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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 21 May 2012 08:27:55 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/21/t1337603330n3cmgsxx3rovku6.htm/, Retrieved Thu, 02 May 2024 14:54:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166916, Retrieved Thu, 02 May 2024 14:54:25 +0000

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No (this computation is public)

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Estimated Impact

122

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Opgave 9 oef2] [2012-05-21 12:27:55] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.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 & 3 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166916&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166916&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166916&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'AstonUniversity' @ aston.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	92.8	NA	NA	-1.89504340277778	NA
2	90.61	NA	NA	-0.12316840277778	NA
3	88.49	NA	NA	0.421831597222223	NA
4	88.33	NA	NA	1.28901909722223	NA
5	87.7	NA	NA	0.66641493055556	NA
6	87.33	NA	NA	0.595894097222223	NA
7	87.33	87.9150607638889	87.4145833333333	0.50047743055556	-0.58506076388889
8	87.33	87.5843315972222	86.715	0.869331597222214	-0.254331597222233
9	85.47	85.7516232638889	86.205	-0.453376736111113	-0.281623263888903
10	86.1	86.0204774305556	85.8233333333334	0.197144097222222	0.0795225694444213
11	86.1	83.9216232638889	85.4979166666667	-1.57629340277777	2.1783767361111
12	86.13	84.4502690972222	84.9425	-0.492230902777777	1.67973090277778
13	83.31	82.2357899305556	84.1308333333333	-1.89504340277778	1.07421006944445
14	83.31	83.1480815972222	83.27125	-0.12316840277778	0.161918402777772
15	83.55	82.7076649305556	82.2858333333333	0.421831597222223	0.842335069444445
16	84.11	82.4931857638889	81.2041666666667	1.28901909722223	1.61681423611111
17	84.11	80.7493315972222	80.0829166666667	0.66641493055556	3.36066840277778
18	77.59	79.5379774305556	78.9420833333333	0.595894097222223	-1.94797743055555
19	77.59	78.4217274305556	77.92125	0.50047743055556	-0.83172743055556
20	76.44	77.8880815972222	77.01875	0.869331597222214	-1.44808159722223
21	72.71	75.6528732638889	76.10625	-0.453376736111113	-2.94287326388891
22	72.9	75.3500607638889	75.1529166666667	0.197144097222222	-2.45006076388889
23	72.39	72.5924565972222	74.16875	-1.57629340277777	-0.202456597222209
24	72.46	72.9640190972222	73.45625	-0.492230902777777	-0.504019097222226
25	72.48	71.0720399305555	72.9670833333333	-1.89504340277778	1.40796006944446
26	72.48	72.3543315972222	72.4775	-0.12316840277778	0.125668402777791
27	72.48	72.5234982638889	72.1016666666667	0.421831597222223	-0.0434982638888783
28	72.3	73.0490190972222	71.76	1.28901909722223	-0.749019097222217
29	72.3	72.0743315972222	71.4079166666667	0.66641493055556	0.225668402777785
30	72.3	71.7058940972222	71.11	0.595894097222223	0.59410590277777
31	71.14	71.1754774305556	70.675	0.50047743055556	-0.0354774305555594
32	71.14	71.1472482638889	70.2779166666667	0.869331597222214	-0.00724826388888289
