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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 24 Apr 2016 15:04:33 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/24/t1461506740l0j9z3i9yvtaors.htm/, Retrieved Tue, 30 Apr 2024 19:05:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294634, Retrieved Tue, 30 Apr 2024 19:05:51 +0000

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127

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-       [Classical Decomposition] [] [2016-04-24 14:04:33] [1b498ae19017f51f703ef2d779b672b0] [Current]

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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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294634&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294634&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294634&T=0

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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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	8.9	NA	NA	-1.25562	NA
2	9.2	NA	NA	-0.855625	NA
3	12.8	NA	NA	1.79104	NA
4	11.1	NA	NA	-0.409792	NA
5	11.2	NA	NA	-0.286458	NA
6	13.1	NA	NA	0.985208	NA
7	12.6	11.5869	11.4458	0.141042	1.01313
8	10	10.216	11.5833	-1.36729	-0.216042
9	12.3	12.2894	11.75	0.539375	0.010625
10	12.5	13.6619	11.9083	1.75354	-1.16188
11	11.4	11.5544	11.9917	-0.437292	-0.154375
12	11.5	11.4435	12.0417	-0.598125	0.0564583
13	10.4	10.8194	12.075	-1.25562	-0.419375
14	11	11.2694	12.125	-0.855625	-0.269375
15	15	14.1119	12.3208	1.79104	0.888125
16	12.7	12.1735	12.5833	-0.409792	0.526458
17	11.6	12.5219	12.8083	-0.286458	-0.921875
18	13.9	14.031	13.0458	0.985208	-0.131042
19	12.6	13.3619	13.2208	0.141042	-0.761875
20	11.2	11.9744	13.3417	-1.36729	-0.774375
21	15.8	14.006	13.4667	0.539375	1.79396
22	15.3	15.2744	13.5208	1.75354	0.025625
23	14	13.1669	13.6042	-0.437292	0.833125
24	14.6	13.0269	13.625	-0.598125	1.57313
25	11.5	12.336	13.5917	-1.25562	-0.836042
26	12.8	12.7944	13.65	-0.855625	0.005625
27	16.2	15.4077	13.6167	1.79104	0.792292
28	12.8	13.2319	13.6417	-0.409792	-0.431875
29	13.5	13.4385	13.725	-0.286458	0.0614583
30	12.5	14.6727	13.6875	0.985208	-2.17271
31	13.2	13.791	13.65	0.141042	-0.591042
32	12	12.2452	13.6125	-1.36729	-0.245208
33	14.2	14.1227	13.5833	0.539375	0.0772917
34	17.5	15.2869	13.5333	1.75354	2.21313
35	13.8	13.0044	13.4417	-0.437292	0.795625
36	13.9	12.931	13.5292	-0.598125	0.968958
37	11.3	12.3652	13.6208	-1.25562	-1.06521
38	12.1	12.7277	13.5833	-0.855625	-0.627708
39	16.2	15.2869	13.4958	1.79104	0.913125
40	11.6	12.8485	13.2583	-0.409792	-1.24854
41	12.5	12.7594	13.0458	-0.286458	-0.259375
