Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 30 Nov 2014 14:14:26 +0000

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/2014/Nov/30/t14173569698scmyeuffj8arcy.htm/, Retrieved Sun, 19 May 2024 14:54:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261453, Retrieved Sun, 19 May 2024 14:54:45 +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

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

-       [Classical Decomposition] [eigen reeks decom...] [2014-11-30 14:14:26] [6e93958bb59fd6ca90246553243cf8d9] [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	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261453&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261453&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261453&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	389.09	NA	NA	-3.8542	NA
2	391.76	NA	NA	-0.752868	NA
3	390.96	NA	NA	1.96147	NA
4	391.76	NA	NA	2.7753	NA
5	392.8	NA	NA	2.90763	NA
6	393.06	NA	NA	2.02672	NA
7	393.06	393.934	392.997	0.936965	-0.874465
8	393.26	393.734	393.551	0.183049	-0.474299
9	393.87	393.953	394.509	-0.555868	-0.0828819
10	394.47	394.772	395.777	-1.00512	-0.301965
11	394.57	395.262	397.107	-1.84503	-0.692465
12	394.57	395.725	398.503	-2.77803	-1.1553
13	394.57	396.052	399.907	-3.8542	-1.48247
14	399.57	400.559	401.312	-0.752868	-0.988799
15	406.13	404.671	402.71	1.96147	1.45895
16	407.03	406.855	404.08	2.7753	0.174701
17	409.46	408.339	405.432	2.90763	1.1207
18	409.9	408.818	406.791	2.02672	1.08245
19	409.9	409.094	408.158	0.936965	0.805535
20	410.14	409.617	409.434	0.183049	0.523201
21	410.54	410.187	410.742	-0.555868	0.353368
22	410.69	411.154	412.159	-1.00512	-0.464049
23	410.79	411.729	413.574	-1.84503	-0.939132
24	410.97	412.192	414.97	-2.77803	-1.22197
25	410.97	412.479	416.333	-3.8542	-1.50913
26	413.8	416.936	417.689	-0.752868	-3.1363
27	423.31	421.016	419.055	1.96147	2.29353
28	423.85	423.224	420.449	2.7753	0.625535
29	426.6	424.788	421.881	2.90763	1.81153
30	426.26	425.38	423.353	2.02672	0.880368
31	426.26	425.776	424.839	0.936965	0.484285
32	426.32	426.643	426.46	0.183049	-0.322632
33	427.14	427.296	427.852	-0.555868	-0.156215
34	427.55	428.066	429.071	-1.00512	-0.515715
35	428.29	428.53	430.375	-1.84503	-0.239549
36	428.8	428.812	431.59	-2.77803	-0.0119653
37	428.8	428.967	432.822	-3.8542	-0.167465
38	434.87	433.333	434.086	-0.752868	1.53703
39	435.66	437.311	435.35	1.96147	-1.65147
40	440.75	439.363	436.588	2.7753	1.38678
41	440.99	440.723	437.815	2.90763	0.267368
42	441.04	441.03	439.004	2.02672	0.00953472
43	441.04	441.108	440.171	0.936965	-0.0682153
44	441.88	441.451	441.268	0.183049	0.428618
45	441.92	441.678	442.234	-0.555868	0.241701
46	442.48	442.007	443.012	-1.00512	0.472618
47	442.81	441.815	443.66	-1.84503	0.995035