33	68.99	69.6353732638889	70.08875	-0.453376736111113	-0.645373263888885
34	68.42	70.1454774305556	69.9483333333333	0.197144097222222	-1.72547743055556
35	68.42	68.1862065972222	69.7625	-1.57629340277777	0.233793402777778
36	69.28	68.9902690972222	69.4825	-0.492230902777777	0.289730902777777
37	65.22	67.3553732638889	69.2504166666667	-1.89504340277778	-2.13537326388889
38	70.21	68.9430815972222	69.06625	-0.12316840277778	1.26691840277776
39	70.21	69.3934982638889	68.9716666666667	0.421831597222223	0.816501736111107
40	71.2	70.2794357638889	68.9904166666667	1.28901909722223	0.920564236111119
41	68.94	69.3247482638889	68.6583333333333	0.66641493055556	-0.384748263888895
42	68.94	68.5575607638889	67.9616666666667	0.595894097222223	0.382439236111111
43	68.93	67.9096440972222	67.4091666666667	0.50047743055556	1.02035590277778
44	68.93	67.6522482638889	66.7829166666667	0.869331597222214	1.27775173611113
45	68.93	65.4920399305555	65.9454166666666	-0.453376736111113	3.43796006944447
46	68.93	65.2658940972222	65.06875	0.197144097222222	3.66410590277781
47	59.94	62.5816232638889	64.1579166666667	-1.57629340277777	-2.64162326388888
48	61.04	62.9373524305555	63.4295833333333	-0.492230902777777	-1.89735243055554
49	60.2	60.9787065972222	62.87375	-1.89504340277778	-0.778706597222211
50	60.2	62.1864149305556	62.3095833333333	-0.12316840277778	-1.98641493055555
51	60.12	62.1672482638889	61.7454166666667	0.421831597222223	-2.04724826388889
52	60.25	62.4702690972222	61.18125	1.28901909722223	-2.22026909722222
53	58.03	61.6634982638889	60.9970833333333	0.66641493055556	-3.63349826388889
54	62.37	61.8304774305556	61.2345833333333	0.595894097222223	0.539522569444443
55	62.16	NA	NA	0.50047743055556	NA
56	62.16	NA	NA	0.869331597222214	NA
57	62.16	NA	NA	-0.453376736111113	NA
58	62.16	NA	NA	0.197144097222222	NA
59	62.29	NA	NA	-1.57629340277777	NA
60	64.39	NA	NA	-0.492230902777777	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 92.8 & NA & NA & -1.89504340277778 & NA \tabularnewline
2 & 90.61 & NA & NA & -0.12316840277778 & NA \tabularnewline
3 & 88.49 & NA & NA & 0.421831597222223 & NA \tabularnewline
4 & 88.33 & NA & NA & 1.28901909722223 & NA \tabularnewline
5 & 87.7 & NA & NA & 0.66641493055556 & NA \tabularnewline
6 & 87.33 & NA & NA & 0.595894097222223 & NA \tabularnewline
7 & 87.33 & 87.9150607638889 & 87.4145833333333 & 0.50047743055556 & -0.58506076388889 \tabularnewline
8 & 87.33 & 87.5843315972222 & 86.715 & 0.869331597222214 & -0.254331597222233 \tabularnewline
9 & 85.47 & 85.7516232638889 & 86.205 & -0.453376736111113 & -0.281623263888903 \tabularnewline
10 & 86.1 & 86.0204774305556 & 85.8233333333334 & 0.197144097222222 & 0.0795225694444213 \tabularnewline
11 & 86.1 & 83.9216232638889 & 85.4979166666667 & -1.57629340277777 & 2.1783767361111 \tabularnewline
12 & 86.13 & 84.4502690972222 & 84.9425 & -0.492230902777777 & 1.67973090277778 \tabularnewline
13 & 83.31 & 82.2357899305556 & 84.1308333333333 & -1.89504340277778 & 1.07421006944445 \tabularnewline
14 & 83.31 & 83.1480815972222 & 83.27125 & -0.12316840277778 & 0.161918402777772 \tabularnewline
15 & 83.55 & 82.7076649305556 & 82.2858333333333 & 0.421831597222223 & 0.842335069444445 \tabularnewline