42	15.6	13.8269	12.8417	0.985208	1.77313
43	12.3	12.9619	12.8208	0.141042	-0.661875
44	12	11.6202	12.9875	-1.36729	0.379792
45	12.1	13.4685	12.9292	0.539375	-1.36854
46	13.9	14.6869	12.9333	1.75354	-0.786875
47	12.3	12.721	13.1583	-0.437292	-0.421042
48	10.5	12.706	13.3042	-0.598125	-2.20604
49	14.2	12.1944	13.45	-1.25562	2.00563
50	13.2	12.7694	13.625	-0.855625	0.430625
51	13.7	15.5535	13.7625	1.79104	-1.85354
52	14.2	13.4985	13.9083	-0.409792	0.701458
53	15.3	13.6969	13.9833	-0.286458	1.60313
54	16.3	15.0769	14.0917	0.985208	1.22312
55	15.1	14.2785	14.1375	0.141042	0.821458
56	13.4	12.7244	14.0917	-1.36729	0.675625
57	14	14.6935	14.1542	0.539375	-0.693542
58	15.5	15.9702	14.2167	1.75354	-0.470208
59	12.5	13.7335	14.1708	-0.437292	-1.23354
60	12.9	13.4727	14.0708	-0.598125	-0.572708
61	12.9	12.7652	14.0208	-1.25562	0.134792
62	13.4	13.1194	13.975	-0.855625	0.280625
63	15	15.9202	14.1292	1.79104	-0.920208
64	14.4	14.1277	14.5375	-0.409792	0.272292
65	14	14.6635	14.95	-0.286458	-0.663542
66	15.2	16.0727	15.0875	0.985208	-0.872708
67	15	NA	NA	0.141042	NA
68	12.4	NA	NA	-1.36729	NA
69	18.7	NA	NA	0.539375	NA
70	20.6	NA	NA	1.75354	NA
71	17.3	NA	NA	-0.437292	NA
72	11.4	NA	NA	-0.598125	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 8.9 & NA & NA & -1.25562 & NA \tabularnewline
2 & 9.2 & NA & NA & -0.855625 & NA \tabularnewline
3 & 12.8 & NA & NA & 1.79104 & NA \tabularnewline
4 & 11.1 & NA & NA & -0.409792 & NA \tabularnewline
5 & 11.2 & NA & NA & -0.286458 & NA \tabularnewline
6 & 13.1 & NA & NA & 0.985208 & NA \tabularnewline
7 & 12.6 & 11.5869 & 11.4458 & 0.141042 & 1.01313 \tabularnewline
8 & 10 & 10.216 & 11.5833 & -1.36729 & -0.216042 \tabularnewline
9 & 12.3 & 12.2894 & 11.75 & 0.539375 & 0.010625 \tabularnewline
10 & 12.5 & 13.6619 & 11.9083 & 1.75354 & -1.16188 \tabularnewline
11 & 11.4 & 11.5544 & 11.9917 & -0.437292 & -0.154375 \tabularnewline
12 & 11.5 & 11.4435 & 12.0417 & -0.598125 & 0.0564583 \tabularnewline
13 & 10.4 & 10.8194 & 12.075 & -1.25562 & -0.419375 \tabularnewline
14 & 11 & 11.2694 & 12.125 & -0.855625 & -0.269375 \tabularnewline
15 & 15 & 14.1119 & 12.3208 & 1.79104 & 0.888125 \tabularnewline
16 & 12.7 & 12.1735 & 12.5833 & -0.409792 & 0.526458 \tabularnewline
17 & 11.6 & 12.5219 & 12.8083 & -0.286458 & -0.921875 \tabularnewline
18 & 13.9 & 14.031 & 13.0458 & 0.985208 & -0.131042 \tabularnewline
19 & 12.6 & 13.3619 & 13.2208 & 0.141042 & -0.761875 \tabularnewline
20 & 11.2 & 11.9744 & 13.3417 & -1.36729 & -0.774375 \tabularnewline
21 & 15.8 & 14.006 & 13.4667 & 0.539375 & 1.79396 \tabularnewline
