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Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 04 Dec 2013 04:08:11 -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/t1386148109juxs1pen4jxzxb3.htm/, Retrieved Fri, 29 Mar 2024 09:34:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230449, Retrieved Fri, 29 Mar 2024 09:34:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-04 09:08:11] [2ad58ca14453c04e73fc838d0bf536d8] [Current]
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Dataseries X:
126,81
125,8
123,07
119,52
118,03
117,27
117,27
116,69
115,38
114,31
113,33
111,79
111,79
110,92
109,37
107,04
104,72
104,14
104,14
102,95
102,13
101,01
100,07
99,4
99,4
99,34
97,72
96,26
95,77
95,04
95,04
94,55
94
93,14
91,21
90,3
90,3
89,74
89,07
89,06
88,97
88,78
88,78
88,23
87,91
87,79
87,89
88
88
87,08
85,75
84,29
84,39
83,72
83,72
81,76
81,53
80,55
79,83
78,98
78,98
78,27
77,41
76,75
76,38
74,96
74,96
74,46
74,04
73,22
72,97
72,91
72,91
73,27
72,93
72,67
71,94
71,9
71,89
71,72
70,85
69,82
69,61
69,48




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230449&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]7 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=230449&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230449&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 time7 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1126.81NANA1.00438NA
2125.8NANA1.0063NA
3123.07NANA1.00153NA
4119.52NANA0.997335NA
5118.03NANA0.997175NA
6117.27NANA0.996738NA
7117.27117.852117.6471.001740.995064
8116.69116.366116.4010.9997051.00278
9115.38115.319115.211.000951.00053
10114.31114.008114.1190.9990291.00265
11113.33112.767113.0450.9975451.00499
12111.79111.672111.9430.997581.00106
13111.79111.334110.8491.004381.00409
14110.92110.42109.7291.00631.00453
15109.37108.77108.6051.001531.00551
16107.04107.212107.4980.9973350.998398
17104.72106.091106.3920.9971750.987076
18104.14104.979105.3230.9967380.992005
19104.14104.472104.291.001740.996821
20102.95103.261103.2920.9997050.996986
21102.13102.421102.3241.000950.997162
22101.01101.291101.3890.9990290.997228
23100.07100.32100.5670.9975450.997506
2499.499.573599.8150.997580.998258
2599.499.490499.05671.004380.999091
2699.3498.946898.32751.00631.00397
2797.7297.787897.63881.001530.999307
2896.2696.713696.97210.9973350.99531
2995.7796.00396.2750.9971750.997573
3095.0495.215195.52670.9967380.998161
3195.0494.933594.76831.001741.00112
3294.5593.961493.98920.9997051.00626
339493.317193.22871.000951.00732
3493.1492.478592.56830.9990291.00715
3591.2191.759291.9850.9975450.994015
3690.391.219691.44080.997580.989919
3790.391.317390.91921.004380.98886
3889.7490.964390.3951.00630.986541
3989.0790.015189.87791.001530.989501
4089.0689.16389.40120.9973350.998845
4188.9788.788589.040.9971751.00204
4288.7888.516288.80580.9967381.00298
4388.7888.768688.61421.001741.00013
4488.2388.381488.40750.9997050.998287
4587.9188.241888.15831.000950.996239