16 & 84.11 & 82.4931857638889 & 81.2041666666667 & 1.28901909722223 & 1.61681423611111 \tabularnewline
17 & 84.11 & 80.7493315972222 & 80.0829166666667 & 0.66641493055556 & 3.36066840277778 \tabularnewline
18 & 77.59 & 79.5379774305556 & 78.9420833333333 & 0.595894097222223 & -1.94797743055555 \tabularnewline
19 & 77.59 & 78.4217274305556 & 77.92125 & 0.50047743055556 & -0.83172743055556 \tabularnewline
20 & 76.44 & 77.8880815972222 & 77.01875 & 0.869331597222214 & -1.44808159722223 \tabularnewline
21 & 72.71 & 75.6528732638889 & 76.10625 & -0.453376736111113 & -2.94287326388891 \tabularnewline
22 & 72.9 & 75.3500607638889 & 75.1529166666667 & 0.197144097222222 & -2.45006076388889 \tabularnewline
23 & 72.39 & 72.5924565972222 & 74.16875 & -1.57629340277777 & -0.202456597222209 \tabularnewline
24 & 72.46 & 72.9640190972222 & 73.45625 & -0.492230902777777 & -0.504019097222226 \tabularnewline
25 & 72.48 & 71.0720399305555 & 72.9670833333333 & -1.89504340277778 & 1.40796006944446 \tabularnewline
26 & 72.48 & 72.3543315972222 & 72.4775 & -0.12316840277778 & 0.125668402777791 \tabularnewline
27 & 72.48 & 72.5234982638889 & 72.1016666666667 & 0.421831597222223 & -0.0434982638888783 \tabularnewline
28 & 72.3 & 73.0490190972222 & 71.76 & 1.28901909722223 & -0.749019097222217 \tabularnewline
29 & 72.3 & 72.0743315972222 & 71.4079166666667 & 0.66641493055556 & 0.225668402777785 \tabularnewline
30 & 72.3 & 71.7058940972222 & 71.11 & 0.595894097222223 & 0.59410590277777 \tabularnewline
31 & 71.14 & 71.1754774305556 & 70.675 & 0.50047743055556 & -0.0354774305555594 \tabularnewline
32 & 71.14 & 71.1472482638889 & 70.2779166666667 & 0.869331597222214 & -0.00724826388888289 \tabularnewline
33 & 68.99 & 69.6353732638889 & 70.08875 & -0.453376736111113 & -0.645373263888885 \tabularnewline
34 & 68.42 & 70.1454774305556 & 69.9483333333333 & 0.197144097222222 & -1.72547743055556 \tabularnewline
35 & 68.42 & 68.1862065972222 & 69.7625 & -1.57629340277777 & 0.233793402777778 \tabularnewline
36 & 69.28 & 68.9902690972222 & 69.4825 & -0.492230902777777 & 0.289730902777777 \tabularnewline
37 & 65.22 & 67.3553732638889 & 69.2504166666667 & -1.89504340277778 & -2.13537326388889 \tabularnewline
38 & 70.21 & 68.9430815972222 & 69.06625 & -0.12316840277778 & 1.26691840277776 \tabularnewline
39 & 70.21 & 69.3934982638889 & 68.9716666666667 & 0.421831597222223 & 0.816501736111107 \tabularnewline
40 & 71.2 & 70.2794357638889 & 68.9904166666667 & 1.28901909722223 & 0.920564236111119 \tabularnewline
41 & 68.94 & 69.3247482638889 & 68.6583333333333 & 0.66641493055556 & -0.384748263888895 \tabularnewline
42 & 68.94 & 68.5575607638889 & 67.9616666666667 & 0.595894097222223 & 0.382439236111111 \tabularnewline
43 & 68.93 & 67.9096440972222 & 67.4091666666667 & 0.50047743055556 & 1.02035590277778 \tabularnewline
44 & 68.93 & 67.6522482638889 & 66.7829166666667 & 0.869331597222214 & 1.27775173611113 \tabularnewline
45 & 68.93 & 65.4920399305555 & 65.9454166666666 & -0.453376736111113 & 3.43796006944447 \tabularnewline
46 & 68.93 & 65.2658940972222 & 65.06875 & 0.197144097222222 & 3.66410590277781 \tabularnewline