22 & 15.3 & 15.2744 & 13.5208 & 1.75354 & 0.025625 \tabularnewline
23 & 14 & 13.1669 & 13.6042 & -0.437292 & 0.833125 \tabularnewline
24 & 14.6 & 13.0269 & 13.625 & -0.598125 & 1.57313 \tabularnewline
25 & 11.5 & 12.336 & 13.5917 & -1.25562 & -0.836042 \tabularnewline
26 & 12.8 & 12.7944 & 13.65 & -0.855625 & 0.005625 \tabularnewline
27 & 16.2 & 15.4077 & 13.6167 & 1.79104 & 0.792292 \tabularnewline
28 & 12.8 & 13.2319 & 13.6417 & -0.409792 & -0.431875 \tabularnewline
29 & 13.5 & 13.4385 & 13.725 & -0.286458 & 0.0614583 \tabularnewline
30 & 12.5 & 14.6727 & 13.6875 & 0.985208 & -2.17271 \tabularnewline
31 & 13.2 & 13.791 & 13.65 & 0.141042 & -0.591042 \tabularnewline
32 & 12 & 12.2452 & 13.6125 & -1.36729 & -0.245208 \tabularnewline
33 & 14.2 & 14.1227 & 13.5833 & 0.539375 & 0.0772917 \tabularnewline
34 & 17.5 & 15.2869 & 13.5333 & 1.75354 & 2.21313 \tabularnewline
35 & 13.8 & 13.0044 & 13.4417 & -0.437292 & 0.795625 \tabularnewline
36 & 13.9 & 12.931 & 13.5292 & -0.598125 & 0.968958 \tabularnewline
37 & 11.3 & 12.3652 & 13.6208 & -1.25562 & -1.06521 \tabularnewline
38 & 12.1 & 12.7277 & 13.5833 & -0.855625 & -0.627708 \tabularnewline
39 & 16.2 & 15.2869 & 13.4958 & 1.79104 & 0.913125 \tabularnewline
40 & 11.6 & 12.8485 & 13.2583 & -0.409792 & -1.24854 \tabularnewline
41 & 12.5 & 12.7594 & 13.0458 & -0.286458 & -0.259375 \tabularnewline
42 & 15.6 & 13.8269 & 12.8417 & 0.985208 & 1.77313 \tabularnewline
43 & 12.3 & 12.9619 & 12.8208 & 0.141042 & -0.661875 \tabularnewline
44 & 12 & 11.6202 & 12.9875 & -1.36729 & 0.379792 \tabularnewline
45 & 12.1 & 13.4685 & 12.9292 & 0.539375 & -1.36854 \tabularnewline
46 & 13.9 & 14.6869 & 12.9333 & 1.75354 & -0.786875 \tabularnewline
47 & 12.3 & 12.721 & 13.1583 & -0.437292 & -0.421042 \tabularnewline
48 & 10.5 & 12.706 & 13.3042 & -0.598125 & -2.20604 \tabularnewline
49 & 14.2 & 12.1944 & 13.45 & -1.25562 & 2.00563 \tabularnewline
50 & 13.2 & 12.7694 & 13.625 & -0.855625 & 0.430625 \tabularnewline
51 & 13.7 & 15.5535 & 13.7625 & 1.79104 & -1.85354 \tabularnewline
52 & 14.2 & 13.4985 & 13.9083 & -0.409792 & 0.701458 \tabularnewline
53 & 15.3 & 13.6969 & 13.9833 & -0.286458 & 1.60313 \tabularnewline
54 & 16.3 & 15.0769 & 14.0917 & 0.985208 & 1.22312 \tabularnewline
55 & 15.1 & 14.2785 & 14.1375 & 0.141042 & 0.821458 \tabularnewline
56 & 13.4 & 12.7244 & 14.0917 & -1.36729 & 0.675625 \tabularnewline
57 & 14 & 14.6935 & 14.1542 & 0.539375 & -0.693542 \tabularnewline
58 & 15.5 & 15.9702 & 14.2167 & 1.75354 & -0.470208 \tabularnewline
59 & 12.5 & 13.7335 & 14.1708 & -0.437292 & -1.23354 \tabularnewline
60 & 12.9 & 13.4727 & 14.0708 & -0.598125 & -0.572708 \tabularnewline
