Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 06 Dec 2009 06:38:52 -0700

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/2009/Dec/06/t1260106763hlos78kj9kuxkw9.htm/, Retrieved Sun, 05 May 2024 23:40:53 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64388, Retrieved Sun, 05 May 2024 23:40:53 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

111

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-    D    [Classical Decomposition] [shw9] [2009-12-04 15:00:44] [3c8b83428ce260cd44df892bb7619588]
-           [Classical Decomposition] [workshop 9] [2009-12-04 18:58:48] [1433a524809eda02c3198b3ae6eebb69]
-    D          [Classical Decomposition] [verbetering workshop] [2009-12-06 13:38:52] [a5c6be3c0aa55fdb2a703a08e16947ef] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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	'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64388&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64388&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64388&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	2 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	3922	NA	NA	0.897304195914187	NA
2	3759	NA	NA	0.954638769538198	NA
3	4138	NA	NA	0.979781268093018	NA
4	4634	NA	NA	1.05020944347549	NA
5	3995	NA	NA	0.917307086918369	NA
6	4308	NA	NA	1.02844256976708	NA
7	4143	4564.15065449425	4578.625	0.996838713477136	0.90772639065287
8	4429	4528.84709251033	4638.79166666667	0.976298876505627	0.97795308817658
9	5219	5173.39800866018	4733.5	1.09293292672656	1.00881470771502
10	4929	4692.26767803032	4783.125	0.981004610590423	1.05045158081626
11	5755	4886.09142571097	4808.83333333333	1.01606587024801	1.17783305685128
12	5592	5422.57498188727	4888.83333333333	1.10917566874590	1.03124438457350
13	4163	4499.38233971237	5014.33333333333	0.897304195914187	0.925238107296773
14	4962	4874.34578064664	5105.95833333333	0.954638769538198	1.01798276595423
15	5208	5063.71371460224	5168.20833333333	0.979781268093018	1.02849416328212
16	4755	5465.24618511963	5203.95833333333	1.05020944347549	0.87004314882403
17	4491	4757.91897533109	5186.83333333333	0.917307086918369	0.94390005867796
18	5732	5317.21949279075	5170.16666666667	1.02844256976708	1.07800703126354
19	5731	5172.18073476891	5188.58333333333	0.996838713477136	1.10804325948522
20	5040	5074.76088095639	5197.95833333333	0.976298876505627	0.993150242588407
21	6102	5661.52917705943	5180.125	1.09293292672656	1.07780068055206
22	4904	5095.91020009617	5194.58333333333	0.981004610590423	0.96234034891499
23	5369	5286.46371466661	5202.875	1.01606587024801	1.01561275926370
24	5578	5703.79722956722	5142.375	1.10917566874590	0.977945003213804
25	4619	4535.68577197207	5054.79166666667	0.897304195914187	1.01836860669290
26	4731	4753.26576337688	4979.125	0.954638769538198	0.995315691466605
27	5011	4804.68404185015	4903.83333333333	0.979781268093018	1.04294058804966
28	5299	5076.31862121921	4833.625	1.05020944347549	1.04386670644549
29	4146	4359.50193057955	4752.5	0.917307086918369	0.951026072707539
30	4625	4813.83970666351	4680.70833333333	1.02844256976708	0.96077150088689