48	442.81	441.524	444.302	-2.77803	1.28595
49	442.81	441.103	444.957	-3.8542	1.70712
50	447.19	444.837	445.59	-0.752868	2.35328
51	446.52	448.131	446.169	1.96147	-1.61063
52	448.57	449.543	446.767	2.7753	-0.972799
53	448.71	450.29	447.382	2.90763	-1.57972
54	448.73	450.005	447.978	2.02672	-1.27463
55	449.07	449.511	448.574	0.936965	-0.440715
56	449.03	449.278	449.095	0.183049	-0.248465
57	448.68	449.13	449.685	-0.555868	-0.449549
58	450.08	449.364	450.37	-1.00512	0.715535
59	449.96	449.177	451.023	-1.84503	0.782535
60	449.96	448.95	451.728	-2.77803	1.0097
61	449.96	448.602	452.456	-3.8542	1.35837
62	452.56	452.419	453.172	-0.752868	0.141201
63	455.31	455.894	453.932	1.96147	-0.583965
64	456.2	457.508	454.732	2.7753	-1.3078
65	456.75	458.463	455.556	2.90763	-1.71347
66	457.63	458.421	456.395	2.02672	-0.791299
67	457.63	NA	NA	0.936965	NA
68	457.65	NA	NA	0.183049	NA
69	458.32	NA	NA	-0.555868	NA
70	459.64	NA	NA	-1.00512	NA
71	460.16	NA	NA	-1.84503	NA
72	459.89	NA	NA	-2.77803	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 389.09 & NA & NA & -3.8542 & NA \tabularnewline
2 & 391.76 & NA & NA & -0.752868 & NA \tabularnewline
3 & 390.96 & NA & NA & 1.96147 & NA \tabularnewline
4 & 391.76 & NA & NA & 2.7753 & NA \tabularnewline
5 & 392.8 & NA & NA & 2.90763 & NA \tabularnewline
6 & 393.06 & NA & NA & 2.02672 & NA \tabularnewline
7 & 393.06 & 393.934 & 392.997 & 0.936965 & -0.874465 \tabularnewline
8 & 393.26 & 393.734 & 393.551 & 0.183049 & -0.474299 \tabularnewline
9 & 393.87 & 393.953 & 394.509 & -0.555868 & -0.0828819 \tabularnewline
10 & 394.47 & 394.772 & 395.777 & -1.00512 & -0.301965 \tabularnewline
11 & 394.57 & 395.262 & 397.107 & -1.84503 & -0.692465 \tabularnewline
12 & 394.57 & 395.725 & 398.503 & -2.77803 & -1.1553 \tabularnewline
13 & 394.57 & 396.052 & 399.907 & -3.8542 & -1.48247 \tabularnewline
14 & 399.57 & 400.559 & 401.312 & -0.752868 & -0.988799 \tabularnewline
15 & 406.13 & 404.671 & 402.71 & 1.96147 & 1.45895 \tabularnewline
16 & 407.03 & 406.855 & 404.08 & 2.7753 & 0.174701 \tabularnewline
17 & 409.46 & 408.339 & 405.432 & 2.90763 & 1.1207 \tabularnewline
18 & 409.9 & 408.818 & 406.791 & 2.02672 & 1.08245 \tabularnewline
19 & 409.9 & 409.094 & 408.158 & 0.936965 & 0.805535 \tabularnewline
20 & 410.14 & 409.617 & 409.434 & 0.183049 & 0.523201 \tabularnewline
21 & 410.54 & 410.187 & 410.742 & -0.555868 & 0.353368 \tabularnewline
22 & 410.69 & 411.154 & 412.159 & -1.00512 & -0.464049 \tabularnewline
23 & 410.79 & 411.729 & 413.574 & -1.84503 & -0.939132 \tabularnewline
24 & 410.97 & 412.192 & 414.97 & -2.77803 & -1.22197 \tabularnewline
25 & 410.97 & 412.479 & 416.333 & -3.8542 & -1.50913 \tabularnewline
26 & 413.8 & 416.936 & 417.689 & -0.752868 & -3.1363 \tabularnewline
27 & 423.31 & 421.016 & 419.055 & 1.96147 & 2.29353 \tabularnewline