61 & 12.9 & 12.7652 & 14.0208 & -1.25562 & 0.134792 \tabularnewline
62 & 13.4 & 13.1194 & 13.975 & -0.855625 & 0.280625 \tabularnewline
63 & 15 & 15.9202 & 14.1292 & 1.79104 & -0.920208 \tabularnewline
64 & 14.4 & 14.1277 & 14.5375 & -0.409792 & 0.272292 \tabularnewline
65 & 14 & 14.6635 & 14.95 & -0.286458 & -0.663542 \tabularnewline
66 & 15.2 & 16.0727 & 15.0875 & 0.985208 & -0.872708 \tabularnewline
67 & 15 & NA & NA & 0.141042 & NA \tabularnewline
68 & 12.4 & NA & NA & -1.36729 & NA \tabularnewline
69 & 18.7 & NA & NA & 0.539375 & NA \tabularnewline
70 & 20.6 & NA & NA & 1.75354 & NA \tabularnewline
71 & 17.3 & NA & NA & -0.437292 & NA \tabularnewline
72 & 11.4 & NA & NA & -0.598125 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294634&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]8.9[/C][C]NA[/C][C]NA[/C][C]-1.25562[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.2[/C][C]NA[/C][C]NA[/C][C]-0.855625[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]NA[/C][C]NA[/C][C]1.79104[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]11.1[/C][C]NA[/C][C]NA[/C][C]-0.409792[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]11.2[/C][C]NA[/C][C]NA[/C][C]-0.286458[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]13.1[/C][C]NA[/C][C]NA[/C][C]0.985208[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]11.5869[/C][C]11.4458[/C][C]0.141042[/C][C]1.01313[/C][/ROW]
[ROW][C]8[/C][C]10[/C][C]10.216[/C][C]11.5833[/C][C]-1.36729[/C][C]-0.216042[/C][/ROW]
[ROW][C]9[/C][C]12.3[/C][C]12.2894[/C][C]11.75[/C][C]0.539375[/C][C]0.010625[/C][/ROW]
[ROW][C]10[/C][C]12.5[/C][C]13.6619[/C][C]11.9083[/C][C]1.75354[/C][C]-1.16188[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.5544[/C][C]11.9917[/C][C]-0.437292[/C][C]-0.154375[/C][/ROW]
[ROW][C]12[/C][C]11.5[/C][C]11.4435[/C][C]12.0417[/C][C]-0.598125[/C][C]0.0564583[/C][/ROW]
[ROW][C]13[/C][C]10.4[/C][C]10.8194[/C][C]12.075[/C][C]-1.25562[/C][C]-0.419375[/C][/ROW]
[ROW][C]14[/C][C]11[/C][C]11.2694[/C][C]12.125[/C][C]-0.855625[/C][C]-0.269375[/C][/ROW]
[ROW][C]15[/C][C]15[/C][C]14.1119[/C][C]12.3208[/C][C]1.79104[/C][C]0.888125[/C][/ROW]
[ROW][C]16[/C][C]12.7[/C][C]12.1735[/C][C]12.5833[/C][C]-0.409792[/C][C]0.526458[/C][/ROW]
[ROW][C]17[/C][C]11.6[/C][C]12.5219[/C][C]12.8083[/C][C]-0.286458[/C][C]-0.921875[/C][/ROW]
[ROW][C]18[/C][C]13.9[/C][C]14.031[/C][C]13.0458[/C][C]0.985208[/C][C]-0.131042[/C][/ROW]
[ROW][C]19[/C][C]12.6[/C][C]13.3619[/C][C]13.2208[/C][C]0.141042[/C][C]-0.761875[/C][/ROW]
[ROW][C]20[/C][C]11.2[/C][C]11.9744[/C][C]13.3417[/C][C]-1.36729[/C][C]-0.774375[/C][/ROW]