4687.7987.73687.82120.9990291.00062
4787.8987.21787.43170.9975451.00772
488886.819487.030.997581.0136
498886.987686.60831.004381.01164
5087.0886.670486.12791.00631.00473
5185.7585.723185.59251.001531.00031
5284.2984.798485.0250.9973350.994005
5384.3984.149184.38750.9971751.00286
5483.7283.402983.67580.9967381.0038
5583.7283.068782.92421.001741.00784
5681.7682.15782.18120.9997050.995168
5781.5381.543881.46671.000950.99983
5880.5580.726680.8050.9990290.997813
5979.8379.960380.15710.9975450.998371
6078.9879.266179.45830.997580.996391
6178.9879.073178.72831.004380.998823
6278.2778.550878.05921.00630.996425
6377.4177.561177.44291.001530.998052
6476.7576.620676.82540.9973351.00169
6576.3876.018876.23420.9971751.00475
6674.9675.448575.69540.9967380.993525
6774.9675.320675.18961.001740.995212
6874.4674.706374.72830.9997050.996703
6974.0474.403774.33331.000950.995111
7073.2273.904973.97670.9990290.990733
7172.9773.440973.62170.9975450.993588
7272.9173.131873.30920.997580.996967
7372.9173.373673.05381.004380.993681
7473.2773.270272.81171.00630.999997
7572.9372.675372.56461.001531.0035
7672.6772.097372.290.9973351.00794
7771.9471.804972.00830.9971751.00188
7871.971.491571.72540.9967381.00571
7971.89NANA1.00174NA
8071.72NANA0.999705NA
8170.85NANA1.00095NA
8269.82NANA0.999029NA
8369.61NANA0.997545NA
8469.48NANA0.99758NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 126.81 & NA & NA & 1.00438 & NA \tabularnewline
2 & 125.8 & NA & NA & 1.0063 & NA \tabularnewline
3 & 123.07 & NA & NA & 1.00153 & NA \tabularnewline
4 & 119.52 & NA & NA & 0.997335 & NA \tabularnewline
5 & 118.03 & NA & NA & 0.997175 & NA \tabularnewline
6 & 117.27 & NA & NA & 0.996738 & NA \tabularnewline
7 & 117.27 & 117.852 & 117.647 & 1.00174 & 0.995064 \tabularnewline
8 & 116.69 & 116.366 & 116.401 & 0.999705 & 1.00278 \tabularnewline
9 & 115.38 & 115.319 & 115.21 & 1.00095 & 1.00053 \tabularnewline
10 & 114.31 & 114.008 & 114.119 & 0.999029 & 1.00265 \tabularnewline
11 & 113.33 & 112.767 & 113.045 & 0.997545 & 1.00499 \tabularnewline
12 & 111.79 & 111.672 & 111.943 & 0.99758 & 1.00106 \tabularnewline
13 & 111.79 & 111.334 & 110.849 & 1.00438 & 1.00409 \tabularnewline
14 & 110.92 & 110.42 & 109.729 & 1.0063 & 1.00453 \tabularnewline
15 & 109.37 & 108.77 & 108.605 & 1.00153 & 1.00551 \tabularnewline
16 & 107.04 & 107.212 & 107.498 & 0.997335 & 0.998398 \tabularnewline
17 & 104.72 & 106.091 & 106.392 & 0.997175 & 0.987076 \tabularnewline
18 & 104.14 & 104.979 & 105.323 & 0.996738 & 0.992005 \tabularnewline
19 & 104.14 & 104.472 & 104.29 & 1.00174 & 0.996821 \tabularnewline
20 & 102.95 & 103.261 & 103.292 & 0.999705 & 0.996986 \tabularnewline
21 & 102.13 & 102.421 & 102.324 & 1.00095 & 0.997162 \tabularnewline
22 & 101.01 & 101.291 & 101.389 & 0.999029 & 0.997228 \tabularnewline
23 & 100.07 & 100.32 & 100.567 & 0.997545 & 0.997506 \tabularnewline
24 & 99.4 & 99.5735 & 99.815 & 0.99758 & 0.998258 \tabularnewline