28 & 423.85 & 423.224 & 420.449 & 2.7753 & 0.625535 \tabularnewline
29 & 426.6 & 424.788 & 421.881 & 2.90763 & 1.81153 \tabularnewline
30 & 426.26 & 425.38 & 423.353 & 2.02672 & 0.880368 \tabularnewline
31 & 426.26 & 425.776 & 424.839 & 0.936965 & 0.484285 \tabularnewline
32 & 426.32 & 426.643 & 426.46 & 0.183049 & -0.322632 \tabularnewline
33 & 427.14 & 427.296 & 427.852 & -0.555868 & -0.156215 \tabularnewline
34 & 427.55 & 428.066 & 429.071 & -1.00512 & -0.515715 \tabularnewline
35 & 428.29 & 428.53 & 430.375 & -1.84503 & -0.239549 \tabularnewline
36 & 428.8 & 428.812 & 431.59 & -2.77803 & -0.0119653 \tabularnewline
37 & 428.8 & 428.967 & 432.822 & -3.8542 & -0.167465 \tabularnewline
38 & 434.87 & 433.333 & 434.086 & -0.752868 & 1.53703 \tabularnewline
39 & 435.66 & 437.311 & 435.35 & 1.96147 & -1.65147 \tabularnewline
40 & 440.75 & 439.363 & 436.588 & 2.7753 & 1.38678 \tabularnewline
41 & 440.99 & 440.723 & 437.815 & 2.90763 & 0.267368 \tabularnewline
42 & 441.04 & 441.03 & 439.004 & 2.02672 & 0.00953472 \tabularnewline
43 & 441.04 & 441.108 & 440.171 & 0.936965 & -0.0682153 \tabularnewline
44 & 441.88 & 441.451 & 441.268 & 0.183049 & 0.428618 \tabularnewline
45 & 441.92 & 441.678 & 442.234 & -0.555868 & 0.241701 \tabularnewline
46 & 442.48 & 442.007 & 443.012 & -1.00512 & 0.472618 \tabularnewline
47 & 442.81 & 441.815 & 443.66 & -1.84503 & 0.995035 \tabularnewline
48 & 442.81 & 441.524 & 444.302 & -2.77803 & 1.28595 \tabularnewline
49 & 442.81 & 441.103 & 444.957 & -3.8542 & 1.70712 \tabularnewline
50 & 447.19 & 444.837 & 445.59 & -0.752868 & 2.35328 \tabularnewline
51 & 446.52 & 448.131 & 446.169 & 1.96147 & -1.61063 \tabularnewline
52 & 448.57 & 449.543 & 446.767 & 2.7753 & -0.972799 \tabularnewline
53 & 448.71 & 450.29 & 447.382 & 2.90763 & -1.57972 \tabularnewline
54 & 448.73 & 450.005 & 447.978 & 2.02672 & -1.27463 \tabularnewline
55 & 449.07 & 449.511 & 448.574 & 0.936965 & -0.440715 \tabularnewline
56 & 449.03 & 449.278 & 449.095 & 0.183049 & -0.248465 \tabularnewline
57 & 448.68 & 449.13 & 449.685 & -0.555868 & -0.449549 \tabularnewline
58 & 450.08 & 449.364 & 450.37 & -1.00512 & 0.715535 \tabularnewline
59 & 449.96 & 449.177 & 451.023 & -1.84503 & 0.782535 \tabularnewline
60 & 449.96 & 448.95 & 451.728 & -2.77803 & 1.0097 \tabularnewline
61 & 449.96 & 448.602 & 452.456 & -3.8542 & 1.35837 \tabularnewline
62 & 452.56 & 452.419 & 453.172 & -0.752868 & 0.141201 \tabularnewline
63 & 455.31 & 455.894 & 453.932 & 1.96147 & -0.583965 \tabularnewline
64 & 456.2 & 457.508 & 454.732 & 2.7753 & -1.3078 \tabularnewline
65 & 456.75 & 458.463 & 455.556 & 2.90763 & -1.71347 \tabularnewline
66 & 457.63 & 458.421 & 456.395 & 2.02672 & -0.791299 \tabularnewline
67 & 457.63 & NA & NA & 0.936965 & NA \tabularnewline