[ROW][C]21[/C][C]15.8[/C][C]14.006[/C][C]13.4667[/C][C]0.539375[/C][C]1.79396[/C][/ROW]
[ROW][C]22[/C][C]15.3[/C][C]15.2744[/C][C]13.5208[/C][C]1.75354[/C][C]0.025625[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]13.1669[/C][C]13.6042[/C][C]-0.437292[/C][C]0.833125[/C][/ROW]
[ROW][C]24[/C][C]14.6[/C][C]13.0269[/C][C]13.625[/C][C]-0.598125[/C][C]1.57313[/C][/ROW]
[ROW][C]25[/C][C]11.5[/C][C]12.336[/C][C]13.5917[/C][C]-1.25562[/C][C]-0.836042[/C][/ROW]
[ROW][C]26[/C][C]12.8[/C][C]12.7944[/C][C]13.65[/C][C]-0.855625[/C][C]0.005625[/C][/ROW]
[ROW][C]27[/C][C]16.2[/C][C]15.4077[/C][C]13.6167[/C][C]1.79104[/C][C]0.792292[/C][/ROW]
[ROW][C]28[/C][C]12.8[/C][C]13.2319[/C][C]13.6417[/C][C]-0.409792[/C][C]-0.431875[/C][/ROW]
[ROW][C]29[/C][C]13.5[/C][C]13.4385[/C][C]13.725[/C][C]-0.286458[/C][C]0.0614583[/C][/ROW]
[ROW][C]30[/C][C]12.5[/C][C]14.6727[/C][C]13.6875[/C][C]0.985208[/C][C]-2.17271[/C][/ROW]
[ROW][C]31[/C][C]13.2[/C][C]13.791[/C][C]13.65[/C][C]0.141042[/C][C]-0.591042[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.2452[/C][C]13.6125[/C][C]-1.36729[/C][C]-0.245208[/C][/ROW]
[ROW][C]33[/C][C]14.2[/C][C]14.1227[/C][C]13.5833[/C][C]0.539375[/C][C]0.0772917[/C][/ROW]
[ROW][C]34[/C][C]17.5[/C][C]15.2869[/C][C]13.5333[/C][C]1.75354[/C][C]2.21313[/C][/ROW]
[ROW][C]35[/C][C]13.8[/C][C]13.0044[/C][C]13.4417[/C][C]-0.437292[/C][C]0.795625[/C][/ROW]
[ROW][C]36[/C][C]13.9[/C][C]12.931[/C][C]13.5292[/C][C]-0.598125[/C][C]0.968958[/C][/ROW]
[ROW][C]37[/C][C]11.3[/C][C]12.3652[/C][C]13.6208[/C][C]-1.25562[/C][C]-1.06521[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]12.7277[/C][C]13.5833[/C][C]-0.855625[/C][C]-0.627708[/C][/ROW]
[ROW][C]39[/C][C]16.2[/C][C]15.2869[/C][C]13.4958[/C][C]1.79104[/C][C]0.913125[/C][/ROW]
[ROW][C]40[/C][C]11.6[/C][C]12.8485[/C][C]13.2583[/C][C]-0.409792[/C][C]-1.24854[/C][/ROW]
[ROW][C]41[/C][C]12.5[/C][C]12.7594[/C][C]13.0458[/C][C]-0.286458[/C][C]-0.259375[/C][/ROW]
[ROW][C]42[/C][C]15.6[/C][C]13.8269[/C][C]12.8417[/C][C]0.985208[/C][C]1.77313[/C][/ROW]
[ROW][C]43[/C][C]12.3[/C][C]12.9619[/C][C]12.8208[/C][C]0.141042[/C][C]-0.661875[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]11.6202[/C][C]12.9875[/C][C]-1.36729[/C][C]0.379792[/C][/ROW]
[ROW][C]45[/C][C]12.1[/C][C]13.4685[/C][C]12.9292[/C][C]0.539375[/C][C]-1.36854[/C][/ROW]
[ROW][C]46[/C][C]13.9[/C][C]14.6869[/C][C]12.9333[/C][C]1.75354[/C][C]-0.786875[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]12.721[/C][C]13.1583[/C][C]-0.437292[/C][C]-0.421042[/C][/ROW]
[ROW][C]48[/C][C]10.5[/C][C]12.706[/C][C]13.3042[/C][C]-0.598125[/C][C]-2.20604[/C][/ROW]