47 & 59.94 & 62.5816232638889 & 64.1579166666667 & -1.57629340277777 & -2.64162326388888 \tabularnewline
48 & 61.04 & 62.9373524305555 & 63.4295833333333 & -0.492230902777777 & -1.89735243055554 \tabularnewline
49 & 60.2 & 60.9787065972222 & 62.87375 & -1.89504340277778 & -0.778706597222211 \tabularnewline
50 & 60.2 & 62.1864149305556 & 62.3095833333333 & -0.12316840277778 & -1.98641493055555 \tabularnewline
51 & 60.12 & 62.1672482638889 & 61.7454166666667 & 0.421831597222223 & -2.04724826388889 \tabularnewline
52 & 60.25 & 62.4702690972222 & 61.18125 & 1.28901909722223 & -2.22026909722222 \tabularnewline
53 & 58.03 & 61.6634982638889 & 60.9970833333333 & 0.66641493055556 & -3.63349826388889 \tabularnewline
54 & 62.37 & 61.8304774305556 & 61.2345833333333 & 0.595894097222223 & 0.539522569444443 \tabularnewline
55 & 62.16 & NA & NA & 0.50047743055556 & NA \tabularnewline
56 & 62.16 & NA & NA & 0.869331597222214 & NA \tabularnewline
57 & 62.16 & NA & NA & -0.453376736111113 & NA \tabularnewline
58 & 62.16 & NA & NA & 0.197144097222222 & NA \tabularnewline
59 & 62.29 & NA & NA & -1.57629340277777 & NA \tabularnewline
60 & 64.39 & NA & NA & -0.492230902777777 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166916&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]92.8[/C][C]NA[/C][C]NA[/C][C]-1.89504340277778[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]90.61[/C][C]NA[/C][C]NA[/C][C]-0.12316840277778[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]88.49[/C][C]NA[/C][C]NA[/C][C]0.421831597222223[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]88.33[/C][C]NA[/C][C]NA[/C][C]1.28901909722223[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]87.7[/C][C]NA[/C][C]NA[/C][C]0.66641493055556[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]87.33[/C][C]NA[/C][C]NA[/C][C]0.595894097222223[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]87.33[/C][C]87.9150607638889[/C][C]87.4145833333333[/C][C]0.50047743055556[/C][C]-0.58506076388889[/C][/ROW]
[ROW][C]8[/C][C]87.33[/C][C]87.5843315972222[/C][C]86.715[/C][C]0.869331597222214[/C][C]-0.254331597222233[/C][/ROW]
[ROW][C]9[/C][C]85.47[/C][C]85.7516232638889[/C][C]86.205[/C][C]-0.453376736111113[/C][C]-0.281623263888903[/C][/ROW]
[ROW][C]10[/C][C]86.1[/C][C]86.0204774305556[/C][C]85.8233333333334[/C][C]0.197144097222222[/C][C]0.0795225694444213[/C][/ROW]
[ROW][C]11[/C][C]86.1[/C][C]83.9216232638889[/C][C]85.4979166666667[/C][C]-1.57629340277777[/C][C]2.1783767361111[/C][/ROW]
[ROW][C]12[/C][C]86.13[/C][C]84.4502690972222[/C][C]84.9425[/C][C]-0.492230902777777[/C][C]1.67973090277778[/C][/ROW]
[ROW][C]13[/C][C]83.31[/C][C]82.2357899305556[/C][C]84.1308333333333[/C][C]-1.89504340277778[/C][C]1.07421006944445[/C][/ROW]
[ROW][C]14[/C][C]83.31[/C][C]83.1480815972222[/C][C]83.27125[/C][C]-0.12316840277778[/C][C]0.161918402777772[/C][/ROW]
[ROW][C]15[/C][C]83.55[/C][C]82.7076649305556[/C][C]82.2858333333333[/C][C]0.421831597222223[/C][C]0.842335069444445[/C][/ROW]
[ROW][C]16[/C][C]84.11[/C][C]82.4931857638889[/C][C]81.2041666666667[/C][C]1.28901909722223[/C][C]1.61681423611111[/C][/ROW]