31	4736	4632.93252572417	4647.625	0.996838713477136	1.02224670307706
32	4219	4518.27052134819	4627.95833333333	0.976298876505627	0.933764364056075
33	5116	4996.34287453047	4571.5	1.09293292672656	1.02394894195102
34	4205	4444.80926500888	4530.875	0.981004610590423	0.94604734405664
35	4121	4617.55368342	4544.54166666667	1.01606587024801	0.892463906764538
36	5103	5008.62137918073	4515.625	1.10917566874590	1.01884323323212
37	4300	4009.37947339357	4468.25	0.897304195914187	1.07248516348602
38	4578	4276.10548506937	4479.29166666667	0.954638769538198	1.07060034322931
39	3809	4384.64364737477	4475.125	0.979781268093018	0.868713698610508
40	5526	4684.80929243691	4460.83333333333	1.05020944347549	1.17955708654376
41	4247	4105.29320411729	4475.375	0.917307086918369	1.03451806943791
42	3830	4588.78219097948	4461.875	1.02844256976708	0.834644103947432
43	4394	4418.90294695135	4432.91666666667	0.996838713477136	0.994364450351069
44	4826	4280.21631196023	4384.125	0.976298876505627	1.12751310874515
45	4409	4782.94772058711	4376.25	1.09293292672656	0.921816473348111
46	4569	4256.00675266234	4338.41666666667	0.981004610590423	1.07354152977832
47	4106	4338.22024125765	4269.625	1.01606587024801	0.946471080686689
48	4794	4773.24505914227	4303.41666666667	1.10917566874590	1.00434818254679
49	3914	3851.26699653852	4292.04166666667	0.897304195914187	1.01628892609052
50	3793	3999.02158221091	4189.04166666667	0.954638769538198	0.948482002916071
51	4405	4033.02464478788	4116.25	0.979781268093018	1.09223235362393
52	4022	4283.67304375608	4078.875	1.05020944347549	0.93891386175294
53	4100	3717.34874860807	4052.45833333333	0.917307086918369	1.10293660274280
54	4788	4131.29665452809	4017.04166666667	1.02844256976708	1.15895816746835
55	3163	NA	NA	0.996838713477136	NA
56	3585	NA	NA	0.976298876505627	NA
57	3903	NA	NA	1.09293292672656	NA
58	4178	NA	NA	0.981004610590423	NA
59	3863	NA	NA	1.01606587024801	NA
60	4187	NA	NA	1.10917566874590	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 3922 & NA & NA & 0.897304195914187 & NA \tabularnewline
2 & 3759 & NA & NA & 0.954638769538198 & NA \tabularnewline
3 & 4138 & NA & NA & 0.979781268093018 & NA \tabularnewline
4 & 4634 & NA & NA & 1.05020944347549 & NA \tabularnewline
5 & 3995 & NA & NA & 0.917307086918369 & NA \tabularnewline
6 & 4308 & NA & NA & 1.02844256976708 & NA \tabularnewline
7 & 4143 & 4564.15065449425 & 4578.625 & 0.996838713477136 & 0.90772639065287 \tabularnewline
8 & 4429 & 4528.84709251033 & 4638.79166666667 & 0.976298876505627 & 0.97795308817658 \tabularnewline
9 & 5219 & 5173.39800866018 & 4733.5 & 1.09293292672656 & 1.00881470771502 \tabularnewline
10 & 4929 & 4692.26767803032 & 4783.125 & 0.981004610590423 & 1.05045158081626 \tabularnewline
11 & 5755 & 4886.09142571097 & 4808.83333333333 & 1.01606587024801 & 1.17783305685128 \tabularnewline
12 & 5592 & 5422.57498188727 & 4888.83333333333 & 1.10917566874590 & 1.03124438457350 \tabularnewline
13 & 4163 & 4499.38233971237 & 5014.33333333333 & 0.897304195914187 & 0.925238107296773 \tabularnewline
14 & 4962 & 4874.34578064664 & 5105.95833333333 & 0.954638769538198 & 1.01798276595423 \tabularnewline
