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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sat, 05 Jun 2010 20:08:05 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/05/t1275768513ewozxykw8wltn7w.htm/, Retrieved Fri, 03 May 2024 05:34:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77598, Retrieved Fri, 03 May 2024 05:34:26 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W52

Estimated Impact

121

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

-       [Classical Decomposition] [opgave 9] [2010-06-05 20:08:05] [d41d8cd98f00b204e9800998ecf8427e] [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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77598&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77598&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77598&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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	103.6	NA	NA	1.0007472369393	NA
2	104.7	NA	NA	0.99865641622814	NA
3	105.5	NA	NA	0.996650073755185	NA
4	106.6	NA	NA	0.996381252604108	NA
5	107.2	NA	NA	0.998271956179898	NA
6	107.5	NA	NA	1.00201337185898	NA
7	108.3	108.262910608017	107.741666666667	1.00483790493944	1.00034258631857
8	108.7	108.435605755290	108.258333333333	1.00163749446808	1.00243826041150
9	108.8	108.905624568176	108.666666666667	1.00219899909364	0.999030127520093
10	109.8	109.247473395573	108.979166666667	1.00246200018877	1.00505756872222
11	109.5	109.273174678851	109.2	1.00067009779168	1.00207576399071
12	109.2	108.875733002351	109.370833333333	0.995473195952773	1.00297832206229
13	110.6	109.577652664699	109.495833333333	1.0007472369393	1.00932988899141
14	110.1	109.427776808199	109.575	0.99865641622814	1.00614307638708
15	109.9	109.270222461334	109.6375	0.996650073755185	1.00576348729306
16	109.7	109.273962290803	109.670833333333	0.996381252604108	1.00389880352342
17	109.4	109.506274126451	109.695833333333	0.998271956179898	0.999029515639186
18	109.4	110.004368007251	109.783333333333	1.00201337185898	0.99450596355218
19	109.4	110.456806700468	109.925	1.00483790493944	0.990432398581522
20	109.5	110.292808609616	110.1125	1.00163749446808	0.992811783292031
21	109.5	110.626066183287	110.383333333333	1.00219899909364	0.989820968763177
22	109.9	111.014312670905	110.741666666667	1.00246200018877	0.989962441381693
23	110	111.241159204508	111.166666666667	1.00067009779168	0.988842626116232
24	110.8	111.144582328127	111.65	0.995473195952773	0.996899692986296
25	112.4	112.258821303666	112.175	1.0007472369393	1.00125761783969
26	112.8	112.552739177312	112.704166666667	0.99865641622814	1.00219684411499
27	113.7	112.870620852775	113.25	0.996650073755185	1.00734805160952
28	114.5	113.388186546347	113.8	0.996381252604108	1.00980537291862
29	114.8	114.152398189171	114.35	0.998271956179898	1.00567313364504
30	115.6	115.110461148016	114.879166666667	1.00201337185898	1.00425277465751
31	115.8	115.866184088725	115.308333333333	1.00483790493944	0.999428788569799
32	115.8	115.856070193475	115.666666666667	1.00163749446808	0.999516035772826
33	116.3	116.242556407374	115.9875	1.00219899909364	1.00049417007335
34	116.3	116.527853671943	116.241666666667	1.00246200018877	0.998044641991047
35	116.8	116.532202346582	116.454166666667	1.00067009779168	1.00229805708659
