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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 25 May 2008 12:12:36 -0600

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/2008/May/25/t1211739203b7un89jlp86jju7.htm/, Retrieved Mon, 20 May 2024 04:52:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13192, Retrieved Mon, 20 May 2024 04:52:55 +0000

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No (this computation is public)

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Estimated Impact

158

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

-       [Classical Decomposition] [Classical Decompo...] [2008-05-25 18:12:36] [6461440fa2a8ea0ebac8d11789a457eb] [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	5 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13192&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13192&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13192&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	5 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	48.04	NA	NA	0.998743086385678	NA
2	48.06	NA	NA	0.998075285228142	NA
3	48.04	NA	NA	0.998586591685917	NA
4	48.09	NA	NA	1.00175252991468	NA
5	48.12	NA	NA	1.00148704763172	NA
6	48.16	NA	NA	1.00108268941237	NA
7	48.16	48.1268286029633	48.1170833333333	1.00020253242622	1.00068924959320
8	48.16	48.0947714213024	48.1254166666667	0.999363221193978	1.00135625093477
9	48.08	48.155967434234	48.13875	1.00035766267786	0.998422471019033
10	48.13	48.1832331800599	48.1641666666667	1.00039586511535	0.998895192859703
11	48.16	48.2095160337659	48.19625	1.00027525033101	0.998972899173449
12	48.15	48.2123987556028	48.2279166666667	0.99967823799707	0.998705752934651
13	48.15	48.1980929201148	48.25875	0.998743086385678	0.999002182094745
14	48.15	48.1966396589648	48.2895833333333	0.998075285228142	0.999032304756207
15	48.27	48.2616899761804	48.33	0.998586591685917	1.00017218675566
16	48.47	48.4610308252852	48.37625	1.00175252991468	1.00018508014712
17	48.51	48.4907509875183	48.41875	1.00148704763172	1.00039696255656
18	48.53	48.5137184822853	48.46125	1.00108268941237	1.00033560646811
19	48.53	48.5135735821681	48.50375	1.00020253242622	1.00033859426587
20	48.53	48.5157531782303	48.5466666666667	0.999363221193978	1.00029365352151
21	48.68	48.6040443039752	48.5866666666667	1.00035766267786	1.00156274435826
22	48.64	48.6446657728444	48.6254166666667	1.00039586511535	0.999904084594472
23	48.67	48.6800621827758	48.6666666666667	1.00027525033101	0.999793299713998
24	48.66	48.6930773750398	48.70875	0.99967823799707	0.999320696558465
25	48.66	48.6899738901598	48.75125	0.998743086385678	0.999384392971182
26	48.67	48.6998359486006	48.79375	0.998075285228142	0.999387350121012
27	48.71	48.7618154275164	48.8308333333333	0.998586591685917	0.998937376981105
28	48.96	48.9527243587183	48.8670833333333	1.00175252991468	1.00014862587072
29	49.01	48.9818969271277	48.9091666666667	1.00148704763172	1.00057374406945
30	49.04	49.0088372957572	48.9558333333333	1.00108268941237	1.00063585887694
31	49.04	49.0157586036571	49.0058333333333	1.00020253242622	1.00049456332073