15 & 5208 & 5063.71371460224 & 5168.20833333333 & 0.979781268093018 & 1.02849416328212 \tabularnewline
16 & 4755 & 5465.24618511963 & 5203.95833333333 & 1.05020944347549 & 0.87004314882403 \tabularnewline
17 & 4491 & 4757.91897533109 & 5186.83333333333 & 0.917307086918369 & 0.94390005867796 \tabularnewline
18 & 5732 & 5317.21949279075 & 5170.16666666667 & 1.02844256976708 & 1.07800703126354 \tabularnewline
19 & 5731 & 5172.18073476891 & 5188.58333333333 & 0.996838713477136 & 1.10804325948522 \tabularnewline
20 & 5040 & 5074.76088095639 & 5197.95833333333 & 0.976298876505627 & 0.993150242588407 \tabularnewline
21 & 6102 & 5661.52917705943 & 5180.125 & 1.09293292672656 & 1.07780068055206 \tabularnewline
22 & 4904 & 5095.91020009617 & 5194.58333333333 & 0.981004610590423 & 0.96234034891499 \tabularnewline
23 & 5369 & 5286.46371466661 & 5202.875 & 1.01606587024801 & 1.01561275926370 \tabularnewline
24 & 5578 & 5703.79722956722 & 5142.375 & 1.10917566874590 & 0.977945003213804 \tabularnewline
25 & 4619 & 4535.68577197207 & 5054.79166666667 & 0.897304195914187 & 1.01836860669290 \tabularnewline
26 & 4731 & 4753.26576337688 & 4979.125 & 0.954638769538198 & 0.995315691466605 \tabularnewline
27 & 5011 & 4804.68404185015 & 4903.83333333333 & 0.979781268093018 & 1.04294058804966 \tabularnewline
28 & 5299 & 5076.31862121921 & 4833.625 & 1.05020944347549 & 1.04386670644549 \tabularnewline
29 & 4146 & 4359.50193057955 & 4752.5 & 0.917307086918369 & 0.951026072707539 \tabularnewline
30 & 4625 & 4813.83970666351 & 4680.70833333333 & 1.02844256976708 & 0.96077150088689 \tabularnewline
31 & 4736 & 4632.93252572417 & 4647.625 & 0.996838713477136 & 1.02224670307706 \tabularnewline
32 & 4219 & 4518.27052134819 & 4627.95833333333 & 0.976298876505627 & 0.933764364056075 \tabularnewline
33 & 5116 & 4996.34287453047 & 4571.5 & 1.09293292672656 & 1.02394894195102 \tabularnewline
34 & 4205 & 4444.80926500888 & 4530.875 & 0.981004610590423 & 0.94604734405664 \tabularnewline
35 & 4121 & 4617.55368342 & 4544.54166666667 & 1.01606587024801 & 0.892463906764538 \tabularnewline
36 & 5103 & 5008.62137918073 & 4515.625 & 1.10917566874590 & 1.01884323323212 \tabularnewline
37 & 4300 & 4009.37947339357 & 4468.25 & 0.897304195914187 & 1.07248516348602 \tabularnewline
38 & 4578 & 4276.10548506937 & 4479.29166666667 & 0.954638769538198 & 1.07060034322931 \tabularnewline
39 & 3809 & 4384.64364737477 & 4475.125 & 0.979781268093018 & 0.868713698610508 \tabularnewline
40 & 5526 & 4684.80929243691 & 4460.83333333333 & 1.05020944347549 & 1.17955708654376 \tabularnewline
41 & 4247 & 4105.29320411729 & 4475.375 & 0.917307086918369 & 1.03451806943791 \tabularnewline
42 & 3830 & 4588.78219097948 & 4461.875 & 1.02844256976708 & 0.834644103947432 \tabularnewline
43 & 4394 & 4418.90294695135 & 4432.91666666667 & 0.996838713477136 & 0.994364450351069 \tabularnewline
44 & 4826 & 4280.21631196023 & 4384.125 & 0.976298876505627 & 1.12751310874515 \tabularnewline
45 & 4409 & 4782.94772058711 & 4376.25 & 1.09293292672656 & 0.921816473348111 \tabularnewline
