210.321823-0.0639062
6261.1160.51960.50170.0173090.591024
6360.5860.173860.3058-0.1320660.406233
6460.3759.995360.1175-0.1222050.374705
6559.4459.616859.9317-0.314913-0.176753
6659.2959.727659.7479-0.0203299-0.437587
6759.2959.802859.56040.242378-0.512795
6859.3359.406959.35620.0506424-0.0768924
6959.0659.097359.1458-0.0485243-0.037309
7058.7558.890458.9479-0.0574826-0.140434
7158.9258.726858.7471-0.02032990.193247
7258.7358.641658.55790.08369790.0883854
7358.7358.70658.38420.3218230.0240104
7458.4658.219458.20210.0173090.240608
7558.1857.892958.025-0.1320660.287066
7658.0257.730357.8525-0.1222050.289705
7756.9757.363857.6787-0.314913-0.393837
7857.2257.483457.5038-0.0203299-0.26342
7957.19NANA0.242378NA
8057.06NANA0.0506424NA
8157.08NANA-0.0485243NA
8256.59NANA-0.0574826NA
8356.91NANA-0.0203299NA
8456.54NANA0.0836979NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 79.57 & NA & NA & 0.321823 & NA \tabularnewline
2 & 77.45 & NA & NA & 0.017309 & NA \tabularnewline
3 & 75.79 & NA & NA & -0.132066 & NA \tabularnewline
4 & 74.88 & NA & NA & -0.122205 & NA \tabularnewline
5 & 74.5 & NA & NA & -0.314913 & NA \tabularnewline
6 & 74.59 & NA & NA & -0.0203299 & NA \tabularnewline
7 & 74.59 & 74.6715 & 74.4292 & 0.242378 & -0.0815451 \tabularnewline
8 & 73.57 & 73.9186 & 73.8679 & 0.0506424 & -0.348559 \tabularnewline
9 & 73.3 & 73.3536 & 73.4021 & -0.0485243 & -0.053559 \tabularnewline
10 & 73.23 & 72.9617 & 73.0192 & -0.0574826 & 0.268316 \tabularnewline
11 & 73 & 72.633 & 72.6533 & -0.0203299 & 0.366997 \tabularnewline
12 & 72.31 & 72.3504 & 72.2667 & 0.0836979 & -0.0403646 \tabularnewline
13 & 72.31 & 72.1952 & 71.8733 & 0.321823 & 0.114844 \tabularnewline
14 & 71.24 & 71.4986 & 71.4812 & 0.017309 & -0.258559 \tabularnewline
15 & 70.82 & 70.9367 & 71.0688 & -0.132066 & -0.116684 \tabularnewline
16 & 70.66 & 70.5274 & 70.6496 & -0.122205 & 0.132622 \tabularnewline
17 & 69.94 & 69.8734 & 70.1883 & -0.314913 & 0.0665799 \tabularnewline
18 & 69.87 & 69.6959 & 69.7162 & -0.0203299 & 0.17408 \tabularnewline
19 & 69.87 & 69.5328 & 69.2904 & 0.242378 & 0.337205 \tabularnewline
20 & 68.88 & 68.9377 & 68.8871 & 0.0506424 & -0.0577257 \tabularnewline
21 & 68.09 & 68.4415 & 68.49 & -0.0485243 & -0.351476 \tabularnewline
22 & 68.38 & 68.0338 & 68.0912 & -0.0574826 & 0.346233 \tabularnewline
23 & 66.78 & 67.7276 & 67.7479 & -0.0203299 & -0.947587 \tabularnewline
24 & 67.2 & 67.5354 & 67.4517 & 0.0836979 & -0.335365 \tabularnewline
25 & 67.2 & 67.4835 & 67.1617 & 0.321823 & -0.28349 \tabularnewline