32	49.04	49.0241792170128	49.0554166666667	0.999363221193978	1.00032271387793
33	49.06	49.1217293944109	49.1041666666667	1.00035766267786	0.998743338331692
34	49.13	49.1673726123672	49.1479166666667	1.00039586511535	0.999239889984324
35	49.19	49.1985381875307	49.185	1.00027525033101	0.999826454446713
36	49.26	49.2037463416166	49.2195833333333	0.99967823799707	1.00114327998508
37	49.26	49.1918422910686	49.25375	0.998743086385678	1.00138554902108
38	49.26	49.1934673500864	49.2883333333333	0.998075285228142	1.00135246920979
39	49.29	49.2573640236405	49.3270833333333	0.998586591685917	1.00066256035024
40	49.43	49.4577745925503	49.37125	1.00175252991468	0.999438418069169
41	49.43	49.4893170312611	49.4158333333333	1.00148704763172	0.998801417460992
42	49.45	49.5093786404634	49.4558333333333	1.00108268941237	0.998800658741961
43	49.45	49.5025238361045	49.4925	1.00020253242622	0.998938966500407
44	49.46	49.5017915564751	49.5333333333333	0.999363221193978	0.999155756687566
45	49.57	49.5964824684901	49.57875	1.00035766267786	0.99946604139705
46	49.68	49.6488131224539	49.6291666666667	1.00039586511535	1.00062814950821
47	49.71	49.702426844885	49.68875	1.00027525033101	1.00015236992630
48	49.7	49.7344088729534	49.7504166666667	0.99967823799707	0.999308147543459
49	49.7	49.7469769899179	49.8095833333333	0.998743086385678	0.999055681515533
50	49.8	49.777757256647	49.87375	0.998075285228142	1.0004468410105
51	49.84	49.8706626220343	49.94125	0.998586591685917	0.999385157115984
52	50.09	50.1176790716316	50.03	1.00175252991468	0.99944771840707
53	50.2	50.2153951407941	50.1408333333333	1.00148704763172	0.999693417909967
54	50.16	50.3060736141207	50.2516666666667	1.00108268941237	0.99709630262061
55	50.16	NA	NA	1.00020253242622	NA
56	50.29	NA	NA	0.999363221193978	NA
57	50.36	NA	NA	1.00035766267786	NA
58	51.02	NA	NA	1.00039586511535	NA
59	51.03	NA	NA	1.00027525033101	NA
60	51.04	NA	NA	0.99967823799707	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 48.04 & NA & NA & 0.998743086385678 & NA \tabularnewline
2 & 48.06 & NA & NA & 0.998075285228142 & NA \tabularnewline
3 & 48.04 & NA & NA & 0.998586591685917 & NA \tabularnewline
4 & 48.09 & NA & NA & 1.00175252991468 & NA \tabularnewline
5 & 48.12 & NA & NA & 1.00148704763172 & NA \tabularnewline
6 & 48.16 & NA & NA & 1.00108268941237 & NA \tabularnewline
7 & 48.16 & 48.1268286029633 & 48.1170833333333 & 1.00020253242622 & 1.00068924959320 \tabularnewline
8 & 48.16 & 48.0947714213024 & 48.1254166666667 & 0.999363221193978 & 1.00135625093477 \tabularnewline
9 & 48.08 & 48.155967434234 & 48.13875 & 1.00035766267786 & 0.998422471019033 \tabularnewline
10 & 48.13 & 48.1832331800599 & 48.1641666666667 & 1.00039586511535 & 0.998895192859703 \tabularnewline
11 & 48.16 & 48.2095160337659 & 48.19625 & 1.00027525033101 & 0.998972899173449 \tabularnewline
12 & 48.15 & 48.2123987556028 & 48.2279166666667 & 0.99967823799707 & 0.998705752934651 \tabularnewline
13 & 48.15 & 48.1980929201148 & 48.25875 & 0.998743086385678 & 0.999002182094745 \tabularnewline
14 & 48.15 & 48.1966396589648 & 48.2895833333333 & 0.998075285228142 & 0.999032304756207 \tabularnewline