46 & 4569 & 4256.00675266234 & 4338.41666666667 & 0.981004610590423 & 1.07354152977832 \tabularnewline
47 & 4106 & 4338.22024125765 & 4269.625 & 1.01606587024801 & 0.946471080686689 \tabularnewline
48 & 4794 & 4773.24505914227 & 4303.41666666667 & 1.10917566874590 & 1.00434818254679 \tabularnewline
49 & 3914 & 3851.26699653852 & 4292.04166666667 & 0.897304195914187 & 1.01628892609052 \tabularnewline
50 & 3793 & 3999.02158221091 & 4189.04166666667 & 0.954638769538198 & 0.948482002916071 \tabularnewline
51 & 4405 & 4033.02464478788 & 4116.25 & 0.979781268093018 & 1.09223235362393 \tabularnewline
52 & 4022 & 4283.67304375608 & 4078.875 & 1.05020944347549 & 0.93891386175294 \tabularnewline
53 & 4100 & 3717.34874860807 & 4052.45833333333 & 0.917307086918369 & 1.10293660274280 \tabularnewline
54 & 4788 & 4131.29665452809 & 4017.04166666667 & 1.02844256976708 & 1.15895816746835 \tabularnewline
55 & 3163 & NA & NA & 0.996838713477136 & NA \tabularnewline
56 & 3585 & NA & NA & 0.976298876505627 & NA \tabularnewline
57 & 3903 & NA & NA & 1.09293292672656 & NA \tabularnewline
58 & 4178 & NA & NA & 0.981004610590423 & NA \tabularnewline
59 & 3863 & NA & NA & 1.01606587024801 & NA \tabularnewline
60 & 4187 & NA & NA & 1.10917566874590 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64388&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]3922[/C][C]NA[/C][C]NA[/C][C]0.897304195914187[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3759[/C][C]NA[/C][C]NA[/C][C]0.954638769538198[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]4138[/C][C]NA[/C][C]NA[/C][C]0.979781268093018[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]4634[/C][C]NA[/C][C]NA[/C][C]1.05020944347549[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3995[/C][C]NA[/C][C]NA[/C][C]0.917307086918369[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]4308[/C][C]NA[/C][C]NA[/C][C]1.02844256976708[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]4143[/C][C]4564.15065449425[/C][C]4578.625[/C][C]0.996838713477136[/C][C]0.90772639065287[/C][/ROW]
[ROW][C]8[/C][C]4429[/C][C]4528.84709251033[/C][C]4638.79166666667[/C][C]0.976298876505627[/C][C]0.97795308817658[/C][/ROW]
[ROW][C]9[/C][C]5219[/C][C]5173.39800866018[/C][C]4733.5[/C][C]1.09293292672656[/C][C]1.00881470771502[/C][/ROW]
[ROW][C]10[/C][C]4929[/C][C]4692.26767803032[/C][C]4783.125[/C][C]0.981004610590423[/C][C]1.05045158081626[/C][/ROW]
[ROW][C]11[/C][C]5755[/C][C]4886.09142571097[/C][C]4808.83333333333[/C][C]1.01606587024801[/C][C]1.17783305685128[/C][/ROW]
[ROW][C]12[/C][C]5592[/C][C]5422.57498188727[/C][C]4888.83333333333[/C][C]1.10917566874590[/C][C]1.03124438457350[/C][/ROW]
[ROW][C]13[/C][C]4163[/C][C]4499.38233971237[/C][C]5014.33333333333[/C][C]0.897304195914187[/C][C]0.925238107296773[/C][/ROW]
[ROW][C]14[/C][C]4962[/C][C]4874.34578064664[/C][C]5105.95833333333[/C][C]0.954638769538198[/C][C]1.01798276595423[/C][/ROW]
[ROW][C]15[/C][C]5208[/C][C]5063.71371460224[/C][C]5168.20833333333[/C][C]0.979781268093018[/C][C]1.02849416328212[/C][/ROW]
[ROW][C]16[/C][C]4755[/C][C]5465.24618511963[/C][C]5203.95833333333[/C][C]1.05020944347549[/C][C]0.87004314882403[/C][/ROW]