36	116.7	116.105357087958	116.633333333333	0.995473195952773	1.00512158032115
37	116.8	116.874767934049	116.7875	1.0007472369393	0.999360273090846
38	117	116.797028946282	116.954166666667	0.99865641622814	1.00173781007573
39	117.2	116.753403431779	117.145833333333	0.996650073755185	1.00382512676371
40	117.1	116.975159055722	117.4	0.996381252604108	1.00106724321032
41	117.3	117.579798572056	117.783333333333	0.998271956179898	0.99762035166369
42	117.4	118.538181890917	118.3	1.00201337185898	0.990398183329957
43	117.7	119.525468792546	118.95	1.00483790493944	0.984727365548218
44	117.9	119.946089962553	119.75	1.00163749446808	0.982941586814615
45	118.8	120.936188386462	120.670833333333	1.00219899909364	0.982336235208307
46	119.9	121.974563872969	121.675	1.00246200018877	0.982991832009092
47	122.4	122.836423962670	122.754166666667	1.00067009779168	0.996447112765167
48	123.5	123.393050443329	123.954166666667	0.995473195952773	1.00086673889888
49	125.6	125.364440327417	125.270833333333	1.0007472369393	1.00187899911624
50	127.4	126.404935884077	126.575	0.99865641622814	1.00787203528852
51	128.9	127.367726717272	127.795833333333	0.996650073755185	1.01203031036370
52	129.5	128.416937106459	128.883333333333	0.996381252604108	1.00843395675013
53	130.8	129.417640185756	129.641666666667	0.998271956179898	1.01068138634162
54	132.7	130.236688007370	129.975	1.00201337185898	1.01891411729151
55	134	130.5996198699	129.970833333333	1.00483790493944	1.02603667708595
56	132.9	129.878995116028	129.666666666667	1.00163749446808	1.02326014981309
57	133.1	129.31290168722	129.029166666667	1.00219899909364	1.02928631453913
58	131.7	128.498920724198	128.183333333333	1.00246200018877	1.024911332
59	128.8	127.360286696436	127.275	1.00067009779168	1.01130425614537
60	125.1	125.715821233886	126.2875	0.995473195952773	0.995101481835448
61	123.9	125.260195823569	125.166666666667	1.0007472369393	0.989141037065877
62	121.8	123.904133775106	124.070833333333	0.99865641622814	0.983018050237736
63	119.2	122.633638866935	123.045833333333	0.996650073755185	0.972000840074063
64	118.9	121.604180291779	122.045833333333	0.996381252604108	0.977762439701576
65	119.6	121.057112552749	121.266666666667	0.998271956179898	0.987963428814527
66	120.2	121.059915543429	120.816666666667	1.00201337185898	0.992896777272903
67	119.6	NA	NA	1.00483790493944	NA
68	121	NA	NA	1.00163749446808	NA
69	120.4	NA	NA	1.00219899909364	NA
70	120.4	NA	NA	1.00246200018877	NA
71	121.4	NA	NA	1.00067009779168	NA
72	121.7	NA	NA	0.995473195952773	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 103.6 & NA & NA & 1.0007472369393 & NA \tabularnewline
2 & 104.7 & NA & NA & 0.99865641622814 & NA \tabularnewline
3 & 105.5 & NA & NA & 0.996650073755185 & NA \tabularnewline
4 & 106.6 & NA & NA & 0.996381252604108 & NA \tabularnewline
5 & 107.2 & NA & NA & 0.998271956179898 & NA \tabularnewline
6 & 107.5 & NA & NA & 1.00201337185898 & NA \tabularnewline
7 & 108.3 & 108.262910608017 & 107.741666666667 & 1.00483790493944 & 1.00034258631857 \tabularnewline
8 & 108.7 & 108.435605755290 & 108.258333333333 & 1.00163749446808 & 1.00243826041150 \tabularnewline
9 & 108.8 & 108.905624568176 & 108.666666666667 & 1.00219899909364 & 0.999030127520093 \tabularnewline
10 & 109.8 & 109.247473395573 & 108.979166666667 & 1.00246200018877 & 1.00505756872222 \tabularnewline