15 & 48.27 & 48.2616899761804 & 48.33 & 0.998586591685917 & 1.00017218675566 \tabularnewline
16 & 48.47 & 48.4610308252852 & 48.37625 & 1.00175252991468 & 1.00018508014712 \tabularnewline
17 & 48.51 & 48.4907509875183 & 48.41875 & 1.00148704763172 & 1.00039696255656 \tabularnewline
18 & 48.53 & 48.5137184822853 & 48.46125 & 1.00108268941237 & 1.00033560646811 \tabularnewline
19 & 48.53 & 48.5135735821681 & 48.50375 & 1.00020253242622 & 1.00033859426587 \tabularnewline
20 & 48.53 & 48.5157531782303 & 48.5466666666667 & 0.999363221193978 & 1.00029365352151 \tabularnewline
21 & 48.68 & 48.6040443039752 & 48.5866666666667 & 1.00035766267786 & 1.00156274435826 \tabularnewline
22 & 48.64 & 48.6446657728444 & 48.6254166666667 & 1.00039586511535 & 0.999904084594472 \tabularnewline
23 & 48.67 & 48.6800621827758 & 48.6666666666667 & 1.00027525033101 & 0.999793299713998 \tabularnewline
24 & 48.66 & 48.6930773750398 & 48.70875 & 0.99967823799707 & 0.999320696558465 \tabularnewline
25 & 48.66 & 48.6899738901598 & 48.75125 & 0.998743086385678 & 0.999384392971182 \tabularnewline
26 & 48.67 & 48.6998359486006 & 48.79375 & 0.998075285228142 & 0.999387350121012 \tabularnewline
27 & 48.71 & 48.7618154275164 & 48.8308333333333 & 0.998586591685917 & 0.998937376981105 \tabularnewline
28 & 48.96 & 48.9527243587183 & 48.8670833333333 & 1.00175252991468 & 1.00014862587072 \tabularnewline
29 & 49.01 & 48.9818969271277 & 48.9091666666667 & 1.00148704763172 & 1.00057374406945 \tabularnewline
30 & 49.04 & 49.0088372957572 & 48.9558333333333 & 1.00108268941237 & 1.00063585887694 \tabularnewline
31 & 49.04 & 49.0157586036571 & 49.0058333333333 & 1.00020253242622 & 1.00049456332073 \tabularnewline
32 & 49.04 & 49.0241792170128 & 49.0554166666667 & 0.999363221193978 & 1.00032271387793 \tabularnewline
33 & 49.06 & 49.1217293944109 & 49.1041666666667 & 1.00035766267786 & 0.998743338331692 \tabularnewline
34 & 49.13 & 49.1673726123672 & 49.1479166666667 & 1.00039586511535 & 0.999239889984324 \tabularnewline
35 & 49.19 & 49.1985381875307 & 49.185 & 1.00027525033101 & 0.999826454446713 \tabularnewline
36 & 49.26 & 49.2037463416166 & 49.2195833333333 & 0.99967823799707 & 1.00114327998508 \tabularnewline
37 & 49.26 & 49.1918422910686 & 49.25375 & 0.998743086385678 & 1.00138554902108 \tabularnewline
38 & 49.26 & 49.1934673500864 & 49.2883333333333 & 0.998075285228142 & 1.00135246920979 \tabularnewline
39 & 49.29 & 49.2573640236405 & 49.3270833333333 & 0.998586591685917 & 1.00066256035024 \tabularnewline
40 & 49.43 & 49.4577745925503 & 49.37125 & 1.00175252991468 & 0.999438418069169 \tabularnewline
41 & 49.43 & 49.4893170312611 & 49.4158333333333 & 1.00148704763172 & 0.998801417460992 \tabularnewline
42 & 49.45 & 49.5093786404634 & 49.4558333333333 & 1.00108268941237 & 0.998800658741961 \tabularnewline
43 & 49.45 & 49.5025238361045 & 49.4925 & 1.00020253242622 & 0.998938966500407 \tabularnewline
44 & 49.46 & 49.5017915564751 & 49.5333333333333 & 0.999363221193978 & 0.999155756687566 \tabularnewline
45 & 49.57 & 49.5964824684901 & 49.57875 & 1.00035766267786 & 0.99946604139705 \tabularnewline