25 & 99.4 & 99.4904 & 99.0567 & 1.00438 & 0.999091 \tabularnewline
26 & 99.34 & 98.9468 & 98.3275 & 1.0063 & 1.00397 \tabularnewline
27 & 97.72 & 97.7878 & 97.6388 & 1.00153 & 0.999307 \tabularnewline
28 & 96.26 & 96.7136 & 96.9721 & 0.997335 & 0.99531 \tabularnewline
29 & 95.77 & 96.003 & 96.275 & 0.997175 & 0.997573 \tabularnewline
30 & 95.04 & 95.2151 & 95.5267 & 0.996738 & 0.998161 \tabularnewline
31 & 95.04 & 94.9335 & 94.7683 & 1.00174 & 1.00112 \tabularnewline
32 & 94.55 & 93.9614 & 93.9892 & 0.999705 & 1.00626 \tabularnewline
33 & 94 & 93.3171 & 93.2287 & 1.00095 & 1.00732 \tabularnewline
34 & 93.14 & 92.4785 & 92.5683 & 0.999029 & 1.00715 \tabularnewline
35 & 91.21 & 91.7592 & 91.985 & 0.997545 & 0.994015 \tabularnewline
36 & 90.3 & 91.2196 & 91.4408 & 0.99758 & 0.989919 \tabularnewline
37 & 90.3 & 91.3173 & 90.9192 & 1.00438 & 0.98886 \tabularnewline
38 & 89.74 & 90.9643 & 90.395 & 1.0063 & 0.986541 \tabularnewline
39 & 89.07 & 90.0151 & 89.8779 & 1.00153 & 0.989501 \tabularnewline
40 & 89.06 & 89.163 & 89.4012 & 0.997335 & 0.998845 \tabularnewline
41 & 88.97 & 88.7885 & 89.04 & 0.997175 & 1.00204 \tabularnewline
42 & 88.78 & 88.5162 & 88.8058 & 0.996738 & 1.00298 \tabularnewline
43 & 88.78 & 88.7686 & 88.6142 & 1.00174 & 1.00013 \tabularnewline
44 & 88.23 & 88.3814 & 88.4075 & 0.999705 & 0.998287 \tabularnewline
45 & 87.91 & 88.2418 & 88.1583 & 1.00095 & 0.996239 \tabularnewline
46 & 87.79 & 87.736 & 87.8212 & 0.999029 & 1.00062 \tabularnewline
47 & 87.89 & 87.217 & 87.4317 & 0.997545 & 1.00772 \tabularnewline
48 & 88 & 86.8194 & 87.03 & 0.99758 & 1.0136 \tabularnewline
49 & 88 & 86.9876 & 86.6083 & 1.00438 & 1.01164 \tabularnewline
50 & 87.08 & 86.6704 & 86.1279 & 1.0063 & 1.00473 \tabularnewline
51 & 85.75 & 85.7231 & 85.5925 & 1.00153 & 1.00031 \tabularnewline
52 & 84.29 & 84.7984 & 85.025 & 0.997335 & 0.994005 \tabularnewline
53 & 84.39 & 84.1491 & 84.3875 & 0.997175 & 1.00286 \tabularnewline
54 & 83.72 & 83.4029 & 83.6758 & 0.996738 & 1.0038 \tabularnewline
55 & 83.72 & 83.0687 & 82.9242 & 1.00174 & 1.00784 \tabularnewline
56 & 81.76 & 82.157 & 82.1812 & 0.999705 & 0.995168 \tabularnewline
57 & 81.53 & 81.5438 & 81.4667 & 1.00095 & 0.99983 \tabularnewline
58 & 80.55 & 80.7266 & 80.805 & 0.999029 & 0.997813 \tabularnewline
59 & 79.83 & 79.9603 & 80.1571 & 0.997545 & 0.998371 \tabularnewline
60 & 78.98 & 79.2661 & 79.4583 & 0.99758 & 0.996391 \tabularnewline
61 & 78.98 & 79.0731 & 78.7283 & 1.00438 & 0.998823 \tabularnewline
62 & 78.27 & 78.5508 & 78.0592 & 1.0063 & 0.996425 \tabularnewline
63 & 77.41 & 77.5611 & 77.4429 & 1.00153 & 0.998052 \tabularnewline
64 & 76.75 & 76.6206 & 76.8254 & 0.997335 & 1.00169 \tabularnewline
65 & 76.38 & 76.0188 & 76.2342 & 0.997175 & 1.00475 \tabularnewline
66 & 74.96 & 75.4485 & 75.6954 & 0.996738 & 0.993525 \tabularnewline
67 & 74.96 & 75.3206 & 75.1896 & 1.00174 & 0.995212 \tabularnewline
68 & 74.46 & 74.7063 & 74.7283 & 0.999705 & 0.996703 \tabularnewline