[ROW][C]17[/C][C]4491[/C][C]4757.91897533109[/C][C]5186.83333333333[/C][C]0.917307086918369[/C][C]0.94390005867796[/C][/ROW]
[ROW][C]18[/C][C]5732[/C][C]5317.21949279075[/C][C]5170.16666666667[/C][C]1.02844256976708[/C][C]1.07800703126354[/C][/ROW]
[ROW][C]19[/C][C]5731[/C][C]5172.18073476891[/C][C]5188.58333333333[/C][C]0.996838713477136[/C][C]1.10804325948522[/C][/ROW]
[ROW][C]20[/C][C]5040[/C][C]5074.76088095639[/C][C]5197.95833333333[/C][C]0.976298876505627[/C][C]0.993150242588407[/C][/ROW]
[ROW][C]21[/C][C]6102[/C][C]5661.52917705943[/C][C]5180.125[/C][C]1.09293292672656[/C][C]1.07780068055206[/C][/ROW]
[ROW][C]22[/C][C]4904[/C][C]5095.91020009617[/C][C]5194.58333333333[/C][C]0.981004610590423[/C][C]0.96234034891499[/C][/ROW]
[ROW][C]23[/C][C]5369[/C][C]5286.46371466661[/C][C]5202.875[/C][C]1.01606587024801[/C][C]1.01561275926370[/C][/ROW]
[ROW][C]24[/C][C]5578[/C][C]5703.79722956722[/C][C]5142.375[/C][C]1.10917566874590[/C][C]0.977945003213804[/C][/ROW]
[ROW][C]25[/C][C]4619[/C][C]4535.68577197207[/C][C]5054.79166666667[/C][C]0.897304195914187[/C][C]1.01836860669290[/C][/ROW]
[ROW][C]26[/C][C]4731[/C][C]4753.26576337688[/C][C]4979.125[/C][C]0.954638769538198[/C][C]0.995315691466605[/C][/ROW]
[ROW][C]27[/C][C]5011[/C][C]4804.68404185015[/C][C]4903.83333333333[/C][C]0.979781268093018[/C][C]1.04294058804966[/C][/ROW]
[ROW][C]28[/C][C]5299[/C][C]5076.31862121921[/C][C]4833.625[/C][C]1.05020944347549[/C][C]1.04386670644549[/C][/ROW]
[ROW][C]29[/C][C]4146[/C][C]4359.50193057955[/C][C]4752.5[/C][C]0.917307086918369[/C][C]0.951026072707539[/C][/ROW]
[ROW][C]30[/C][C]4625[/C][C]4813.83970666351[/C][C]4680.70833333333[/C][C]1.02844256976708[/C][C]0.96077150088689[/C][/ROW]
[ROW][C]31[/C][C]4736[/C][C]4632.93252572417[/C][C]4647.625[/C][C]0.996838713477136[/C][C]1.02224670307706[/C][/ROW]
[ROW][C]32[/C][C]4219[/C][C]4518.27052134819[/C][C]4627.95833333333[/C][C]0.976298876505627[/C][C]0.933764364056075[/C][/ROW]
[ROW][C]33[/C][C]5116[/C][C]4996.34287453047[/C][C]4571.5[/C][C]1.09293292672656[/C][C]1.02394894195102[/C][/ROW]
[ROW][C]34[/C][C]4205[/C][C]4444.80926500888[/C][C]4530.875[/C][C]0.981004610590423[/C][C]0.94604734405664[/C][/ROW]
[ROW][C]35[/C][C]4121[/C][C]4617.55368342[/C][C]4544.54166666667[/C][C]1.01606587024801[/C][C]0.892463906764538[/C][/ROW]
[ROW][C]36[/C][C]5103[/C][C]5008.62137918073[/C][C]4515.625[/C][C]1.10917566874590[/C][C]1.01884323323212[/C][/ROW]
[ROW][C]37[/C][C]4300[/C][C]4009.37947339357[/C][C]4468.25[/C][C]0.897304195914187[/C][C]1.07248516348602[/C][/ROW]
[ROW][C]38[/C][C]4578[/C][C]4276.10548506937[/C][C]4479.29166666667[/C][C]0.954638769538198[/C][C]1.07060034322931[/C][/ROW]
[ROW][C]39[/C][C]3809[/C][C]4384.64364737477[/C][C]4475.125[/C][C]0.979781268093018[/C][C]0.868713698610508[/C][/ROW]
[ROW][C]40[/C][C]5526[/C][C]4684.80929243691[/C][C]4460.83333333333[/C][C]1.05020944347549[/C][C]1.17955708654376[/C][/ROW]
[ROW][C]41[/C][C]4247[/C][C]4105.29320411729[/C][C]4475.375[/C][C]0.917307086918369[/C][C]1.03451806943791[/C][/ROW]