46 & 49.68 & 49.6488131224539 & 49.6291666666667 & 1.00039586511535 & 1.00062814950821 \tabularnewline
47 & 49.71 & 49.702426844885 & 49.68875 & 1.00027525033101 & 1.00015236992630 \tabularnewline
48 & 49.7 & 49.7344088729534 & 49.7504166666667 & 0.99967823799707 & 0.999308147543459 \tabularnewline
49 & 49.7 & 49.7469769899179 & 49.8095833333333 & 0.998743086385678 & 0.999055681515533 \tabularnewline
50 & 49.8 & 49.777757256647 & 49.87375 & 0.998075285228142 & 1.0004468410105 \tabularnewline
51 & 49.84 & 49.8706626220343 & 49.94125 & 0.998586591685917 & 0.999385157115984 \tabularnewline
52 & 50.09 & 50.1176790716316 & 50.03 & 1.00175252991468 & 0.99944771840707 \tabularnewline
53 & 50.2 & 50.2153951407941 & 50.1408333333333 & 1.00148704763172 & 0.999693417909967 \tabularnewline
54 & 50.16 & 50.3060736141207 & 50.2516666666667 & 1.00108268941237 & 0.99709630262061 \tabularnewline
55 & 50.16 & NA & NA & 1.00020253242622 & NA \tabularnewline
56 & 50.29 & NA & NA & 0.999363221193978 & NA \tabularnewline
57 & 50.36 & NA & NA & 1.00035766267786 & NA \tabularnewline
58 & 51.02 & NA & NA & 1.00039586511535 & NA \tabularnewline
59 & 51.03 & NA & NA & 1.00027525033101 & NA \tabularnewline
60 & 51.04 & NA & NA & 0.99967823799707 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13192&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]48.04[/C][C]NA[/C][C]NA[/C][C]0.998743086385678[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]48.06[/C][C]NA[/C][C]NA[/C][C]0.998075285228142[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]48.04[/C][C]NA[/C][C]NA[/C][C]0.998586591685917[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]48.09[/C][C]NA[/C][C]NA[/C][C]1.00175252991468[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]48.12[/C][C]NA[/C][C]NA[/C][C]1.00148704763172[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]48.16[/C][C]NA[/C][C]NA[/C][C]1.00108268941237[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]48.16[/C][C]48.1268286029633[/C][C]48.1170833333333[/C][C]1.00020253242622[/C][C]1.00068924959320[/C][/ROW]
[ROW][C]8[/C][C]48.16[/C][C]48.0947714213024[/C][C]48.1254166666667[/C][C]0.999363221193978[/C][C]1.00135625093477[/C][/ROW]
[ROW][C]9[/C][C]48.08[/C][C]48.155967434234[/C][C]48.13875[/C][C]1.00035766267786[/C][C]0.998422471019033[/C][/ROW]
[ROW][C]10[/C][C]48.13[/C][C]48.1832331800599[/C][C]48.1641666666667[/C][C]1.00039586511535[/C][C]0.998895192859703[/C][/ROW]
[ROW][C]11[/C][C]48.16[/C][C]48.2095160337659[/C][C]48.19625[/C][C]1.00027525033101[/C][C]0.998972899173449[/C][/ROW]
[ROW][C]12[/C][C]48.15[/C][C]48.2123987556028[/C][C]48.2279166666667[/C][C]0.99967823799707[/C][C]0.998705752934651[/C][/ROW]
[ROW][C]13[/C][C]48.15[/C][C]48.1980929201148[/C][C]48.25875[/C][C]0.998743086385678[/C][C]0.999002182094745[/C][/ROW]
[ROW][C]14[/C][C]48.15[/C][C]48.1966396589648[/C][C]48.2895833333333[/C][C]0.998075285228142[/C][C]0.999032304756207[/C][/ROW]
[ROW][C]15[/C][C]48.27[/C][C]48.2616899761804[/C][C]48.33[/C][C]0.998586591685917[/C][C]1.00017218675566[/C][/ROW]
[ROW][C]16[/C][C]48.47[/C][C]48.4610308252852[/C][C]48.37625[/C][C]1.00175252991468[/C][C]1.00018508014712[/C][/ROW]