11 & 109.5 & 109.273174678851 & 109.2 & 1.00067009779168 & 1.00207576399071 \tabularnewline
12 & 109.2 & 108.875733002351 & 109.370833333333 & 0.995473195952773 & 1.00297832206229 \tabularnewline
13 & 110.6 & 109.577652664699 & 109.495833333333 & 1.0007472369393 & 1.00932988899141 \tabularnewline
14 & 110.1 & 109.427776808199 & 109.575 & 0.99865641622814 & 1.00614307638708 \tabularnewline
15 & 109.9 & 109.270222461334 & 109.6375 & 0.996650073755185 & 1.00576348729306 \tabularnewline
16 & 109.7 & 109.273962290803 & 109.670833333333 & 0.996381252604108 & 1.00389880352342 \tabularnewline
17 & 109.4 & 109.506274126451 & 109.695833333333 & 0.998271956179898 & 0.999029515639186 \tabularnewline
18 & 109.4 & 110.004368007251 & 109.783333333333 & 1.00201337185898 & 0.99450596355218 \tabularnewline
19 & 109.4 & 110.456806700468 & 109.925 & 1.00483790493944 & 0.990432398581522 \tabularnewline
20 & 109.5 & 110.292808609616 & 110.1125 & 1.00163749446808 & 0.992811783292031 \tabularnewline
21 & 109.5 & 110.626066183287 & 110.383333333333 & 1.00219899909364 & 0.989820968763177 \tabularnewline
22 & 109.9 & 111.014312670905 & 110.741666666667 & 1.00246200018877 & 0.989962441381693 \tabularnewline
23 & 110 & 111.241159204508 & 111.166666666667 & 1.00067009779168 & 0.988842626116232 \tabularnewline
24 & 110.8 & 111.144582328127 & 111.65 & 0.995473195952773 & 0.996899692986296 \tabularnewline
25 & 112.4 & 112.258821303666 & 112.175 & 1.0007472369393 & 1.00125761783969 \tabularnewline
26 & 112.8 & 112.552739177312 & 112.704166666667 & 0.99865641622814 & 1.00219684411499 \tabularnewline
27 & 113.7 & 112.870620852775 & 113.25 & 0.996650073755185 & 1.00734805160952 \tabularnewline
28 & 114.5 & 113.388186546347 & 113.8 & 0.996381252604108 & 1.00980537291862 \tabularnewline
29 & 114.8 & 114.152398189171 & 114.35 & 0.998271956179898 & 1.00567313364504 \tabularnewline
30 & 115.6 & 115.110461148016 & 114.879166666667 & 1.00201337185898 & 1.00425277465751 \tabularnewline
31 & 115.8 & 115.866184088725 & 115.308333333333 & 1.00483790493944 & 0.999428788569799 \tabularnewline
32 & 115.8 & 115.856070193475 & 115.666666666667 & 1.00163749446808 & 0.999516035772826 \tabularnewline
33 & 116.3 & 116.242556407374 & 115.9875 & 1.00219899909364 & 1.00049417007335 \tabularnewline
34 & 116.3 & 116.527853671943 & 116.241666666667 & 1.00246200018877 & 0.998044641991047 \tabularnewline
35 & 116.8 & 116.532202346582 & 116.454166666667 & 1.00067009779168 & 1.00229805708659 \tabularnewline
36 & 116.7 & 116.105357087958 & 116.633333333333 & 0.995473195952773 & 1.00512158032115 \tabularnewline
37 & 116.8 & 116.874767934049 & 116.7875 & 1.0007472369393 & 0.999360273090846 \tabularnewline
38 & 117 & 116.797028946282 & 116.954166666667 & 0.99865641622814 & 1.00173781007573 \tabularnewline
39 & 117.2 & 116.753403431779 & 117.145833333333 & 0.996650073755185 & 1.00382512676371 \tabularnewline
40 & 117.1 & 116.975159055722 & 117.4 & 0.996381252604108 & 1.00106724321032 \tabularnewline
41 & 117.3 & 117.579798572056 & 117.783333333333 & 0.998271956179898 & 0.99762035166369 \tabularnewline
42 & 117.4 & 118.538181890917 & 118.3 & 1.00201337185898 & 0.990398183329957 \tabularnewline
43 & 117.7 & 119.525468792546 & 118.95 & 1.00483790493944 & 0.984727365548218 \tabularnewline