68 & 457.65 & NA & NA & 0.183049 & NA \tabularnewline
69 & 458.32 & NA & NA & -0.555868 & NA \tabularnewline
70 & 459.64 & NA & NA & -1.00512 & NA \tabularnewline
71 & 460.16 & NA & NA & -1.84503 & NA \tabularnewline
72 & 459.89 & NA & NA & -2.77803 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261453&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]389.09[/C][C]NA[/C][C]NA[/C][C]-3.8542[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]391.76[/C][C]NA[/C][C]NA[/C][C]-0.752868[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]390.96[/C][C]NA[/C][C]NA[/C][C]1.96147[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]391.76[/C][C]NA[/C][C]NA[/C][C]2.7753[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]392.8[/C][C]NA[/C][C]NA[/C][C]2.90763[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]393.06[/C][C]NA[/C][C]NA[/C][C]2.02672[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]393.06[/C][C]393.934[/C][C]392.997[/C][C]0.936965[/C][C]-0.874465[/C][/ROW]
[ROW][C]8[/C][C]393.26[/C][C]393.734[/C][C]393.551[/C][C]0.183049[/C][C]-0.474299[/C][/ROW]
[ROW][C]9[/C][C]393.87[/C][C]393.953[/C][C]394.509[/C][C]-0.555868[/C][C]-0.0828819[/C][/ROW]
[ROW][C]10[/C][C]394.47[/C][C]394.772[/C][C]395.777[/C][C]-1.00512[/C][C]-0.301965[/C][/ROW]
[ROW][C]11[/C][C]394.57[/C][C]395.262[/C][C]397.107[/C][C]-1.84503[/C][C]-0.692465[/C][/ROW]
[ROW][C]12[/C][C]394.57[/C][C]395.725[/C][C]398.503[/C][C]-2.77803[/C][C]-1.1553[/C][/ROW]
[ROW][C]13[/C][C]394.57[/C][C]396.052[/C][C]399.907[/C][C]-3.8542[/C][C]-1.48247[/C][/ROW]
[ROW][C]14[/C][C]399.57[/C][C]400.559[/C][C]401.312[/C][C]-0.752868[/C][C]-0.988799[/C][/ROW]
[ROW][C]15[/C][C]406.13[/C][C]404.671[/C][C]402.71[/C][C]1.96147[/C][C]1.45895[/C][/ROW]
[ROW][C]16[/C][C]407.03[/C][C]406.855[/C][C]404.08[/C][C]2.7753[/C][C]0.174701[/C][/ROW]
[ROW][C]17[/C][C]409.46[/C][C]408.339[/C][C]405.432[/C][C]2.90763[/C][C]1.1207[/C][/ROW]
[ROW][C]18[/C][C]409.9[/C][C]408.818[/C][C]406.791[/C][C]2.02672[/C][C]1.08245[/C][/ROW]
[ROW][C]19[/C][C]409.9[/C][C]409.094[/C][C]408.158[/C][C]0.936965[/C][C]0.805535[/C][/ROW]
[ROW][C]20[/C][C]410.14[/C][C]409.617[/C][C]409.434[/C][C]0.183049[/C][C]0.523201[/C][/ROW]
[ROW][C]21[/C][C]410.54[/C][C]410.187[/C][C]410.742[/C][C]-0.555868[/C][C]0.353368[/C][/ROW]
[ROW][C]22[/C][C]410.69[/C][C]411.154[/C][C]412.159[/C][C]-1.00512[/C][C]-0.464049[/C][/ROW]
[ROW][C]23[/C][C]410.79[/C][C]411.729[/C][C]413.574[/C][C]-1.84503[/C][C]-0.939132[/C][/ROW]
[ROW][C]24[/C][C]410.97[/C][C]412.192[/C][C]414.97[/C][C]-2.77803[/C][C]-1.22197[/C][/ROW]
[ROW][C]25[/C][C]410.97[/C][C]412.479[/C][C]416.333[/C][C]-3.8542[/C][C]-1.50913[/C][/ROW]
[ROW][C]26[/C][C]413.8[/C][C]416.936[/C][C]417.689[/C][C]-0.752868[/C][C]-3.1363[/C][/ROW]
[ROW][C]27[/C][C]423.31[/C][C]421.016[/C][C]419.055[/C][C]1.96147[/C][C]2.29353[/C][/ROW]