[ROW][C]17[/C][C]48.51[/C][C]48.4907509875183[/C][C]48.41875[/C][C]1.00148704763172[/C][C]1.00039696255656[/C][/ROW]
[ROW][C]18[/C][C]48.53[/C][C]48.5137184822853[/C][C]48.46125[/C][C]1.00108268941237[/C][C]1.00033560646811[/C][/ROW]
[ROW][C]19[/C][C]48.53[/C][C]48.5135735821681[/C][C]48.50375[/C][C]1.00020253242622[/C][C]1.00033859426587[/C][/ROW]
[ROW][C]20[/C][C]48.53[/C][C]48.5157531782303[/C][C]48.5466666666667[/C][C]0.999363221193978[/C][C]1.00029365352151[/C][/ROW]
[ROW][C]21[/C][C]48.68[/C][C]48.6040443039752[/C][C]48.5866666666667[/C][C]1.00035766267786[/C][C]1.00156274435826[/C][/ROW]
[ROW][C]22[/C][C]48.64[/C][C]48.6446657728444[/C][C]48.6254166666667[/C][C]1.00039586511535[/C][C]0.999904084594472[/C][/ROW]
[ROW][C]23[/C][C]48.67[/C][C]48.6800621827758[/C][C]48.6666666666667[/C][C]1.00027525033101[/C][C]0.999793299713998[/C][/ROW]
[ROW][C]24[/C][C]48.66[/C][C]48.6930773750398[/C][C]48.70875[/C][C]0.99967823799707[/C][C]0.999320696558465[/C][/ROW]
[ROW][C]25[/C][C]48.66[/C][C]48.6899738901598[/C][C]48.75125[/C][C]0.998743086385678[/C][C]0.999384392971182[/C][/ROW]
[ROW][C]26[/C][C]48.67[/C][C]48.6998359486006[/C][C]48.79375[/C][C]0.998075285228142[/C][C]0.999387350121012[/C][/ROW]
[ROW][C]27[/C][C]48.71[/C][C]48.7618154275164[/C][C]48.8308333333333[/C][C]0.998586591685917[/C][C]0.998937376981105[/C][/ROW]
[ROW][C]28[/C][C]48.96[/C][C]48.9527243587183[/C][C]48.8670833333333[/C][C]1.00175252991468[/C][C]1.00014862587072[/C][/ROW]
[ROW][C]29[/C][C]49.01[/C][C]48.9818969271277[/C][C]48.9091666666667[/C][C]1.00148704763172[/C][C]1.00057374406945[/C][/ROW]
[ROW][C]30[/C][C]49.04[/C][C]49.0088372957572[/C][C]48.9558333333333[/C][C]1.00108268941237[/C][C]1.00063585887694[/C][/ROW]
[ROW][C]31[/C][C]49.04[/C][C]49.0157586036571[/C][C]49.0058333333333[/C][C]1.00020253242622[/C][C]1.00049456332073[/C][/ROW]
[ROW][C]32[/C][C]49.04[/C][C]49.0241792170128[/C][C]49.0554166666667[/C][C]0.999363221193978[/C][C]1.00032271387793[/C][/ROW]
[ROW][C]33[/C][C]49.06[/C][C]49.1217293944109[/C][C]49.1041666666667[/C][C]1.00035766267786[/C][C]0.998743338331692[/C][/ROW]
[ROW][C]34[/C][C]49.13[/C][C]49.1673726123672[/C][C]49.1479166666667[/C][C]1.00039586511535[/C][C]0.999239889984324[/C][/ROW]
[ROW][C]35[/C][C]49.19[/C][C]49.1985381875307[/C][C]49.185[/C][C]1.00027525033101[/C][C]0.999826454446713[/C][/ROW]
[ROW][C]36[/C][C]49.26[/C][C]49.2037463416166[/C][C]49.2195833333333[/C][C]0.99967823799707[/C][C]1.00114327998508[/C][/ROW]
[ROW][C]37[/C][C]49.26[/C][C]49.1918422910686[/C][C]49.25375[/C][C]0.998743086385678[/C][C]1.00138554902108[/C][/ROW]
[ROW][C]38[/C][C]49.26[/C][C]49.1934673500864[/C][C]49.2883333333333[/C][C]0.998075285228142[/C][C]1.00135246920979[/C][/ROW]
[ROW][C]39[/C][C]49.29[/C][C]49.2573640236405[/C][C]49.3270833333333[/C][C]0.998586591685917[/C][C]1.00066256035024[/C][/ROW]
[ROW][C]40[/C][C]49.43[/C][C]49.4577745925503[/C][C]49.37125[/C][C]1.00175252991468[/C][C]0.999438418069169[/C][/ROW]
[ROW][C]41[/C][C]49.43[/C][C]49.4893170312611[/C][C]49.4158333333333[/C][C]1.00148704763172[/C][C]0.998801417460992[/C][/ROW]
[ROW][C]42[/C][C]49.45[/C][C]49.5093786404634[/C][C]49.4558333333333[/C][C]1.00108268941237[/C][C]0.998800658741961[/C][/ROW]