69 & 74.04 & 74.4037 & 74.3333 & 1.00095 & 0.995111 \tabularnewline
70 & 73.22 & 73.9049 & 73.9767 & 0.999029 & 0.990733 \tabularnewline
71 & 72.97 & 73.4409 & 73.6217 & 0.997545 & 0.993588 \tabularnewline
72 & 72.91 & 73.1318 & 73.3092 & 0.99758 & 0.996967 \tabularnewline
73 & 72.91 & 73.3736 & 73.0538 & 1.00438 & 0.993681 \tabularnewline
74 & 73.27 & 73.2702 & 72.8117 & 1.0063 & 0.999997 \tabularnewline
75 & 72.93 & 72.6753 & 72.5646 & 1.00153 & 1.0035 \tabularnewline
76 & 72.67 & 72.0973 & 72.29 & 0.997335 & 1.00794 \tabularnewline
77 & 71.94 & 71.8049 & 72.0083 & 0.997175 & 1.00188 \tabularnewline
78 & 71.9 & 71.4915 & 71.7254 & 0.996738 & 1.00571 \tabularnewline
79 & 71.89 & NA & NA & 1.00174 & NA \tabularnewline
80 & 71.72 & NA & NA & 0.999705 & NA \tabularnewline
81 & 70.85 & NA & NA & 1.00095 & NA \tabularnewline
82 & 69.82 & NA & NA & 0.999029 & NA \tabularnewline
83 & 69.61 & NA & NA & 0.997545 & NA \tabularnewline
84 & 69.48 & NA & NA & 0.99758 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230449&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]126.81[/C][C]NA[/C][C]NA[/C][C]1.00438[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]125.8[/C][C]NA[/C][C]NA[/C][C]1.0063[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]123.07[/C][C]NA[/C][C]NA[/C][C]1.00153[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]119.52[/C][C]NA[/C][C]NA[/C][C]0.997335[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]118.03[/C][C]NA[/C][C]NA[/C][C]0.997175[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]117.27[/C][C]NA[/C][C]NA[/C][C]0.996738[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]117.27[/C][C]117.852[/C][C]117.647[/C][C]1.00174[/C][C]0.995064[/C][/ROW]
[ROW][C]8[/C][C]116.69[/C][C]116.366[/C][C]116.401[/C][C]0.999705[/C][C]1.00278[/C][/ROW]
[ROW][C]9[/C][C]115.38[/C][C]115.319[/C][C]115.21[/C][C]1.00095[/C][C]1.00053[/C][/ROW]
[ROW][C]10[/C][C]114.31[/C][C]114.008[/C][C]114.119[/C][C]0.999029[/C][C]1.00265[/C][/ROW]
[ROW][C]11[/C][C]113.33[/C][C]112.767[/C][C]113.045[/C][C]0.997545[/C][C]1.00499[/C][/ROW]
[ROW][C]12[/C][C]111.79[/C][C]111.672[/C][C]111.943[/C][C]0.99758[/C][C]1.00106[/C][/ROW]
[ROW][C]13[/C][C]111.79[/C][C]111.334[/C][C]110.849[/C][C]1.00438[/C][C]1.00409[/C][/ROW]
[ROW][C]14[/C][C]110.92[/C][C]110.42[/C][C]109.729[/C][C]1.0063[/C][C]1.00453[/C][/ROW]
[ROW][C]15[/C][C]109.37[/C][C]108.77[/C][C]108.605[/C][C]1.00153[/C][C]1.00551[/C][/ROW]
[ROW][C]16[/C][C]107.04[/C][C]107.212[/C][C]107.498[/C][C]0.997335[/C][C]0.998398[/C][/ROW]
[ROW][C]17[/C][C]104.72[/C][C]106.091[/C][C]106.392[/C][C]0.997175[/C][C]0.987076[/C][/ROW]
[ROW][C]18[/C][C]104.14[/C][C]104.979[/C][C]105.323[/C][C]0.996738[/C][C]0.992005[/C][/ROW]
[ROW][C]19[/C][C]104.14[/C][C]104.472[/C][C]104.29[/C][C]1.00174[/C][C]0.996821[/C][/ROW]
[ROW][C]20[/C][C]102.95[/C][C]103.261[/C][C]103.292[/C][C]0.999705[/C][C]0.996986[/C][/ROW]
[ROW][C]21[/C][C]102.13[/C][C]102.421[/C][C]102.324[/C][C]1.00095[/C][C]0.997162[/C][/ROW]