44 & 117.9 & 119.946089962553 & 119.75 & 1.00163749446808 & 0.982941586814615 \tabularnewline
45 & 118.8 & 120.936188386462 & 120.670833333333 & 1.00219899909364 & 0.982336235208307 \tabularnewline
46 & 119.9 & 121.974563872969 & 121.675 & 1.00246200018877 & 0.982991832009092 \tabularnewline
47 & 122.4 & 122.836423962670 & 122.754166666667 & 1.00067009779168 & 0.996447112765167 \tabularnewline
48 & 123.5 & 123.393050443329 & 123.954166666667 & 0.995473195952773 & 1.00086673889888 \tabularnewline
49 & 125.6 & 125.364440327417 & 125.270833333333 & 1.0007472369393 & 1.00187899911624 \tabularnewline
50 & 127.4 & 126.404935884077 & 126.575 & 0.99865641622814 & 1.00787203528852 \tabularnewline
51 & 128.9 & 127.367726717272 & 127.795833333333 & 0.996650073755185 & 1.01203031036370 \tabularnewline
52 & 129.5 & 128.416937106459 & 128.883333333333 & 0.996381252604108 & 1.00843395675013 \tabularnewline
53 & 130.8 & 129.417640185756 & 129.641666666667 & 0.998271956179898 & 1.01068138634162 \tabularnewline
54 & 132.7 & 130.236688007370 & 129.975 & 1.00201337185898 & 1.01891411729151 \tabularnewline
55 & 134 & 130.5996198699 & 129.970833333333 & 1.00483790493944 & 1.02603667708595 \tabularnewline
56 & 132.9 & 129.878995116028 & 129.666666666667 & 1.00163749446808 & 1.02326014981309 \tabularnewline
57 & 133.1 & 129.31290168722 & 129.029166666667 & 1.00219899909364 & 1.02928631453913 \tabularnewline
58 & 131.7 & 128.498920724198 & 128.183333333333 & 1.00246200018877 & 1.024911332 \tabularnewline
59 & 128.8 & 127.360286696436 & 127.275 & 1.00067009779168 & 1.01130425614537 \tabularnewline
60 & 125.1 & 125.715821233886 & 126.2875 & 0.995473195952773 & 0.995101481835448 \tabularnewline
61 & 123.9 & 125.260195823569 & 125.166666666667 & 1.0007472369393 & 0.989141037065877 \tabularnewline
62 & 121.8 & 123.904133775106 & 124.070833333333 & 0.99865641622814 & 0.983018050237736 \tabularnewline
63 & 119.2 & 122.633638866935 & 123.045833333333 & 0.996650073755185 & 0.972000840074063 \tabularnewline
64 & 118.9 & 121.604180291779 & 122.045833333333 & 0.996381252604108 & 0.977762439701576 \tabularnewline
65 & 119.6 & 121.057112552749 & 121.266666666667 & 0.998271956179898 & 0.987963428814527 \tabularnewline
66 & 120.2 & 121.059915543429 & 120.816666666667 & 1.00201337185898 & 0.992896777272903 \tabularnewline
67 & 119.6 & NA & NA & 1.00483790493944 & NA \tabularnewline
68 & 121 & NA & NA & 1.00163749446808 & NA \tabularnewline
69 & 120.4 & NA & NA & 1.00219899909364 & NA \tabularnewline
70 & 120.4 & NA & NA & 1.00246200018877 & NA \tabularnewline
71 & 121.4 & NA & NA & 1.00067009779168 & NA \tabularnewline
72 & 121.7 & NA & NA & 0.995473195952773 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77598&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]103.6[/C][C]NA[/C][C]NA[/C][C]1.0007472369393[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]104.7[/C][C]NA[/C][C]NA[/C][C]0.99865641622814[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]105.5[/C][C]NA[/C][C]NA[/C][C]0.996650073755185[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]106.6[/C][C]NA[/C][C]NA[/C][C]0.996381252604108[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]107.2[/C][C]NA[/C][C]NA[/C][C]0.998271956179898[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]107.5[/C][C]NA[/C][C]NA[/C][C]1.00201337185898[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]108.3[/C][C]108.262910608017[/C][C]107.741666666667[/C][C]1.00483790493944[/C][C]1.00034258631857[/C][/ROW]