26 & 66.67 & 66.9023 & 66.885 & 0.017309 & -0.232309 \tabularnewline
27 & 65.86 & 66.5142 & 66.6462 & -0.132066 & -0.654184 \tabularnewline
28 & 66.05 & 66.2732 & 66.3954 & -0.122205 & -0.223212 \tabularnewline
29 & 66.31 & 65.8738 & 66.1888 & -0.314913 & 0.436163 \tabularnewline
30 & 66.39 & 66.0155 & 66.0358 & -0.0203299 & 0.374497 \tabularnewline
31 & 66.39 & 66.0974 & 65.855 & 0.242378 & 0.292622 \tabularnewline
32 & 65.72 & 65.7336 & 65.6829 & 0.0506424 & -0.013559 \tabularnewline
33 & 65.52 & 65.504 & 65.5525 & -0.0485243 & 0.0160243 \tabularnewline
34 & 64.93 & 65.3775 & 65.435 & -0.0574826 & -0.447517 \tabularnewline
35 & 65.27 & 65.283 & 65.3033 & -0.0203299 & -0.0130035 \tabularnewline
36 & 65.04 & 65.2537 & 65.17 & 0.0836979 & -0.213698 \tabularnewline
37 & 65.02 & 65.3518 & 65.03 & 0.321823 & -0.331823 \tabularnewline
38 & 64.72 & 64.9402 & 64.9229 & 0.017309 & -0.220226 \tabularnewline
39 & 64.68 & 64.7225 & 64.8546 & -0.132066 & -0.0425174 \tabularnewline
40 & 64.41 & 64.6703 & 64.7925 & -0.122205 & -0.260295 \tabularnewline
41 & 64.79 & 64.4051 & 64.72 & -0.314913 & 0.384913 \tabularnewline
42 & 64.71 & 64.6243 & 64.6446 & -0.0203299 & 0.0857465 \tabularnewline
43 & 64.71 & 64.8203 & 64.5779 & 0.242378 & -0.110295 \tabularnewline
44 & 64.83 & 64.5252 & 64.4746 & 0.0506424 & 0.304774 \tabularnewline
45 & 64.77 & 64.2794 & 64.3279 & -0.0485243 & 0.490608 \tabularnewline
46 & 64.19 & 64.1 & 64.1575 & -0.0574826 & 0.0899826 \tabularnewline
47 & 64.27 & 63.9138 & 63.9342 & -0.0203299 & 0.356163 \tabularnewline
48 & 64.23 & 63.7799 & 63.6962 & 0.0836979 & 0.450052 \tabularnewline
49 & 64.23 & 63.8006 & 63.4788 & 0.321823 & 0.429427 \tabularnewline
50 & 63.03 & 63.2615 & 63.2442 & 0.017309 & -0.231476 \tabularnewline
51 & 62.85 & 62.8409 & 62.9729 & -0.132066 & 0.00914931 \tabularnewline
52 & 62.15 & 62.5745 & 62.6967 & -0.122205 & -0.424462 \tabularnewline
53 & 61.69 & 62.118 & 62.4329 & -0.314913 & -0.428003 \tabularnewline
54 & 62.1 & 62.1443 & 62.1646 & -0.0203299 & -0.0442535 \tabularnewline
55 & 62.1 & 62.1361 & 61.8937 & 0.242378 & -0.0361285 \tabularnewline
56 & 61.81 & 61.729 & 61.6783 & 0.0506424 & 0.0810243 \tabularnewline
57 & 61.28 & 61.4552 & 61.5037 & -0.0485243 & -0.175226 \tabularnewline
58 & 61.05 & 61.2775 & 61.335 & -0.0574826 & -0.227517 \tabularnewline
59 & 61.08 & 61.1468 & 61.1671 & -0.0203299 & -0.0667535 \tabularnewline
60 & 60.98 & 61.0399 & 60.9562 & 0.0836979 & -0.0599479 \tabularnewline
61 & 60.98 & 61.0439 & 60.7221 & 0.321823 & -0.0639062 \tabularnewline