[ROW][C]42[/C][C]3830[/C][C]4588.78219097948[/C][C]4461.875[/C][C]1.02844256976708[/C][C]0.834644103947432[/C][/ROW]
[ROW][C]43[/C][C]4394[/C][C]4418.90294695135[/C][C]4432.91666666667[/C][C]0.996838713477136[/C][C]0.994364450351069[/C][/ROW]
[ROW][C]44[/C][C]4826[/C][C]4280.21631196023[/C][C]4384.125[/C][C]0.976298876505627[/C][C]1.12751310874515[/C][/ROW]
[ROW][C]45[/C][C]4409[/C][C]4782.94772058711[/C][C]4376.25[/C][C]1.09293292672656[/C][C]0.921816473348111[/C][/ROW]
[ROW][C]46[/C][C]4569[/C][C]4256.00675266234[/C][C]4338.41666666667[/C][C]0.981004610590423[/C][C]1.07354152977832[/C][/ROW]
[ROW][C]47[/C][C]4106[/C][C]4338.22024125765[/C][C]4269.625[/C][C]1.01606587024801[/C][C]0.946471080686689[/C][/ROW]
[ROW][C]48[/C][C]4794[/C][C]4773.24505914227[/C][C]4303.41666666667[/C][C]1.10917566874590[/C][C]1.00434818254679[/C][/ROW]
[ROW][C]49[/C][C]3914[/C][C]3851.26699653852[/C][C]4292.04166666667[/C][C]0.897304195914187[/C][C]1.01628892609052[/C][/ROW]
[ROW][C]50[/C][C]3793[/C][C]3999.02158221091[/C][C]4189.04166666667[/C][C]0.954638769538198[/C][C]0.948482002916071[/C][/ROW]
[ROW][C]51[/C][C]4405[/C][C]4033.02464478788[/C][C]4116.25[/C][C]0.979781268093018[/C][C]1.09223235362393[/C][/ROW]
[ROW][C]52[/C][C]4022[/C][C]4283.67304375608[/C][C]4078.875[/C][C]1.05020944347549[/C][C]0.93891386175294[/C][/ROW]
[ROW][C]53[/C][C]4100[/C][C]3717.34874860807[/C][C]4052.45833333333[/C][C]0.917307086918369[/C][C]1.10293660274280[/C][/ROW]
[ROW][C]54[/C][C]4788[/C][C]4131.29665452809[/C][C]4017.04166666667[/C][C]1.02844256976708[/C][C]1.15895816746835[/C][/ROW]
[ROW][C]55[/C][C]3163[/C][C]NA[/C][C]NA[/C][C]0.996838713477136[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]3585[/C][C]NA[/C][C]NA[/C][C]0.976298876505627[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]3903[/C][C]NA[/C][C]NA[/C][C]1.09293292672656[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]4178[/C][C]NA[/C][C]NA[/C][C]0.981004610590423[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]3863[/C][C]NA[/C][C]NA[/C][C]1.01606587024801[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]4187[/C][C]NA[/C][C]NA[/C][C]1.10917566874590[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64388&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64388&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	3922	NA	NA	0.897304195914187	NA
2	3759	NA	NA	0.954638769538198	NA
3	4138	NA	NA	0.979781268093018	NA
4	4634	NA	NA	1.05020944347549	NA
5	3995	NA	NA	0.917307086918369	NA
6	4308	NA	NA	1.02844256976708	NA
7	4143	4564.15065449425	4578.625	0.996838713477136	0.90772639065287
8	4429	4528.84709251033	4638.79166666667	0.976298876505627	0.97795308817658
9	5219	5173.39800866018	4733.5	1.09293292672656	1.00881470771502
10	4929	4692.26767803032	4783.125	0.981004610590423	1.05045158081626
11	5755	4886.09142571097	4808.83333333333	1.01606587024801	1.17783305685128
12	5592	5422.57498188727	4888.83333333333	1.10917566874590	1.03124438457350
13	4163	4499.38233971237	5014.33333333333	0.897304195914187	0.925238107296773
14	4962	4874.34578064664	5105.95833333333	0.954638769538198	1.01798276595423
15	5208	5063.71371460224	5168.20833333333	0.979781268093018	1.02849416328212