[ROW][C]17[/C][C]84.11[/C][C]80.7493315972222[/C][C]80.0829166666667[/C][C]0.66641493055556[/C][C]3.36066840277778[/C][/ROW]
[ROW][C]18[/C][C]77.59[/C][C]79.5379774305556[/C][C]78.9420833333333[/C][C]0.595894097222223[/C][C]-1.94797743055555[/C][/ROW]
[ROW][C]19[/C][C]77.59[/C][C]78.4217274305556[/C][C]77.92125[/C][C]0.50047743055556[/C][C]-0.83172743055556[/C][/ROW]
[ROW][C]20[/C][C]76.44[/C][C]77.8880815972222[/C][C]77.01875[/C][C]0.869331597222214[/C][C]-1.44808159722223[/C][/ROW]
[ROW][C]21[/C][C]72.71[/C][C]75.6528732638889[/C][C]76.10625[/C][C]-0.453376736111113[/C][C]-2.94287326388891[/C][/ROW]
[ROW][C]22[/C][C]72.9[/C][C]75.3500607638889[/C][C]75.1529166666667[/C][C]0.197144097222222[/C][C]-2.45006076388889[/C][/ROW]
[ROW][C]23[/C][C]72.39[/C][C]72.5924565972222[/C][C]74.16875[/C][C]-1.57629340277777[/C][C]-0.202456597222209[/C][/ROW]
[ROW][C]24[/C][C]72.46[/C][C]72.9640190972222[/C][C]73.45625[/C][C]-0.492230902777777[/C][C]-0.504019097222226[/C][/ROW]
[ROW][C]25[/C][C]72.48[/C][C]71.0720399305555[/C][C]72.9670833333333[/C][C]-1.89504340277778[/C][C]1.40796006944446[/C][/ROW]
[ROW][C]26[/C][C]72.48[/C][C]72.3543315972222[/C][C]72.4775[/C][C]-0.12316840277778[/C][C]0.125668402777791[/C][/ROW]
[ROW][C]27[/C][C]72.48[/C][C]72.5234982638889[/C][C]72.1016666666667[/C][C]0.421831597222223[/C][C]-0.0434982638888783[/C][/ROW]
[ROW][C]28[/C][C]72.3[/C][C]73.0490190972222[/C][C]71.76[/C][C]1.28901909722223[/C][C]-0.749019097222217[/C][/ROW]
[ROW][C]29[/C][C]72.3[/C][C]72.0743315972222[/C][C]71.4079166666667[/C][C]0.66641493055556[/C][C]0.225668402777785[/C][/ROW]
[ROW][C]30[/C][C]72.3[/C][C]71.7058940972222[/C][C]71.11[/C][C]0.595894097222223[/C][C]0.59410590277777[/C][/ROW]
[ROW][C]31[/C][C]71.14[/C][C]71.1754774305556[/C][C]70.675[/C][C]0.50047743055556[/C][C]-0.0354774305555594[/C][/ROW]
[ROW][C]32[/C][C]71.14[/C][C]71.1472482638889[/C][C]70.2779166666667[/C][C]0.869331597222214[/C][C]-0.00724826388888289[/C][/ROW]
[ROW][C]33[/C][C]68.99[/C][C]69.6353732638889[/C][C]70.08875[/C][C]-0.453376736111113[/C][C]-0.645373263888885[/C][/ROW]
[ROW][C]34[/C][C]68.42[/C][C]70.1454774305556[/C][C]69.9483333333333[/C][C]0.197144097222222[/C][C]-1.72547743055556[/C][/ROW]
[ROW][C]35[/C][C]68.42[/C][C]68.1862065972222[/C][C]69.7625[/C][C]-1.57629340277777[/C][C]0.233793402777778[/C][/ROW]
[ROW][C]36[/C][C]69.28[/C][C]68.9902690972222[/C][C]69.4825[/C][C]-0.492230902777777[/C][C]0.289730902777777[/C][/ROW]
[ROW][C]37[/C][C]65.22[/C][C]67.3553732638889[/C][C]69.2504166666667[/C][C]-1.89504340277778[/C][C]-2.13537326388889[/C][/ROW]
[ROW][C]38[/C][C]70.21[/C][C]68.9430815972222[/C][C]69.06625[/C][C]-0.12316840277778[/C][C]1.26691840277776[/C][/ROW]
[ROW][C]39[/C][C]70.21[/C][C]69.3934982638889[/C][C]68.9716666666667[/C][C]0.421831597222223[/C][C]0.816501736111107[/C][/ROW]
[ROW][C]40[/C][C]71.2[/C][C]70.2794357638889[/C][C]68.9904166666667[/C][C]1.28901909722223[/C][C]0.920564236111119[/C][/ROW]
[ROW][C]41[/C][C]68.94[/C][C]69.3247482638889[/C][C]68.6583333333333[/C][C]0.66641493055556[/C][C]-0.384748263888895[/C][/ROW]
[ROW][C]42[/C][C]68.94[/C][C]68.5575607638889[/C][C]67.9616666666667[/C][C]0.595894097222223[/C][C]0.382439236111111[/C][/ROW]