62 & 61.11 & 60.519 & 60.5017 & 0.017309 & 0.591024 \tabularnewline
63 & 60.58 & 60.1738 & 60.3058 & -0.132066 & 0.406233 \tabularnewline
64 & 60.37 & 59.9953 & 60.1175 & -0.122205 & 0.374705 \tabularnewline
65 & 59.44 & 59.6168 & 59.9317 & -0.314913 & -0.176753 \tabularnewline
66 & 59.29 & 59.7276 & 59.7479 & -0.0203299 & -0.437587 \tabularnewline
67 & 59.29 & 59.8028 & 59.5604 & 0.242378 & -0.512795 \tabularnewline
68 & 59.33 & 59.4069 & 59.3562 & 0.0506424 & -0.0768924 \tabularnewline
69 & 59.06 & 59.0973 & 59.1458 & -0.0485243 & -0.037309 \tabularnewline
70 & 58.75 & 58.8904 & 58.9479 & -0.0574826 & -0.140434 \tabularnewline
71 & 58.92 & 58.7268 & 58.7471 & -0.0203299 & 0.193247 \tabularnewline
72 & 58.73 & 58.6416 & 58.5579 & 0.0836979 & 0.0883854 \tabularnewline
73 & 58.73 & 58.706 & 58.3842 & 0.321823 & 0.0240104 \tabularnewline
74 & 58.46 & 58.2194 & 58.2021 & 0.017309 & 0.240608 \tabularnewline
75 & 58.18 & 57.8929 & 58.025 & -0.132066 & 0.287066 \tabularnewline
76 & 58.02 & 57.7303 & 57.8525 & -0.122205 & 0.289705 \tabularnewline
77 & 56.97 & 57.3638 & 57.6787 & -0.314913 & -0.393837 \tabularnewline
78 & 57.22 & 57.4834 & 57.5038 & -0.0203299 & -0.26342 \tabularnewline
79 & 57.19 & NA & NA & 0.242378 & NA \tabularnewline
80 & 57.06 & NA & NA & 0.0506424 & NA \tabularnewline
81 & 57.08 & NA & NA & -0.0485243 & NA \tabularnewline
82 & 56.59 & NA & NA & -0.0574826 & NA \tabularnewline
83 & 56.91 & NA & NA & -0.0203299 & NA \tabularnewline
84 & 56.54 & NA & NA & 0.0836979 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232242&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]79.57[/C][C]NA[/C][C]NA[/C][C]0.321823[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]77.45[/C][C]NA[/C][C]NA[/C][C]0.017309[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]75.79[/C][C]NA[/C][C]NA[/C][C]-0.132066[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]74.88[/C][C]NA[/C][C]NA[/C][C]-0.122205[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]74.5[/C][C]NA[/C][C]NA[/C][C]-0.314913[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]74.59[/C][C]NA[/C][C]NA[/C][C]-0.0203299[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]74.59[/C][C]74.6715[/C][C]74.4292[/C][C]0.242378[/C][C]-0.0815451[/C][/ROW]
[ROW][C]8[/C][C]73.57[/C][C]73.9186[/C][C]73.8679[/C][C]0.0506424[/C][C]-0.348559[/C][/ROW]
[ROW][C]9[/C][C]73.3[/C][C]73.3536[/C][C]73.4021[/C][C]-0.0485243[/C][C]-0.053559[/C][/ROW]
[ROW][C]10[/C][C]73.23[/C][C]72.9617[/C][C]73.0192[/C][C]-0.0574826[/C][C]0.268316[/C][/ROW]