[ROW][C]22[/C][C]101.01[/C][C]101.291[/C][C]101.389[/C][C]0.999029[/C][C]0.997228[/C][/ROW]
[ROW][C]23[/C][C]100.07[/C][C]100.32[/C][C]100.567[/C][C]0.997545[/C][C]0.997506[/C][/ROW]
[ROW][C]24[/C][C]99.4[/C][C]99.5735[/C][C]99.815[/C][C]0.99758[/C][C]0.998258[/C][/ROW]
[ROW][C]25[/C][C]99.4[/C][C]99.4904[/C][C]99.0567[/C][C]1.00438[/C][C]0.999091[/C][/ROW]
[ROW][C]26[/C][C]99.34[/C][C]98.9468[/C][C]98.3275[/C][C]1.0063[/C][C]1.00397[/C][/ROW]
[ROW][C]27[/C][C]97.72[/C][C]97.7878[/C][C]97.6388[/C][C]1.00153[/C][C]0.999307[/C][/ROW]
[ROW][C]28[/C][C]96.26[/C][C]96.7136[/C][C]96.9721[/C][C]0.997335[/C][C]0.99531[/C][/ROW]
[ROW][C]29[/C][C]95.77[/C][C]96.003[/C][C]96.275[/C][C]0.997175[/C][C]0.997573[/C][/ROW]
[ROW][C]30[/C][C]95.04[/C][C]95.2151[/C][C]95.5267[/C][C]0.996738[/C][C]0.998161[/C][/ROW]
[ROW][C]31[/C][C]95.04[/C][C]94.9335[/C][C]94.7683[/C][C]1.00174[/C][C]1.00112[/C][/ROW]
[ROW][C]32[/C][C]94.55[/C][C]93.9614[/C][C]93.9892[/C][C]0.999705[/C][C]1.00626[/C][/ROW]
[ROW][C]33[/C][C]94[/C][C]93.3171[/C][C]93.2287[/C][C]1.00095[/C][C]1.00732[/C][/ROW]
[ROW][C]34[/C][C]93.14[/C][C]92.4785[/C][C]92.5683[/C][C]0.999029[/C][C]1.00715[/C][/ROW]
[ROW][C]35[/C][C]91.21[/C][C]91.7592[/C][C]91.985[/C][C]0.997545[/C][C]0.994015[/C][/ROW]
[ROW][C]36[/C][C]90.3[/C][C]91.2196[/C][C]91.4408[/C][C]0.99758[/C][C]0.989919[/C][/ROW]
[ROW][C]37[/C][C]90.3[/C][C]91.3173[/C][C]90.9192[/C][C]1.00438[/C][C]0.98886[/C][/ROW]
[ROW][C]38[/C][C]89.74[/C][C]90.9643[/C][C]90.395[/C][C]1.0063[/C][C]0.986541[/C][/ROW]
[ROW][C]39[/C][C]89.07[/C][C]90.0151[/C][C]89.8779[/C][C]1.00153[/C][C]0.989501[/C][/ROW]
[ROW][C]40[/C][C]89.06[/C][C]89.163[/C][C]89.4012[/C][C]0.997335[/C][C]0.998845[/C][/ROW]
[ROW][C]41[/C][C]88.97[/C][C]88.7885[/C][C]89.04[/C][C]0.997175[/C][C]1.00204[/C][/ROW]
[ROW][C]42[/C][C]88.78[/C][C]88.5162[/C][C]88.8058[/C][C]0.996738[/C][C]1.00298[/C][/ROW]
[ROW][C]43[/C][C]88.78[/C][C]88.7686[/C][C]88.6142[/C][C]1.00174[/C][C]1.00013[/C][/ROW]
[ROW][C]44[/C][C]88.23[/C][C]88.3814[/C][C]88.4075[/C][C]0.999705[/C][C]0.998287[/C][/ROW]
[ROW][C]45[/C][C]87.91[/C][C]88.2418[/C][C]88.1583[/C][C]1.00095[/C][C]0.996239[/C][/ROW]
[ROW][C]46[/C][C]87.79[/C][C]87.736[/C][C]87.8212[/C][C]0.999029[/C][C]1.00062[/C][/ROW]
[ROW][C]47[/C][C]87.89[/C][C]87.217[/C][C]87.4317[/C][C]0.997545[/C][C]1.00772[/C][/ROW]
[ROW][C]48[/C][C]88[/C][C]86.8194[/C][C]87.03[/C][C]0.99758[/C][C]1.0136[/C][/ROW]
[ROW][C]49[/C][C]88[/C][C]86.9876[/C][C]86.6083[/C][C]1.00438[/C][C]1.01164[/C][/ROW]
[ROW][C]50[/C][C]87.08[/C][C]86.6704[/C][C]86.1279[/C][C]1.0063[/C][C]1.00473[/C][/ROW]
[ROW][C]51[/C][C]85.75[/C][C]85.7231[/C][C]85.5925[/C][C]1.00153[/C][C]1.00031[/C][/ROW]
[ROW][C]52[/C][C]84.29[/C][C]84.7984[/C][C]85.025[/C][C]0.997335[/C][C]0.994005[/C][/ROW]
[ROW][C]53[/C][C]84.39[/C][C]84.1491[/C][C]84.3875[/C][C]0.997175[/C][C]1.00286[/C][/ROW]
[ROW][C]54[/C][C]83.72[/C][C]83.4029[/C][C]83.6758[/C][C]0.996738[/C][C]1.0038[/C][/ROW]