16	4755	5465.24618511963	5203.95833333333	1.05020944347549	0.87004314882403
17	4491	4757.91897533109	5186.83333333333	0.917307086918369	0.94390005867796
18	5732	5317.21949279075	5170.16666666667	1.02844256976708	1.07800703126354
19	5731	5172.18073476891	5188.58333333333	0.996838713477136	1.10804325948522
20	5040	5074.76088095639	5197.95833333333	0.976298876505627	0.993150242588407
21	6102	5661.52917705943	5180.125	1.09293292672656	1.07780068055206
22	4904	5095.91020009617	5194.58333333333	0.981004610590423	0.96234034891499
23	5369	5286.46371466661	5202.875	1.01606587024801	1.01561275926370
24	5578	5703.79722956722	5142.375	1.10917566874590	0.977945003213804
25	4619	4535.68577197207	5054.79166666667	0.897304195914187	1.01836860669290
26	4731	4753.26576337688	4979.125	0.954638769538198	0.995315691466605
27	5011	4804.68404185015	4903.83333333333	0.979781268093018	1.04294058804966
28	5299	5076.31862121921	4833.625	1.05020944347549	1.04386670644549
29	4146	4359.50193057955	4752.5	0.917307086918369	0.951026072707539
30	4625	4813.83970666351	4680.70833333333	1.02844256976708	0.96077150088689
31	4736	4632.93252572417	4647.625	0.996838713477136	1.02224670307706
32	4219	4518.27052134819	4627.95833333333	0.976298876505627	0.933764364056075
33	5116	4996.34287453047	4571.5	1.09293292672656	1.02394894195102
34	4205	4444.80926500888	4530.875	0.981004610590423	0.94604734405664
35	4121	4617.55368342	4544.54166666667	1.01606587024801	0.892463906764538
36	5103	5008.62137918073	4515.625	1.10917566874590	1.01884323323212
37	4300	4009.37947339357	4468.25	0.897304195914187	1.07248516348602
38	4578	4276.10548506937	4479.29166666667	0.954638769538198	1.07060034322931
39	3809	4384.64364737477	4475.125	0.979781268093018	0.868713698610508
40	5526	4684.80929243691	4460.83333333333	1.05020944347549	1.17955708654376
41	4247	4105.29320411729	4475.375	0.917307086918369	1.03451806943791
42	3830	4588.78219097948	4461.875	1.02844256976708	0.834644103947432
43	4394	4418.90294695135	4432.91666666667	0.996838713477136	0.994364450351069
44	4826	4280.21631196023	4384.125	0.976298876505627	1.12751310874515
45	4409	4782.94772058711	4376.25	1.09293292672656	0.921816473348111
46	4569	4256.00675266234	4338.41666666667	0.981004610590423	1.07354152977832
47	4106	4338.22024125765	4269.625	1.01606587024801	0.946471080686689
48	4794	4773.24505914227	4303.41666666667	1.10917566874590	1.00434818254679
49	3914	3851.26699653852	4292.04166666667	0.897304195914187	1.01628892609052
50	3793	3999.02158221091	4189.04166666667	0.954638769538198	0.948482002916071
51	4405	4033.02464478788	4116.25	0.979781268093018	1.09223235362393
52	4022	4283.67304375608	4078.875	1.05020944347549	0.93891386175294
53	4100	3717.34874860807	4052.45833333333	0.917307086918369	1.10293660274280
54	4788	4131.29665452809	4017.04166666667	1.02844256976708	1.15895816746835
55	3163	NA	NA	0.996838713477136	NA
56	3585	NA	NA	0.976298876505627	NA
57	3903	NA	NA	1.09293292672656	NA
58	4178	NA	NA	0.981004610590423	NA
59	3863	NA	NA	1.01606587024801	NA
60	4187	NA	NA	1.10917566874590	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