[ROW][C]11[/C][C]73[/C][C]72.633[/C][C]72.6533[/C][C]-0.0203299[/C][C]0.366997[/C][/ROW]
[ROW][C]12[/C][C]72.31[/C][C]72.3504[/C][C]72.2667[/C][C]0.0836979[/C][C]-0.0403646[/C][/ROW]
[ROW][C]13[/C][C]72.31[/C][C]72.1952[/C][C]71.8733[/C][C]0.321823[/C][C]0.114844[/C][/ROW]
[ROW][C]14[/C][C]71.24[/C][C]71.4986[/C][C]71.4812[/C][C]0.017309[/C][C]-0.258559[/C][/ROW]
[ROW][C]15[/C][C]70.82[/C][C]70.9367[/C][C]71.0688[/C][C]-0.132066[/C][C]-0.116684[/C][/ROW]
[ROW][C]16[/C][C]70.66[/C][C]70.5274[/C][C]70.6496[/C][C]-0.122205[/C][C]0.132622[/C][/ROW]
[ROW][C]17[/C][C]69.94[/C][C]69.8734[/C][C]70.1883[/C][C]-0.314913[/C][C]0.0665799[/C][/ROW]
[ROW][C]18[/C][C]69.87[/C][C]69.6959[/C][C]69.7162[/C][C]-0.0203299[/C][C]0.17408[/C][/ROW]
[ROW][C]19[/C][C]69.87[/C][C]69.5328[/C][C]69.2904[/C][C]0.242378[/C][C]0.337205[/C][/ROW]
[ROW][C]20[/C][C]68.88[/C][C]68.9377[/C][C]68.8871[/C][C]0.0506424[/C][C]-0.0577257[/C][/ROW]
[ROW][C]21[/C][C]68.09[/C][C]68.4415[/C][C]68.49[/C][C]-0.0485243[/C][C]-0.351476[/C][/ROW]
[ROW][C]22[/C][C]68.38[/C][C]68.0338[/C][C]68.0912[/C][C]-0.0574826[/C][C]0.346233[/C][/ROW]
[ROW][C]23[/C][C]66.78[/C][C]67.7276[/C][C]67.7479[/C][C]-0.0203299[/C][C]-0.947587[/C][/ROW]
[ROW][C]24[/C][C]67.2[/C][C]67.5354[/C][C]67.4517[/C][C]0.0836979[/C][C]-0.335365[/C][/ROW]
[ROW][C]25[/C][C]67.2[/C][C]67.4835[/C][C]67.1617[/C][C]0.321823[/C][C]-0.28349[/C][/ROW]
[ROW][C]26[/C][C]66.67[/C][C]66.9023[/C][C]66.885[/C][C]0.017309[/C][C]-0.232309[/C][/ROW]
[ROW][C]27[/C][C]65.86[/C][C]66.5142[/C][C]66.6462[/C][C]-0.132066[/C][C]-0.654184[/C][/ROW]
[ROW][C]28[/C][C]66.05[/C][C]66.2732[/C][C]66.3954[/C][C]-0.122205[/C][C]-0.223212[/C][/ROW]
[ROW][C]29[/C][C]66.31[/C][C]65.8738[/C][C]66.1888[/C][C]-0.314913[/C][C]0.436163[/C][/ROW]
[ROW][C]30[/C][C]66.39[/C][C]66.0155[/C][C]66.0358[/C][C]-0.0203299[/C][C]0.374497[/C][/ROW]
[ROW][C]31[/C][C]66.39[/C][C]66.0974[/C][C]65.855[/C][C]0.242378[/C][C]0.292622[/C][/ROW]
[ROW][C]32[/C][C]65.72[/C][C]65.7336[/C][C]65.6829[/C][C]0.0506424[/C][C]-0.013559[/C][/ROW]
[ROW][C]33[/C][C]65.52[/C][C]65.504[/C][C]65.5525[/C][C]-0.0485243[/C][C]0.0160243[/C][/ROW]
[ROW][C]34[/C][C]64.93[/C][C]65.3775[/C][C]65.435[/C][C]-0.0574826[/C][C]-0.447517[/C][/ROW]
[ROW][C]35[/C][C]65.27[/C][C]65.283[/C][C]65.3033[/C][C]-0.0203299[/C][C]-0.0130035[/C][/ROW]
[ROW][C]36[/C][C]65.04[/C][C]65.2537[/C][C]65.17[/C][C]0.0836979[/C][C]-0.213698[/C][/ROW]
[ROW][C]37[/C][C]65.02[/C][C]65.3518[/C][C]65.03[/C][C]0.321823[/C][C]-0.331823[/C][/ROW]
[ROW][C]38[/C][C]64.72[/C][C]64.9402[/C][C]64.9229[/C][C]0.017309[/C][C]-0.220226[/C][/ROW]