[ROW][C]49[/C][C]14.2[/C][C]12.1944[/C][C]13.45[/C][C]-1.25562[/C][C]2.00563[/C][/ROW]
[ROW][C]50[/C][C]13.2[/C][C]12.7694[/C][C]13.625[/C][C]-0.855625[/C][C]0.430625[/C][/ROW]
[ROW][C]51[/C][C]13.7[/C][C]15.5535[/C][C]13.7625[/C][C]1.79104[/C][C]-1.85354[/C][/ROW]
[ROW][C]52[/C][C]14.2[/C][C]13.4985[/C][C]13.9083[/C][C]-0.409792[/C][C]0.701458[/C][/ROW]
[ROW][C]53[/C][C]15.3[/C][C]13.6969[/C][C]13.9833[/C][C]-0.286458[/C][C]1.60313[/C][/ROW]
[ROW][C]54[/C][C]16.3[/C][C]15.0769[/C][C]14.0917[/C][C]0.985208[/C][C]1.22312[/C][/ROW]
[ROW][C]55[/C][C]15.1[/C][C]14.2785[/C][C]14.1375[/C][C]0.141042[/C][C]0.821458[/C][/ROW]
[ROW][C]56[/C][C]13.4[/C][C]12.7244[/C][C]14.0917[/C][C]-1.36729[/C][C]0.675625[/C][/ROW]
[ROW][C]57[/C][C]14[/C][C]14.6935[/C][C]14.1542[/C][C]0.539375[/C][C]-0.693542[/C][/ROW]
[ROW][C]58[/C][C]15.5[/C][C]15.9702[/C][C]14.2167[/C][C]1.75354[/C][C]-0.470208[/C][/ROW]
[ROW][C]59[/C][C]12.5[/C][C]13.7335[/C][C]14.1708[/C][C]-0.437292[/C][C]-1.23354[/C][/ROW]
[ROW][C]60[/C][C]12.9[/C][C]13.4727[/C][C]14.0708[/C][C]-0.598125[/C][C]-0.572708[/C][/ROW]
[ROW][C]61[/C][C]12.9[/C][C]12.7652[/C][C]14.0208[/C][C]-1.25562[/C][C]0.134792[/C][/ROW]
[ROW][C]62[/C][C]13.4[/C][C]13.1194[/C][C]13.975[/C][C]-0.855625[/C][C]0.280625[/C][/ROW]
[ROW][C]63[/C][C]15[/C][C]15.9202[/C][C]14.1292[/C][C]1.79104[/C][C]-0.920208[/C][/ROW]
[ROW][C]64[/C][C]14.4[/C][C]14.1277[/C][C]14.5375[/C][C]-0.409792[/C][C]0.272292[/C][/ROW]
[ROW][C]65[/C][C]14[/C][C]14.6635[/C][C]14.95[/C][C]-0.286458[/C][C]-0.663542[/C][/ROW]
[ROW][C]66[/C][C]15.2[/C][C]16.0727[/C][C]15.0875[/C][C]0.985208[/C][C]-0.872708[/C][/ROW]
[ROW][C]67[/C][C]15[/C][C]NA[/C][C]NA[/C][C]0.141042[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]12.4[/C][C]NA[/C][C]NA[/C][C]-1.36729[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]18.7[/C][C]NA[/C][C]NA[/C][C]0.539375[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]20.6[/C][C]NA[/C][C]NA[/C][C]1.75354[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]17.3[/C][C]NA[/C][C]NA[/C][C]-0.437292[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]NA[/C][C]NA[/C][C]-0.598125[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294634&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294634&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	8.9	NA	NA	-1.25562	NA
2	9.2	NA	NA	-0.855625	NA
3	12.8	NA	NA	1.79104	NA
4	11.1	NA	NA	-0.409792	NA
5	11.2	NA	NA	-0.286458	NA
6	13.1	NA	NA	0.985208	NA
7	12.6	11.5869	11.4458	0.141042	1.01313
8	10	10.216	11.5833	-1.36729	-0.216042
9	12.3	12.2894	11.75	0.539375	0.010625
10	12.5	13.6619	11.9083	1.75354	-1.16188
11	11.4	11.5544	11.9917	-0.437292	-0.154375