[ROW][C]28[/C][C]423.85[/C][C]423.224[/C][C]420.449[/C][C]2.7753[/C][C]0.625535[/C][/ROW]
[ROW][C]29[/C][C]426.6[/C][C]424.788[/C][C]421.881[/C][C]2.90763[/C][C]1.81153[/C][/ROW]
[ROW][C]30[/C][C]426.26[/C][C]425.38[/C][C]423.353[/C][C]2.02672[/C][C]0.880368[/C][/ROW]
[ROW][C]31[/C][C]426.26[/C][C]425.776[/C][C]424.839[/C][C]0.936965[/C][C]0.484285[/C][/ROW]
[ROW][C]32[/C][C]426.32[/C][C]426.643[/C][C]426.46[/C][C]0.183049[/C][C]-0.322632[/C][/ROW]
[ROW][C]33[/C][C]427.14[/C][C]427.296[/C][C]427.852[/C][C]-0.555868[/C][C]-0.156215[/C][/ROW]
[ROW][C]34[/C][C]427.55[/C][C]428.066[/C][C]429.071[/C][C]-1.00512[/C][C]-0.515715[/C][/ROW]
[ROW][C]35[/C][C]428.29[/C][C]428.53[/C][C]430.375[/C][C]-1.84503[/C][C]-0.239549[/C][/ROW]
[ROW][C]36[/C][C]428.8[/C][C]428.812[/C][C]431.59[/C][C]-2.77803[/C][C]-0.0119653[/C][/ROW]
[ROW][C]37[/C][C]428.8[/C][C]428.967[/C][C]432.822[/C][C]-3.8542[/C][C]-0.167465[/C][/ROW]
[ROW][C]38[/C][C]434.87[/C][C]433.333[/C][C]434.086[/C][C]-0.752868[/C][C]1.53703[/C][/ROW]
[ROW][C]39[/C][C]435.66[/C][C]437.311[/C][C]435.35[/C][C]1.96147[/C][C]-1.65147[/C][/ROW]
[ROW][C]40[/C][C]440.75[/C][C]439.363[/C][C]436.588[/C][C]2.7753[/C][C]1.38678[/C][/ROW]
[ROW][C]41[/C][C]440.99[/C][C]440.723[/C][C]437.815[/C][C]2.90763[/C][C]0.267368[/C][/ROW]
[ROW][C]42[/C][C]441.04[/C][C]441.03[/C][C]439.004[/C][C]2.02672[/C][C]0.00953472[/C][/ROW]
[ROW][C]43[/C][C]441.04[/C][C]441.108[/C][C]440.171[/C][C]0.936965[/C][C]-0.0682153[/C][/ROW]
[ROW][C]44[/C][C]441.88[/C][C]441.451[/C][C]441.268[/C][C]0.183049[/C][C]0.428618[/C][/ROW]
[ROW][C]45[/C][C]441.92[/C][C]441.678[/C][C]442.234[/C][C]-0.555868[/C][C]0.241701[/C][/ROW]
[ROW][C]46[/C][C]442.48[/C][C]442.007[/C][C]443.012[/C][C]-1.00512[/C][C]0.472618[/C][/ROW]
[ROW][C]47[/C][C]442.81[/C][C]441.815[/C][C]443.66[/C][C]-1.84503[/C][C]0.995035[/C][/ROW]
[ROW][C]48[/C][C]442.81[/C][C]441.524[/C][C]444.302[/C][C]-2.77803[/C][C]1.28595[/C][/ROW]
[ROW][C]49[/C][C]442.81[/C][C]441.103[/C][C]444.957[/C][C]-3.8542[/C][C]1.70712[/C][/ROW]
[ROW][C]50[/C][C]447.19[/C][C]444.837[/C][C]445.59[/C][C]-0.752868[/C][C]2.35328[/C][/ROW]
[ROW][C]51[/C][C]446.52[/C][C]448.131[/C][C]446.169[/C][C]1.96147[/C][C]-1.61063[/C][/ROW]
[ROW][C]52[/C][C]448.57[/C][C]449.543[/C][C]446.767[/C][C]2.7753[/C][C]-0.972799[/C][/ROW]
[ROW][C]53[/C][C]448.71[/C][C]450.29[/C][C]447.382[/C][C]2.90763[/C][C]-1.57972[/C][/ROW]
[ROW][C]54[/C][C]448.73[/C][C]450.005[/C][C]447.978[/C][C]2.02672[/C][C]-1.27463[/C][/ROW]
[ROW][C]55[/C][C]449.07[/C][C]449.511[/C][C]448.574[/C][C]0.936965[/C][C]-0.440715[/C][/ROW]
[ROW][C]56[/C][C]449.03[/C][C]449.278[/C][C]449.095[/C][C]0.183049[/C][C]-0.248465[/C][/ROW]
[ROW][C]57[/C][C]448.68[/C][C]449.13[/C][C]449.685[/C][C]-0.555868[/C][C]-0.449549[/C][/ROW]