[ROW][C]39[/C][C]64.68[/C][C]64.7225[/C][C]64.8546[/C][C]-0.132066[/C][C]-0.0425174[/C][/ROW]
[ROW][C]40[/C][C]64.41[/C][C]64.6703[/C][C]64.7925[/C][C]-0.122205[/C][C]-0.260295[/C][/ROW]
[ROW][C]41[/C][C]64.79[/C][C]64.4051[/C][C]64.72[/C][C]-0.314913[/C][C]0.384913[/C][/ROW]
[ROW][C]42[/C][C]64.71[/C][C]64.6243[/C][C]64.6446[/C][C]-0.0203299[/C][C]0.0857465[/C][/ROW]
[ROW][C]43[/C][C]64.71[/C][C]64.8203[/C][C]64.5779[/C][C]0.242378[/C][C]-0.110295[/C][/ROW]
[ROW][C]44[/C][C]64.83[/C][C]64.5252[/C][C]64.4746[/C][C]0.0506424[/C][C]0.304774[/C][/ROW]
[ROW][C]45[/C][C]64.77[/C][C]64.2794[/C][C]64.3279[/C][C]-0.0485243[/C][C]0.490608[/C][/ROW]
[ROW][C]46[/C][C]64.19[/C][C]64.1[/C][C]64.1575[/C][C]-0.0574826[/C][C]0.0899826[/C][/ROW]
[ROW][C]47[/C][C]64.27[/C][C]63.9138[/C][C]63.9342[/C][C]-0.0203299[/C][C]0.356163[/C][/ROW]
[ROW][C]48[/C][C]64.23[/C][C]63.7799[/C][C]63.6962[/C][C]0.0836979[/C][C]0.450052[/C][/ROW]
[ROW][C]49[/C][C]64.23[/C][C]63.8006[/C][C]63.4788[/C][C]0.321823[/C][C]0.429427[/C][/ROW]
[ROW][C]50[/C][C]63.03[/C][C]63.2615[/C][C]63.2442[/C][C]0.017309[/C][C]-0.231476[/C][/ROW]
[ROW][C]51[/C][C]62.85[/C][C]62.8409[/C][C]62.9729[/C][C]-0.132066[/C][C]0.00914931[/C][/ROW]
[ROW][C]52[/C][C]62.15[/C][C]62.5745[/C][C]62.6967[/C][C]-0.122205[/C][C]-0.424462[/C][/ROW]
[ROW][C]53[/C][C]61.69[/C][C]62.118[/C][C]62.4329[/C][C]-0.314913[/C][C]-0.428003[/C][/ROW]
[ROW][C]54[/C][C]62.1[/C][C]62.1443[/C][C]62.1646[/C][C]-0.0203299[/C][C]-0.0442535[/C][/ROW]
[ROW][C]55[/C][C]62.1[/C][C]62.1361[/C][C]61.8937[/C][C]0.242378[/C][C]-0.0361285[/C][/ROW]
[ROW][C]56[/C][C]61.81[/C][C]61.729[/C][C]61.6783[/C][C]0.0506424[/C][C]0.0810243[/C][/ROW]
[ROW][C]57[/C][C]61.28[/C][C]61.4552[/C][C]61.5037[/C][C]-0.0485243[/C][C]-0.175226[/C][/ROW]
[ROW][C]58[/C][C]61.05[/C][C]61.2775[/C][C]61.335[/C][C]-0.0574826[/C][C]-0.227517[/C][/ROW]
[ROW][C]59[/C][C]61.08[/C][C]61.1468[/C][C]61.1671[/C][C]-0.0203299[/C][C]-0.0667535[/C][/ROW]
[ROW][C]60[/C][C]60.98[/C][C]61.0399[/C][C]60.9562[/C][C]0.0836979[/C][C]-0.0599479[/C][/ROW]
[ROW][C]61[/C][C]60.98[/C][C]61.0439[/C][C]60.7221[/C][C]0.321823[/C][C]-0.0639062[/C][/ROW]
[ROW][C]62[/C][C]61.11[/C][C]60.519[/C][C]60.5017[/C][C]0.017309[/C][C]0.591024[/C][/ROW]
[ROW][C]63[/C][C]60.58[/C][C]60.1738[/C][C]60.3058[/C][C]-0.132066[/C][C]0.406233[/C][/ROW]
[ROW][C]64[/C][C]60.37[/C][C]59.9953[/C][C]60.1175[/C][C]-0.122205[/C][C]0.374705[/C][/ROW]
[ROW][C]65[/C][C]59.44[/C][C]59.6168[/C][C]59.9317[/C][C]-0.314913[/C][C]-0.176753[/C][/ROW]