[ROW][C]55[/C][C]83.72[/C][C]83.0687[/C][C]82.9242[/C][C]1.00174[/C][C]1.00784[/C][/ROW]
[ROW][C]56[/C][C]81.76[/C][C]82.157[/C][C]82.1812[/C][C]0.999705[/C][C]0.995168[/C][/ROW]
[ROW][C]57[/C][C]81.53[/C][C]81.5438[/C][C]81.4667[/C][C]1.00095[/C][C]0.99983[/C][/ROW]
[ROW][C]58[/C][C]80.55[/C][C]80.7266[/C][C]80.805[/C][C]0.999029[/C][C]0.997813[/C][/ROW]
[ROW][C]59[/C][C]79.83[/C][C]79.9603[/C][C]80.1571[/C][C]0.997545[/C][C]0.998371[/C][/ROW]
[ROW][C]60[/C][C]78.98[/C][C]79.2661[/C][C]79.4583[/C][C]0.99758[/C][C]0.996391[/C][/ROW]
[ROW][C]61[/C][C]78.98[/C][C]79.0731[/C][C]78.7283[/C][C]1.00438[/C][C]0.998823[/C][/ROW]
[ROW][C]62[/C][C]78.27[/C][C]78.5508[/C][C]78.0592[/C][C]1.0063[/C][C]0.996425[/C][/ROW]
[ROW][C]63[/C][C]77.41[/C][C]77.5611[/C][C]77.4429[/C][C]1.00153[/C][C]0.998052[/C][/ROW]
[ROW][C]64[/C][C]76.75[/C][C]76.6206[/C][C]76.8254[/C][C]0.997335[/C][C]1.00169[/C][/ROW]
[ROW][C]65[/C][C]76.38[/C][C]76.0188[/C][C]76.2342[/C][C]0.997175[/C][C]1.00475[/C][/ROW]
[ROW][C]66[/C][C]74.96[/C][C]75.4485[/C][C]75.6954[/C][C]0.996738[/C][C]0.993525[/C][/ROW]
[ROW][C]67[/C][C]74.96[/C][C]75.3206[/C][C]75.1896[/C][C]1.00174[/C][C]0.995212[/C][/ROW]
[ROW][C]68[/C][C]74.46[/C][C]74.7063[/C][C]74.7283[/C][C]0.999705[/C][C]0.996703[/C][/ROW]
[ROW][C]69[/C][C]74.04[/C][C]74.4037[/C][C]74.3333[/C][C]1.00095[/C][C]0.995111[/C][/ROW]
[ROW][C]70[/C][C]73.22[/C][C]73.9049[/C][C]73.9767[/C][C]0.999029[/C][C]0.990733[/C][/ROW]
[ROW][C]71[/C][C]72.97[/C][C]73.4409[/C][C]73.6217[/C][C]0.997545[/C][C]0.993588[/C][/ROW]
[ROW][C]72[/C][C]72.91[/C][C]73.1318[/C][C]73.3092[/C][C]0.99758[/C][C]0.996967[/C][/ROW]
[ROW][C]73[/C][C]72.91[/C][C]73.3736[/C][C]73.0538[/C][C]1.00438[/C][C]0.993681[/C][/ROW]
[ROW][C]74[/C][C]73.27[/C][C]73.2702[/C][C]72.8117[/C][C]1.0063[/C][C]0.999997[/C][/ROW]
[ROW][C]75[/C][C]72.93[/C][C]72.6753[/C][C]72.5646[/C][C]1.00153[/C][C]1.0035[/C][/ROW]
[ROW][C]76[/C][C]72.67[/C][C]72.0973[/C][C]72.29[/C][C]0.997335[/C][C]1.00794[/C][/ROW]
[ROW][C]77[/C][C]71.94[/C][C]71.8049[/C][C]72.0083[/C][C]0.997175[/C][C]1.00188[/C][/ROW]
[ROW][C]78[/C][C]71.9[/C][C]71.4915[/C][C]71.7254[/C][C]0.996738[/C][C]1.00571[/C][/ROW]
[ROW][C]79[/C][C]71.89[/C][C]NA[/C][C]NA[/C][C]1.00174[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]71.72[/C][C]NA[/C][C]NA[/C][C]0.999705[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]70.85[/C][C]NA[/C][C]NA[/C][C]1.00095[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]69.82[/C][C]NA[/C][C]NA[/C][C]0.999029[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]69.61[/C][C]NA[/C][C]NA[/C][C]0.997545[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]69.48[/C][C]NA[/C][C]NA[/C][C]0.99758[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230449&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230449&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
1126.81NANA1.00438NA
2125.8NANA1.0063NA
3123.07NANA1.00153NA
4119.52NANA0.997335NA