[ROW][C]8[/C][C]108.7[/C][C]108.435605755290[/C][C]108.258333333333[/C][C]1.00163749446808[/C][C]1.00243826041150[/C][/ROW]
[ROW][C]9[/C][C]108.8[/C][C]108.905624568176[/C][C]108.666666666667[/C][C]1.00219899909364[/C][C]0.999030127520093[/C][/ROW]
[ROW][C]10[/C][C]109.8[/C][C]109.247473395573[/C][C]108.979166666667[/C][C]1.00246200018877[/C][C]1.00505756872222[/C][/ROW]
[ROW][C]11[/C][C]109.5[/C][C]109.273174678851[/C][C]109.2[/C][C]1.00067009779168[/C][C]1.00207576399071[/C][/ROW]
[ROW][C]12[/C][C]109.2[/C][C]108.875733002351[/C][C]109.370833333333[/C][C]0.995473195952773[/C][C]1.00297832206229[/C][/ROW]
[ROW][C]13[/C][C]110.6[/C][C]109.577652664699[/C][C]109.495833333333[/C][C]1.0007472369393[/C][C]1.00932988899141[/C][/ROW]
[ROW][C]14[/C][C]110.1[/C][C]109.427776808199[/C][C]109.575[/C][C]0.99865641622814[/C][C]1.00614307638708[/C][/ROW]
[ROW][C]15[/C][C]109.9[/C][C]109.270222461334[/C][C]109.6375[/C][C]0.996650073755185[/C][C]1.00576348729306[/C][/ROW]
[ROW][C]16[/C][C]109.7[/C][C]109.273962290803[/C][C]109.670833333333[/C][C]0.996381252604108[/C][C]1.00389880352342[/C][/ROW]
[ROW][C]17[/C][C]109.4[/C][C]109.506274126451[/C][C]109.695833333333[/C][C]0.998271956179898[/C][C]0.999029515639186[/C][/ROW]
[ROW][C]18[/C][C]109.4[/C][C]110.004368007251[/C][C]109.783333333333[/C][C]1.00201337185898[/C][C]0.99450596355218[/C][/ROW]
[ROW][C]19[/C][C]109.4[/C][C]110.456806700468[/C][C]109.925[/C][C]1.00483790493944[/C][C]0.990432398581522[/C][/ROW]
[ROW][C]20[/C][C]109.5[/C][C]110.292808609616[/C][C]110.1125[/C][C]1.00163749446808[/C][C]0.992811783292031[/C][/ROW]
[ROW][C]21[/C][C]109.5[/C][C]110.626066183287[/C][C]110.383333333333[/C][C]1.00219899909364[/C][C]0.989820968763177[/C][/ROW]
[ROW][C]22[/C][C]109.9[/C][C]111.014312670905[/C][C]110.741666666667[/C][C]1.00246200018877[/C][C]0.989962441381693[/C][/ROW]
[ROW][C]23[/C][C]110[/C][C]111.241159204508[/C][C]111.166666666667[/C][C]1.00067009779168[/C][C]0.988842626116232[/C][/ROW]
[ROW][C]24[/C][C]110.8[/C][C]111.144582328127[/C][C]111.65[/C][C]0.995473195952773[/C][C]0.996899692986296[/C][/ROW]
[ROW][C]25[/C][C]112.4[/C][C]112.258821303666[/C][C]112.175[/C][C]1.0007472369393[/C][C]1.00125761783969[/C][/ROW]
[ROW][C]26[/C][C]112.8[/C][C]112.552739177312[/C][C]112.704166666667[/C][C]0.99865641622814[/C][C]1.00219684411499[/C][/ROW]
[ROW][C]27[/C][C]113.7[/C][C]112.870620852775[/C][C]113.25[/C][C]0.996650073755185[/C][C]1.00734805160952[/C][/ROW]
[ROW][C]28[/C][C]114.5[/C][C]113.388186546347[/C][C]113.8[/C][C]0.996381252604108[/C][C]1.00980537291862[/C][/ROW]
[ROW][C]29[/C][C]114.8[/C][C]114.152398189171[/C][C]114.35[/C][C]0.998271956179898[/C][C]1.00567313364504[/C][/ROW]
[ROW][C]30[/C][C]115.6[/C][C]115.110461148016[/C][C]114.879166666667[/C][C]1.00201337185898[/C][C]1.00425277465751[/C][/ROW]
[ROW][C]31[/C][C]115.8[/C][C]115.866184088725[/C][C]115.308333333333[/C][C]1.00483790493944[/C][C]0.999428788569799[/C][/ROW]
[ROW][C]32[/C][C]115.8[/C][C]115.856070193475[/C][C]115.666666666667[/C][C]1.00163749446808[/C][C]0.999516035772826[/C][/ROW]