[ROW][C]66[/C][C]59.29[/C][C]59.7276[/C][C]59.7479[/C][C]-0.0203299[/C][C]-0.437587[/C][/ROW]
[ROW][C]67[/C][C]59.29[/C][C]59.8028[/C][C]59.5604[/C][C]0.242378[/C][C]-0.512795[/C][/ROW]
[ROW][C]68[/C][C]59.33[/C][C]59.4069[/C][C]59.3562[/C][C]0.0506424[/C][C]-0.0768924[/C][/ROW]
[ROW][C]69[/C][C]59.06[/C][C]59.0973[/C][C]59.1458[/C][C]-0.0485243[/C][C]-0.037309[/C][/ROW]
[ROW][C]70[/C][C]58.75[/C][C]58.8904[/C][C]58.9479[/C][C]-0.0574826[/C][C]-0.140434[/C][/ROW]
[ROW][C]71[/C][C]58.92[/C][C]58.7268[/C][C]58.7471[/C][C]-0.0203299[/C][C]0.193247[/C][/ROW]
[ROW][C]72[/C][C]58.73[/C][C]58.6416[/C][C]58.5579[/C][C]0.0836979[/C][C]0.0883854[/C][/ROW]
[ROW][C]73[/C][C]58.73[/C][C]58.706[/C][C]58.3842[/C][C]0.321823[/C][C]0.0240104[/C][/ROW]
[ROW][C]74[/C][C]58.46[/C][C]58.2194[/C][C]58.2021[/C][C]0.017309[/C][C]0.240608[/C][/ROW]
[ROW][C]75[/C][C]58.18[/C][C]57.8929[/C][C]58.025[/C][C]-0.132066[/C][C]0.287066[/C][/ROW]
[ROW][C]76[/C][C]58.02[/C][C]57.7303[/C][C]57.8525[/C][C]-0.122205[/C][C]0.289705[/C][/ROW]
[ROW][C]77[/C][C]56.97[/C][C]57.3638[/C][C]57.6787[/C][C]-0.314913[/C][C]-0.393837[/C][/ROW]
[ROW][C]78[/C][C]57.22[/C][C]57.4834[/C][C]57.5038[/C][C]-0.0203299[/C][C]-0.26342[/C][/ROW]
[ROW][C]79[/C][C]57.19[/C][C]NA[/C][C]NA[/C][C]0.242378[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]57.06[/C][C]NA[/C][C]NA[/C][C]0.0506424[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]57.08[/C][C]NA[/C][C]NA[/C][C]-0.0485243[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]56.59[/C][C]NA[/C][C]NA[/C][C]-0.0574826[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]56.91[/C][C]NA[/C][C]NA[/C][C]-0.0203299[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]56.54[/C][C]NA[/C][C]NA[/C][C]0.0836979[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232242&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232242&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
179.57NANA0.321823NA
277.45NANA0.017309NA
375.79NANA-0.132066NA
474.88NANA-0.122205NA
574.5NANA-0.314913NA
674.59NANA-0.0203299NA
774.5974.671574.42920.242378-0.0815451
873.5773.918673.86790.0506424-0.348559
973.373.353673.4021-0.0485243-0.053559
1073.2372.961773.0192-0.05748260.268316
117372.63372.6533-0.02032990.366997
1272.3172.350472.26670.0836979-0.0403646
1372.3172.195271.87330.3218230.114844
1471.2471.498671.48120.017309-0.258559
1570.8270.936771.0688-0.132066-0.116684
1670.6670.527470.6496-0.1222050.132622
1769.9469.873470.1883-0.3149130.0665799
1869.8769.695969.7162-0.02032990.17408
1969.8769.532869.29040.2423780.337205