[ROW][C]43[/C][C]68.93[/C][C]67.9096440972222[/C][C]67.4091666666667[/C][C]0.50047743055556[/C][C]1.02035590277778[/C][/ROW]
[ROW][C]44[/C][C]68.93[/C][C]67.6522482638889[/C][C]66.7829166666667[/C][C]0.869331597222214[/C][C]1.27775173611113[/C][/ROW]
[ROW][C]45[/C][C]68.93[/C][C]65.4920399305555[/C][C]65.9454166666666[/C][C]-0.453376736111113[/C][C]3.43796006944447[/C][/ROW]
[ROW][C]46[/C][C]68.93[/C][C]65.2658940972222[/C][C]65.06875[/C][C]0.197144097222222[/C][C]3.66410590277781[/C][/ROW]
[ROW][C]47[/C][C]59.94[/C][C]62.5816232638889[/C][C]64.1579166666667[/C][C]-1.57629340277777[/C][C]-2.64162326388888[/C][/ROW]
[ROW][C]48[/C][C]61.04[/C][C]62.9373524305555[/C][C]63.4295833333333[/C][C]-0.492230902777777[/C][C]-1.89735243055554[/C][/ROW]
[ROW][C]49[/C][C]60.2[/C][C]60.9787065972222[/C][C]62.87375[/C][C]-1.89504340277778[/C][C]-0.778706597222211[/C][/ROW]
[ROW][C]50[/C][C]60.2[/C][C]62.1864149305556[/C][C]62.3095833333333[/C][C]-0.12316840277778[/C][C]-1.98641493055555[/C][/ROW]
[ROW][C]51[/C][C]60.12[/C][C]62.1672482638889[/C][C]61.7454166666667[/C][C]0.421831597222223[/C][C]-2.04724826388889[/C][/ROW]
[ROW][C]52[/C][C]60.25[/C][C]62.4702690972222[/C][C]61.18125[/C][C]1.28901909722223[/C][C]-2.22026909722222[/C][/ROW]
[ROW][C]53[/C][C]58.03[/C][C]61.6634982638889[/C][C]60.9970833333333[/C][C]0.66641493055556[/C][C]-3.63349826388889[/C][/ROW]
[ROW][C]54[/C][C]62.37[/C][C]61.8304774305556[/C][C]61.2345833333333[/C][C]0.595894097222223[/C][C]0.539522569444443[/C][/ROW]
[ROW][C]55[/C][C]62.16[/C][C]NA[/C][C]NA[/C][C]0.50047743055556[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]62.16[/C][C]NA[/C][C]NA[/C][C]0.869331597222214[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]62.16[/C][C]NA[/C][C]NA[/C][C]-0.453376736111113[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]62.16[/C][C]NA[/C][C]NA[/C][C]0.197144097222222[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]62.29[/C][C]NA[/C][C]NA[/C][C]-1.57629340277777[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]64.39[/C][C]NA[/C][C]NA[/C][C]-0.492230902777777[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166916&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166916&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
t	Observations	Fit	Trend	Seasonal	Random
1	92.8	NA	NA	-1.89504340277778	NA
2	90.61	NA	NA	-0.12316840277778	NA
3	88.49	NA	NA	0.421831597222223	NA
4	88.33	NA	NA	1.28901909722223	NA
5	87.7	NA	NA	0.66641493055556	NA
6	87.33	NA	NA	0.595894097222223	NA
7	87.33	87.9150607638889	87.4145833333333	0.50047743055556	-0.58506076388889
8	87.33	87.5843315972222	86.715	0.869331597222214	-0.254331597222233
9	85.47	85.7516232638889	86.205	-0.453376736111113	-0.281623263888903
10	86.1	86.0204774305556	85.8233333333334	0.197144097222222	0.0795225694444213
11	86.1	83.9216232638889	85.4979166666667	-1.57629340277777	2.1783767361111
12	86.13	84.4502690972222	84.9425	-0.492230902777777	1.67973090277778
13	83.31	82.2357899305556	84.1308333333333	-1.89504340277778	1.07421006944445
14	83.31	83.1480815972222	83.27125	-0.12316840277778	0.161918402777772
15	83.55	82.7076649305556	82.2858333333333	0.421831597222223	0.842335069444445
16	84.11	82.4931857638889	81.2041666666667	1.28901909722223	1.61681423611111