12	11.5	11.4435	12.0417	-0.598125	0.0564583
13	10.4	10.8194	12.075	-1.25562	-0.419375
14	11	11.2694	12.125	-0.855625	-0.269375
15	15	14.1119	12.3208	1.79104	0.888125
16	12.7	12.1735	12.5833	-0.409792	0.526458
17	11.6	12.5219	12.8083	-0.286458	-0.921875
18	13.9	14.031	13.0458	0.985208	-0.131042
19	12.6	13.3619	13.2208	0.141042	-0.761875
20	11.2	11.9744	13.3417	-1.36729	-0.774375
21	15.8	14.006	13.4667	0.539375	1.79396
22	15.3	15.2744	13.5208	1.75354	0.025625
23	14	13.1669	13.6042	-0.437292	0.833125
24	14.6	13.0269	13.625	-0.598125	1.57313
25	11.5	12.336	13.5917	-1.25562	-0.836042
26	12.8	12.7944	13.65	-0.855625	0.005625
27	16.2	15.4077	13.6167	1.79104	0.792292
28	12.8	13.2319	13.6417	-0.409792	-0.431875
29	13.5	13.4385	13.725	-0.286458	0.0614583
30	12.5	14.6727	13.6875	0.985208	-2.17271
31	13.2	13.791	13.65	0.141042	-0.591042
32	12	12.2452	13.6125	-1.36729	-0.245208
33	14.2	14.1227	13.5833	0.539375	0.0772917
34	17.5	15.2869	13.5333	1.75354	2.21313
35	13.8	13.0044	13.4417	-0.437292	0.795625
36	13.9	12.931	13.5292	-0.598125	0.968958
37	11.3	12.3652	13.6208	-1.25562	-1.06521
38	12.1	12.7277	13.5833	-0.855625	-0.627708
39	16.2	15.2869	13.4958	1.79104	0.913125
40	11.6	12.8485	13.2583	-0.409792	-1.24854
41	12.5	12.7594	13.0458	-0.286458	-0.259375
42	15.6	13.8269	12.8417	0.985208	1.77313
43	12.3	12.9619	12.8208	0.141042	-0.661875
44	12	11.6202	12.9875	-1.36729	0.379792
45	12.1	13.4685	12.9292	0.539375	-1.36854
46	13.9	14.6869	12.9333	1.75354	-0.786875
47	12.3	12.721	13.1583	-0.437292	-0.421042
48	10.5	12.706	13.3042	-0.598125	-2.20604
49	14.2	12.1944	13.45	-1.25562	2.00563
50	13.2	12.7694	13.625	-0.855625	0.430625
51	13.7	15.5535	13.7625	1.79104	-1.85354
52	14.2	13.4985	13.9083	-0.409792	0.701458
53	15.3	13.6969	13.9833	-0.286458	1.60313
54	16.3	15.0769	14.0917	0.985208	1.22312
55	15.1	14.2785	14.1375	0.141042	0.821458
56	13.4	12.7244	14.0917	-1.36729	0.675625
57	14	14.6935	14.1542	0.539375	-0.693542
58	15.5	15.9702	14.2167	1.75354	-0.470208
59	12.5	13.7335	14.1708	-0.437292	-1.23354
60	12.9	13.4727	14.0708	-0.598125	-0.572708
61	12.9	12.7652	14.0208	-1.25562	0.134792
62	13.4	13.1194	13.975	-0.855625	0.280625
63	15	15.9202	14.1292	1.79104	-0.920208
64	14.4	14.1277	14.5375	-0.409792	0.272292
65	14	14.6635	14.95	-0.286458	-0.663542
66	15.2	16.0727	15.0875	0.985208	-0.872708
67	15	NA	NA	0.141042	NA
68	12.4	NA	NA	-1.36729	NA
69	18.7	NA	NA	0.539375	NA
70	20.6	NA	NA	1.75354	NA
71	17.3	NA	NA	-0.437292	NA
72	11.4	NA	NA	-0.598125	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 <- '12'
par1 <- 'multiplicative'
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code