[ROW][C]33[/C][C]116.3[/C][C]116.242556407374[/C][C]115.9875[/C][C]1.00219899909364[/C][C]1.00049417007335[/C][/ROW]
[ROW][C]34[/C][C]116.3[/C][C]116.527853671943[/C][C]116.241666666667[/C][C]1.00246200018877[/C][C]0.998044641991047[/C][/ROW]
[ROW][C]35[/C][C]116.8[/C][C]116.532202346582[/C][C]116.454166666667[/C][C]1.00067009779168[/C][C]1.00229805708659[/C][/ROW]
[ROW][C]36[/C][C]116.7[/C][C]116.105357087958[/C][C]116.633333333333[/C][C]0.995473195952773[/C][C]1.00512158032115[/C][/ROW]
[ROW][C]37[/C][C]116.8[/C][C]116.874767934049[/C][C]116.7875[/C][C]1.0007472369393[/C][C]0.999360273090846[/C][/ROW]
[ROW][C]38[/C][C]117[/C][C]116.797028946282[/C][C]116.954166666667[/C][C]0.99865641622814[/C][C]1.00173781007573[/C][/ROW]
[ROW][C]39[/C][C]117.2[/C][C]116.753403431779[/C][C]117.145833333333[/C][C]0.996650073755185[/C][C]1.00382512676371[/C][/ROW]
[ROW][C]40[/C][C]117.1[/C][C]116.975159055722[/C][C]117.4[/C][C]0.996381252604108[/C][C]1.00106724321032[/C][/ROW]
[ROW][C]41[/C][C]117.3[/C][C]117.579798572056[/C][C]117.783333333333[/C][C]0.998271956179898[/C][C]0.99762035166369[/C][/ROW]
[ROW][C]42[/C][C]117.4[/C][C]118.538181890917[/C][C]118.3[/C][C]1.00201337185898[/C][C]0.990398183329957[/C][/ROW]
[ROW][C]43[/C][C]117.7[/C][C]119.525468792546[/C][C]118.95[/C][C]1.00483790493944[/C][C]0.984727365548218[/C][/ROW]
[ROW][C]44[/C][C]117.9[/C][C]119.946089962553[/C][C]119.75[/C][C]1.00163749446808[/C][C]0.982941586814615[/C][/ROW]
[ROW][C]45[/C][C]118.8[/C][C]120.936188386462[/C][C]120.670833333333[/C][C]1.00219899909364[/C][C]0.982336235208307[/C][/ROW]
[ROW][C]46[/C][C]119.9[/C][C]121.974563872969[/C][C]121.675[/C][C]1.00246200018877[/C][C]0.982991832009092[/C][/ROW]
[ROW][C]47[/C][C]122.4[/C][C]122.836423962670[/C][C]122.754166666667[/C][C]1.00067009779168[/C][C]0.996447112765167[/C][/ROW]
[ROW][C]48[/C][C]123.5[/C][C]123.393050443329[/C][C]123.954166666667[/C][C]0.995473195952773[/C][C]1.00086673889888[/C][/ROW]
[ROW][C]49[/C][C]125.6[/C][C]125.364440327417[/C][C]125.270833333333[/C][C]1.0007472369393[/C][C]1.00187899911624[/C][/ROW]
[ROW][C]50[/C][C]127.4[/C][C]126.404935884077[/C][C]126.575[/C][C]0.99865641622814[/C][C]1.00787203528852[/C][/ROW]
[ROW][C]51[/C][C]128.9[/C][C]127.367726717272[/C][C]127.795833333333[/C][C]0.996650073755185[/C][C]1.01203031036370[/C][/ROW]
[ROW][C]52[/C][C]129.5[/C][C]128.416937106459[/C][C]128.883333333333[/C][C]0.996381252604108[/C][C]1.00843395675013[/C][/ROW]
[ROW][C]53[/C][C]130.8[/C][C]129.417640185756[/C][C]129.641666666667[/C][C]0.998271956179898[/C][C]1.01068138634162[/C][/ROW]
[ROW][C]54[/C][C]132.7[/C][C]130.236688007370[/C][C]129.975[/C][C]1.00201337185898[/C][C]1.01891411729151[/C][/ROW]
[ROW][C]55[/C][C]134[/C][C]130.5996198699[/C][C]129.970833333333[/C][C]1.00483790493944[/C][C]1.02603667708595[/C][/ROW]
[ROW][C]56[/C][C]132.9[/C][C]129.878995116028[/C][C]129.666666666667[/C][C]1.00163749446808[/C][C]1.02326014981309[/C][/ROW]
[ROW][C]57[/C][C]133.1[/C][C]129.31290168722[/C][C]129.029166666667[/C][C]1.00219899909364[/C][C]1.02928631453913[/C][/ROW]
[ROW][C]58[/C][C]131.7[/C][C]128.498920724198[/C][C]128.183333333333[/C][C]1.00246200018877[/C][C]1.024911332[/C][/ROW]
[ROW][C]59[/C][C]128.8[/C][C]127.360286696436[/C][C]127.275[/C][C]1.00067009779168[/C][C]1.01130425614537[/C][/ROW]