[ROW][C]43[/C][C]49.45[/C][C]49.5025238361045[/C][C]49.4925[/C][C]1.00020253242622[/C][C]0.998938966500407[/C][/ROW]
[ROW][C]44[/C][C]49.46[/C][C]49.5017915564751[/C][C]49.5333333333333[/C][C]0.999363221193978[/C][C]0.999155756687566[/C][/ROW]
[ROW][C]45[/C][C]49.57[/C][C]49.5964824684901[/C][C]49.57875[/C][C]1.00035766267786[/C][C]0.99946604139705[/C][/ROW]
[ROW][C]46[/C][C]49.68[/C][C]49.6488131224539[/C][C]49.6291666666667[/C][C]1.00039586511535[/C][C]1.00062814950821[/C][/ROW]
[ROW][C]47[/C][C]49.71[/C][C]49.702426844885[/C][C]49.68875[/C][C]1.00027525033101[/C][C]1.00015236992630[/C][/ROW]
[ROW][C]48[/C][C]49.7[/C][C]49.7344088729534[/C][C]49.7504166666667[/C][C]0.99967823799707[/C][C]0.999308147543459[/C][/ROW]
[ROW][C]49[/C][C]49.7[/C][C]49.7469769899179[/C][C]49.8095833333333[/C][C]0.998743086385678[/C][C]0.999055681515533[/C][/ROW]
[ROW][C]50[/C][C]49.8[/C][C]49.777757256647[/C][C]49.87375[/C][C]0.998075285228142[/C][C]1.0004468410105[/C][/ROW]
[ROW][C]51[/C][C]49.84[/C][C]49.8706626220343[/C][C]49.94125[/C][C]0.998586591685917[/C][C]0.999385157115984[/C][/ROW]
[ROW][C]52[/C][C]50.09[/C][C]50.1176790716316[/C][C]50.03[/C][C]1.00175252991468[/C][C]0.99944771840707[/C][/ROW]
[ROW][C]53[/C][C]50.2[/C][C]50.2153951407941[/C][C]50.1408333333333[/C][C]1.00148704763172[/C][C]0.999693417909967[/C][/ROW]
[ROW][C]54[/C][C]50.16[/C][C]50.3060736141207[/C][C]50.2516666666667[/C][C]1.00108268941237[/C][C]0.99709630262061[/C][/ROW]
[ROW][C]55[/C][C]50.16[/C][C]NA[/C][C]NA[/C][C]1.00020253242622[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]50.29[/C][C]NA[/C][C]NA[/C][C]0.999363221193978[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]50.36[/C][C]NA[/C][C]NA[/C][C]1.00035766267786[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]51.02[/C][C]NA[/C][C]NA[/C][C]1.00039586511535[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]51.03[/C][C]NA[/C][C]NA[/C][C]1.00027525033101[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]51.04[/C][C]NA[/C][C]NA[/C][C]0.99967823799707[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13192&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13192&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	48.04	NA	NA	0.998743086385678	NA
2	48.06	NA	NA	0.998075285228142	NA
3	48.04	NA	NA	0.998586591685917	NA
4	48.09	NA	NA	1.00175252991468	NA
5	48.12	NA	NA	1.00148704763172	NA
6	48.16	NA	NA	1.00108268941237	NA
7	48.16	48.1268286029633	48.1170833333333	1.00020253242622	1.00068924959320
8	48.16	48.0947714213024	48.1254166666667	0.999363221193978	1.00135625093477
9	48.08	48.155967434234	48.13875	1.00035766267786	0.998422471019033
10	48.13	48.1832331800599	48.1641666666667	1.00039586511535	0.998895192859703
11	48.16	48.2095160337659	48.19625	1.00027525033101	0.998972899173449
12	48.15	48.2123987556028	48.2279166666667	0.99967823799707	0.998705752934651
13	48.15	48.1980929201148	48.25875	0.998743086385678	0.999002182094745
14	48.15	48.1966396589648	48.2895833333333	0.998075285228142	0.999032304756207
15	48.27	48.2616899761804	48.33	0.998586591685917	1.00017218675566