17	84.11	80.7493315972222	80.0829166666667	0.66641493055556	3.36066840277778
18	77.59	79.5379774305556	78.9420833333333	0.595894097222223	-1.94797743055555
19	77.59	78.4217274305556	77.92125	0.50047743055556	-0.83172743055556
20	76.44	77.8880815972222	77.01875	0.869331597222214	-1.44808159722223
21	72.71	75.6528732638889	76.10625	-0.453376736111113	-2.94287326388891
22	72.9	75.3500607638889	75.1529166666667	0.197144097222222	-2.45006076388889
23	72.39	72.5924565972222	74.16875	-1.57629340277777	-0.202456597222209
24	72.46	72.9640190972222	73.45625	-0.492230902777777	-0.504019097222226
25	72.48	71.0720399305555	72.9670833333333	-1.89504340277778	1.40796006944446
26	72.48	72.3543315972222	72.4775	-0.12316840277778	0.125668402777791
27	72.48	72.5234982638889	72.1016666666667	0.421831597222223	-0.0434982638888783
28	72.3	73.0490190972222	71.76	1.28901909722223	-0.749019097222217
29	72.3	72.0743315972222	71.4079166666667	0.66641493055556	0.225668402777785
30	72.3	71.7058940972222	71.11	0.595894097222223	0.59410590277777
31	71.14	71.1754774305556	70.675	0.50047743055556	-0.0354774305555594
32	71.14	71.1472482638889	70.2779166666667	0.869331597222214	-0.00724826388888289
33	68.99	69.6353732638889	70.08875	-0.453376736111113	-0.645373263888885
34	68.42	70.1454774305556	69.9483333333333	0.197144097222222	-1.72547743055556
35	68.42	68.1862065972222	69.7625	-1.57629340277777	0.233793402777778
36	69.28	68.9902690972222	69.4825	-0.492230902777777	0.289730902777777
37	65.22	67.3553732638889	69.2504166666667	-1.89504340277778	-2.13537326388889
38	70.21	68.9430815972222	69.06625	-0.12316840277778	1.26691840277776
39	70.21	69.3934982638889	68.9716666666667	0.421831597222223	0.816501736111107
40	71.2	70.2794357638889	68.9904166666667	1.28901909722223	0.920564236111119
41	68.94	69.3247482638889	68.6583333333333	0.66641493055556	-0.384748263888895
42	68.94	68.5575607638889	67.9616666666667	0.595894097222223	0.382439236111111
43	68.93	67.9096440972222	67.4091666666667	0.50047743055556	1.02035590277778
44	68.93	67.6522482638889	66.7829166666667	0.869331597222214	1.27775173611113
45	68.93	65.4920399305555	65.9454166666666	-0.453376736111113	3.43796006944447
46	68.93	65.2658940972222	65.06875	0.197144097222222	3.66410590277781
47	59.94	62.5816232638889	64.1579166666667	-1.57629340277777	-2.64162326388888
48	61.04	62.9373524305555	63.4295833333333	-0.492230902777777	-1.89735243055554
49	60.2	60.9787065972222	62.87375	-1.89504340277778	-0.778706597222211
50	60.2	62.1864149305556	62.3095833333333	-0.12316840277778	-1.98641493055555
51	60.12	62.1672482638889	61.7454166666667	0.421831597222223	-2.04724826388889
52	60.25	62.4702690972222	61.18125	1.28901909722223	-2.22026909722222
53	58.03	61.6634982638889	60.9970833333333	0.66641493055556	-3.63349826388889
54	62.37	61.8304774305556	61.2345833333333	0.595894097222223	0.539522569444443
55	62.16	NA	NA	0.50047743055556	NA
56	62.16	NA	NA	0.869331597222214	NA
57	62.16	NA	NA	-0.453376736111113	NA
58	62.16	NA	NA	0.197144097222222	NA
59	62.29	NA	NA	-1.57629340277777	NA
60	64.39	NA	NA	-0.492230902777777	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code