2068.8868.937768.88710.0506424-0.0577257
2168.0968.441568.49-0.0485243-0.351476
2268.3868.033868.0912-0.05748260.346233
2366.7867.727667.7479-0.0203299-0.947587
2467.267.535467.45170.0836979-0.335365
2567.267.483567.16170.321823-0.28349
2666.6766.902366.8850.017309-0.232309
2765.8666.514266.6462-0.132066-0.654184
2866.0566.273266.3954-0.122205-0.223212
2966.3165.873866.1888-0.3149130.436163
3066.3966.015566.0358-0.02032990.374497
3166.3966.097465.8550.2423780.292622
3265.7265.733665.68290.0506424-0.013559
3365.5265.50465.5525-0.04852430.0160243
3464.9365.377565.435-0.0574826-0.447517
3565.2765.28365.3033-0.0203299-0.0130035
3665.0465.253765.170.0836979-0.213698
3765.0265.351865.030.321823-0.331823
3864.7264.940264.92290.017309-0.220226
3964.6864.722564.8546-0.132066-0.0425174
4064.4164.670364.7925-0.122205-0.260295
4164.7964.405164.72-0.3149130.384913
4264.7164.624364.6446-0.02032990.0857465
4364.7164.820364.57790.242378-0.110295
4464.8364.525264.47460.05064240.304774
4564.7764.279464.3279-0.04852430.490608
4664.1964.164.1575-0.05748260.0899826
4764.2763.913863.9342-0.02032990.356163
4864.2363.779963.69620.08369790.450052
4964.2363.800663.47880.3218230.429427
5063.0363.261563.24420.017309-0.231476
5162.8562.840962.9729-0.1320660.00914931
5262.1562.574562.6967-0.122205-0.424462
5361.6962.11862.4329-0.314913-0.428003
5462.162.144362.1646-0.0203299-0.0442535
5562.162.136161.89370.242378-0.0361285
5661.8161.72961.67830.05064240.0810243
5761.2861.455261.5037-0.0485243-0.175226
5861.0561.277561.335-0.0574826-0.227517
5961.0861.146861.1671-0.0203299-0.0667535
6060.9861.039960.95620.0836979-0.0599479
6160.9861.043960.72210.321823-0.0639062
6261.1160.51960.50170.0173090.591024
6360.5860.173860.3058-0.1320660.406233
6460.3759.995360.1175-0.1222050.374705
6559.4459.616859.9317-0.314913-0.176753
6659.2959.727659.7479-0.0203299-0.437587
6759.2959.802859.56040.242378-0.512795
6859.3359.406959.35620.0506424-0.0768924
6959.0659.097359.1458-0.0485243-0.037309
7058.7558.890458.9479-0.0574826-0.140434
7158.9258.726858.7471-0.02032990.193247
7258.7358.641658.55790.08369790.0883854
7358.7358.70658.38420.3218230.0240104
7458.4658.219458.20210.0173090.240608
7558.1857.892958.025-0.1320660.287066
7658.0257.730357.8525-0.1222050.289705
7756.9757.363857.6787-0.314913-0.393837
7857.2257.483457.5038-0.0203299-0.26342
7957.19NANA0.242378NA
8057.06NANA0.0506424NA
8157.08NANA-0.0485243NA
8256.59NANA-0.0574826NA
8356.91NANA-0.0203299NA
8456.54NANA0.0836979NA



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')