16	48.47	48.4610308252852	48.37625	1.00175252991468	1.00018508014712
17	48.51	48.4907509875183	48.41875	1.00148704763172	1.00039696255656
18	48.53	48.5137184822853	48.46125	1.00108268941237	1.00033560646811
19	48.53	48.5135735821681	48.50375	1.00020253242622	1.00033859426587
20	48.53	48.5157531782303	48.5466666666667	0.999363221193978	1.00029365352151
21	48.68	48.6040443039752	48.5866666666667	1.00035766267786	1.00156274435826
22	48.64	48.6446657728444	48.6254166666667	1.00039586511535	0.999904084594472
23	48.67	48.6800621827758	48.6666666666667	1.00027525033101	0.999793299713998
24	48.66	48.6930773750398	48.70875	0.99967823799707	0.999320696558465
25	48.66	48.6899738901598	48.75125	0.998743086385678	0.999384392971182
26	48.67	48.6998359486006	48.79375	0.998075285228142	0.999387350121012
27	48.71	48.7618154275164	48.8308333333333	0.998586591685917	0.998937376981105
28	48.96	48.9527243587183	48.8670833333333	1.00175252991468	1.00014862587072
29	49.01	48.9818969271277	48.9091666666667	1.00148704763172	1.00057374406945
30	49.04	49.0088372957572	48.9558333333333	1.00108268941237	1.00063585887694
31	49.04	49.0157586036571	49.0058333333333	1.00020253242622	1.00049456332073
32	49.04	49.0241792170128	49.0554166666667	0.999363221193978	1.00032271387793
33	49.06	49.1217293944109	49.1041666666667	1.00035766267786	0.998743338331692
34	49.13	49.1673726123672	49.1479166666667	1.00039586511535	0.999239889984324
35	49.19	49.1985381875307	49.185	1.00027525033101	0.999826454446713
36	49.26	49.2037463416166	49.2195833333333	0.99967823799707	1.00114327998508
37	49.26	49.1918422910686	49.25375	0.998743086385678	1.00138554902108
38	49.26	49.1934673500864	49.2883333333333	0.998075285228142	1.00135246920979
39	49.29	49.2573640236405	49.3270833333333	0.998586591685917	1.00066256035024
40	49.43	49.4577745925503	49.37125	1.00175252991468	0.999438418069169
41	49.43	49.4893170312611	49.4158333333333	1.00148704763172	0.998801417460992
42	49.45	49.5093786404634	49.4558333333333	1.00108268941237	0.998800658741961
43	49.45	49.5025238361045	49.4925	1.00020253242622	0.998938966500407
44	49.46	49.5017915564751	49.5333333333333	0.999363221193978	0.999155756687566
45	49.57	49.5964824684901	49.57875	1.00035766267786	0.99946604139705
46	49.68	49.6488131224539	49.6291666666667	1.00039586511535	1.00062814950821
47	49.71	49.702426844885	49.68875	1.00027525033101	1.00015236992630
48	49.7	49.7344088729534	49.7504166666667	0.99967823799707	0.999308147543459
49	49.7	49.7469769899179	49.8095833333333	0.998743086385678	0.999055681515533
50	49.8	49.777757256647	49.87375	0.998075285228142	1.0004468410105
51	49.84	49.8706626220343	49.94125	0.998586591685917	0.999385157115984
52	50.09	50.1176790716316	50.03	1.00175252991468	0.99944771840707
53	50.2	50.2153951407941	50.1408333333333	1.00148704763172	0.999693417909967
54	50.16	50.3060736141207	50.2516666666667	1.00108268941237	0.99709630262061
55	50.16	NA	NA	1.00020253242622	NA
56	50.29	NA	NA	0.999363221193978	NA
57	50.36	NA	NA	1.00035766267786	NA
58	51.02	NA	NA	1.00039586511535	NA
59	51.03	NA	NA	1.00027525033101	NA
60	51.04	NA	NA	0.99967823799707	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