[ROW][C]60[/C][C]125.1[/C][C]125.715821233886[/C][C]126.2875[/C][C]0.995473195952773[/C][C]0.995101481835448[/C][/ROW]
[ROW][C]61[/C][C]123.9[/C][C]125.260195823569[/C][C]125.166666666667[/C][C]1.0007472369393[/C][C]0.989141037065877[/C][/ROW]
[ROW][C]62[/C][C]121.8[/C][C]123.904133775106[/C][C]124.070833333333[/C][C]0.99865641622814[/C][C]0.983018050237736[/C][/ROW]
[ROW][C]63[/C][C]119.2[/C][C]122.633638866935[/C][C]123.045833333333[/C][C]0.996650073755185[/C][C]0.972000840074063[/C][/ROW]
[ROW][C]64[/C][C]118.9[/C][C]121.604180291779[/C][C]122.045833333333[/C][C]0.996381252604108[/C][C]0.977762439701576[/C][/ROW]
[ROW][C]65[/C][C]119.6[/C][C]121.057112552749[/C][C]121.266666666667[/C][C]0.998271956179898[/C][C]0.987963428814527[/C][/ROW]
[ROW][C]66[/C][C]120.2[/C][C]121.059915543429[/C][C]120.816666666667[/C][C]1.00201337185898[/C][C]0.992896777272903[/C][/ROW]
[ROW][C]67[/C][C]119.6[/C][C]NA[/C][C]NA[/C][C]1.00483790493944[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]121[/C][C]NA[/C][C]NA[/C][C]1.00163749446808[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]120.4[/C][C]NA[/C][C]NA[/C][C]1.00219899909364[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]120.4[/C][C]NA[/C][C]NA[/C][C]1.00246200018877[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]121.4[/C][C]NA[/C][C]NA[/C][C]1.00067009779168[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]121.7[/C][C]NA[/C][C]NA[/C][C]0.995473195952773[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77598&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77598&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	103.6	NA	NA	1.0007472369393	NA
2	104.7	NA	NA	0.99865641622814	NA
3	105.5	NA	NA	0.996650073755185	NA
4	106.6	NA	NA	0.996381252604108	NA
5	107.2	NA	NA	0.998271956179898	NA
6	107.5	NA	NA	1.00201337185898	NA
7	108.3	108.262910608017	107.741666666667	1.00483790493944	1.00034258631857
8	108.7	108.435605755290	108.258333333333	1.00163749446808	1.00243826041150
9	108.8	108.905624568176	108.666666666667	1.00219899909364	0.999030127520093
10	109.8	109.247473395573	108.979166666667	1.00246200018877	1.00505756872222
11	109.5	109.273174678851	109.2	1.00067009779168	1.00207576399071
12	109.2	108.875733002351	109.370833333333	0.995473195952773	1.00297832206229
13	110.6	109.577652664699	109.495833333333	1.0007472369393	1.00932988899141
14	110.1	109.427776808199	109.575	0.99865641622814	1.00614307638708
15	109.9	109.270222461334	109.6375	0.996650073755185	1.00576348729306
16	109.7	109.273962290803	109.670833333333	0.996381252604108	1.00389880352342
17	109.4	109.506274126451	109.695833333333	0.998271956179898	0.999029515639186
18	109.4	110.004368007251	109.783333333333	1.00201337185898	0.99450596355218
19	109.4	110.456806700468	109.925	1.00483790493944	0.990432398581522
20	109.5	110.292808609616	110.1125	1.00163749446808	0.992811783292031
21	109.5	110.626066183287	110.383333333333	1.00219899909364	0.989820968763177
22	109.9	111.014312670905	110.741666666667	1.00246200018877	0.989962441381693
23	110	111.241159204508	111.166666666667	1.00067009779168	0.988842626116232
24	110.8	111.144582328127	111.65	0.995473195952773	0.996899692986296
25	112.4	112.258821303666	112.175	1.0007472369393	1.00125761783969
26	112.8	112.552739177312	112.704166666667	0.99865641622814	1.00219684411499