5118.03NANA0.997175NA
6117.27NANA0.996738NA
7117.27117.852117.6471.001740.995064
8116.69116.366116.4010.9997051.00278
9115.38115.319115.211.000951.00053
10114.31114.008114.1190.9990291.00265
11113.33112.767113.0450.9975451.00499
12111.79111.672111.9430.997581.00106
13111.79111.334110.8491.004381.00409
14110.92110.42109.7291.00631.00453
15109.37108.77108.6051.001531.00551
16107.04107.212107.4980.9973350.998398
17104.72106.091106.3920.9971750.987076
18104.14104.979105.3230.9967380.992005
19104.14104.472104.291.001740.996821
20102.95103.261103.2920.9997050.996986
21102.13102.421102.3241.000950.997162
22101.01101.291101.3890.9990290.997228
23100.07100.32100.5670.9975450.997506
2499.499.573599.8150.997580.998258
2599.499.490499.05671.004380.999091
2699.3498.946898.32751.00631.00397
2797.7297.787897.63881.001530.999307
2896.2696.713696.97210.9973350.99531
2995.7796.00396.2750.9971750.997573
3095.0495.215195.52670.9967380.998161
3195.0494.933594.76831.001741.00112
3294.5593.961493.98920.9997051.00626
339493.317193.22871.000951.00732
3493.1492.478592.56830.9990291.00715
3591.2191.759291.9850.9975450.994015
3690.391.219691.44080.997580.989919
3790.391.317390.91921.004380.98886
3889.7490.964390.3951.00630.986541
3989.0790.015189.87791.001530.989501
4089.0689.16389.40120.9973350.998845
4188.9788.788589.040.9971751.00204
4288.7888.516288.80580.9967381.00298
4388.7888.768688.61421.001741.00013
4488.2388.381488.40750.9997050.998287
4587.9188.241888.15831.000950.996239
4687.7987.73687.82120.9990291.00062
4787.8987.21787.43170.9975451.00772
488886.819487.030.997581.0136
498886.987686.60831.004381.01164
5087.0886.670486.12791.00631.00473
5185.7585.723185.59251.001531.00031
5284.2984.798485.0250.9973350.994005
5384.3984.149184.38750.9971751.00286
5483.7283.402983.67580.9967381.0038
5583.7283.068782.92421.001741.00784
5681.7682.15782.18120.9997050.995168
5781.5381.543881.46671.000950.99983
5880.5580.726680.8050.9990290.997813
5979.8379.960380.15710.9975450.998371
6078.9879.266179.45830.997580.996391
6178.9879.073178.72831.004380.998823
6278.2778.550878.05921.00630.996425
6377.4177.561177.44291.001530.998052
6476.7576.620676.82540.9973351.00169
6576.3876.018876.23420.9971751.00475
6674.9675.448575.69540.9967380.993525
6774.9675.320675.18961.001740.995212
6874.4674.706374.72830.9997050.996703
6974.0474.403774.33331.000950.995111
7073.2273.904973.97670.9990290.990733
7172.9773.440973.62170.9975450.993588
7272.9173.131873.30920.997580.996967
7372.9173.373673.05381.004380.993681
7473.2773.270272.81171.00630.999997
7572.9372.675372.56461.001531.0035
7672.6772.097372.290.9973351.00794
7771.9471.804972.00830.9971751.00188
7871.971.491571.72540.9967381.00571
7971.89NANA1.00174NA
8071.72NANA0.999705NA
8170.85NANA1.00095NA
8269.82NANA0.999029NA
8369.61NANA0.997545NA
8469.48NANA0.99758NA



Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = multiplicative ; 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')