27	113.7	112.870620852775	113.25	0.996650073755185	1.00734805160952
28	114.5	113.388186546347	113.8	0.996381252604108	1.00980537291862
29	114.8	114.152398189171	114.35	0.998271956179898	1.00567313364504
30	115.6	115.110461148016	114.879166666667	1.00201337185898	1.00425277465751
31	115.8	115.866184088725	115.308333333333	1.00483790493944	0.999428788569799
32	115.8	115.856070193475	115.666666666667	1.00163749446808	0.999516035772826
33	116.3	116.242556407374	115.9875	1.00219899909364	1.00049417007335
34	116.3	116.527853671943	116.241666666667	1.00246200018877	0.998044641991047
35	116.8	116.532202346582	116.454166666667	1.00067009779168	1.00229805708659
36	116.7	116.105357087958	116.633333333333	0.995473195952773	1.00512158032115
37	116.8	116.874767934049	116.7875	1.0007472369393	0.999360273090846
38	117	116.797028946282	116.954166666667	0.99865641622814	1.00173781007573
39	117.2	116.753403431779	117.145833333333	0.996650073755185	1.00382512676371
40	117.1	116.975159055722	117.4	0.996381252604108	1.00106724321032
41	117.3	117.579798572056	117.783333333333	0.998271956179898	0.99762035166369
42	117.4	118.538181890917	118.3	1.00201337185898	0.990398183329957
43	117.7	119.525468792546	118.95	1.00483790493944	0.984727365548218
44	117.9	119.946089962553	119.75	1.00163749446808	0.982941586814615
45	118.8	120.936188386462	120.670833333333	1.00219899909364	0.982336235208307
46	119.9	121.974563872969	121.675	1.00246200018877	0.982991832009092
47	122.4	122.836423962670	122.754166666667	1.00067009779168	0.996447112765167
48	123.5	123.393050443329	123.954166666667	0.995473195952773	1.00086673889888
49	125.6	125.364440327417	125.270833333333	1.0007472369393	1.00187899911624
50	127.4	126.404935884077	126.575	0.99865641622814	1.00787203528852
51	128.9	127.367726717272	127.795833333333	0.996650073755185	1.01203031036370
52	129.5	128.416937106459	128.883333333333	0.996381252604108	1.00843395675013
53	130.8	129.417640185756	129.641666666667	0.998271956179898	1.01068138634162
54	132.7	130.236688007370	129.975	1.00201337185898	1.01891411729151
55	134	130.5996198699	129.970833333333	1.00483790493944	1.02603667708595
56	132.9	129.878995116028	129.666666666667	1.00163749446808	1.02326014981309
57	133.1	129.31290168722	129.029166666667	1.00219899909364	1.02928631453913
58	131.7	128.498920724198	128.183333333333	1.00246200018877	1.024911332
59	128.8	127.360286696436	127.275	1.00067009779168	1.01130425614537
60	125.1	125.715821233886	126.2875	0.995473195952773	0.995101481835448
61	123.9	125.260195823569	125.166666666667	1.0007472369393	0.989141037065877
62	121.8	123.904133775106	124.070833333333	0.99865641622814	0.983018050237736
63	119.2	122.633638866935	123.045833333333	0.996650073755185	0.972000840074063
64	118.9	121.604180291779	122.045833333333	0.996381252604108	0.977762439701576
65	119.6	121.057112552749	121.266666666667	0.998271956179898	0.987963428814527
66	120.2	121.059915543429	120.816666666667	1.00201337185898	0.992896777272903
67	119.6	NA	NA	1.00483790493944	NA
68	121	NA	NA	1.00163749446808	NA
69	120.4	NA	NA	1.00219899909364	NA
70	120.4	NA	NA	1.00246200018877	NA
71	121.4	NA	NA	1.00067009779168	NA
72	121.7	NA	NA	0.995473195952773	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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