[ROW][C]58[/C][C]450.08[/C][C]449.364[/C][C]450.37[/C][C]-1.00512[/C][C]0.715535[/C][/ROW]
[ROW][C]59[/C][C]449.96[/C][C]449.177[/C][C]451.023[/C][C]-1.84503[/C][C]0.782535[/C][/ROW]
[ROW][C]60[/C][C]449.96[/C][C]448.95[/C][C]451.728[/C][C]-2.77803[/C][C]1.0097[/C][/ROW]
[ROW][C]61[/C][C]449.96[/C][C]448.602[/C][C]452.456[/C][C]-3.8542[/C][C]1.35837[/C][/ROW]
[ROW][C]62[/C][C]452.56[/C][C]452.419[/C][C]453.172[/C][C]-0.752868[/C][C]0.141201[/C][/ROW]
[ROW][C]63[/C][C]455.31[/C][C]455.894[/C][C]453.932[/C][C]1.96147[/C][C]-0.583965[/C][/ROW]
[ROW][C]64[/C][C]456.2[/C][C]457.508[/C][C]454.732[/C][C]2.7753[/C][C]-1.3078[/C][/ROW]
[ROW][C]65[/C][C]456.75[/C][C]458.463[/C][C]455.556[/C][C]2.90763[/C][C]-1.71347[/C][/ROW]
[ROW][C]66[/C][C]457.63[/C][C]458.421[/C][C]456.395[/C][C]2.02672[/C][C]-0.791299[/C][/ROW]
[ROW][C]67[/C][C]457.63[/C][C]NA[/C][C]NA[/C][C]0.936965[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]457.65[/C][C]NA[/C][C]NA[/C][C]0.183049[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]458.32[/C][C]NA[/C][C]NA[/C][C]-0.555868[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]459.64[/C][C]NA[/C][C]NA[/C][C]-1.00512[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]460.16[/C][C]NA[/C][C]NA[/C][C]-1.84503[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]459.89[/C][C]NA[/C][C]NA[/C][C]-2.77803[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261453&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261453&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	389.09	NA	NA	-3.8542	NA
2	391.76	NA	NA	-0.752868	NA
3	390.96	NA	NA	1.96147	NA
4	391.76	NA	NA	2.7753	NA
5	392.8	NA	NA	2.90763	NA
6	393.06	NA	NA	2.02672	NA
7	393.06	393.934	392.997	0.936965	-0.874465
8	393.26	393.734	393.551	0.183049	-0.474299
9	393.87	393.953	394.509	-0.555868	-0.0828819
10	394.47	394.772	395.777	-1.00512	-0.301965
11	394.57	395.262	397.107	-1.84503	-0.692465
12	394.57	395.725	398.503	-2.77803	-1.1553
13	394.57	396.052	399.907	-3.8542	-1.48247
14	399.57	400.559	401.312	-0.752868	-0.988799
15	406.13	404.671	402.71	1.96147	1.45895
16	407.03	406.855	404.08	2.7753	0.174701
17	409.46	408.339	405.432	2.90763	1.1207
18	409.9	408.818	406.791	2.02672	1.08245
19	409.9	409.094	408.158	0.936965	0.805535
20	410.14	409.617	409.434	0.183049	0.523201
21	410.54	410.187	410.742	-0.555868	0.353368
22	410.69	411.154	412.159	-1.00512	-0.464049
23	410.79	411.729	413.574	-1.84503	-0.939132
24	410.97	412.192	414.97	-2.77803	-1.22197
25	410.97	412.479	416.333	-3.8542	-1.50913
26	413.8	416.936	417.689	-0.752868	-3.1363
27	423.31	421.016	419.055	1.96147	2.29353
28	423.85	423.224	420.449	2.7753	0.625535
29	426.6	424.788	421.881	2.90763	1.81153
30	426.26	425.38	423.353	2.02672	0.880368
31	426.26	425.776	424.839	0.936965	0.484285
32	426.32	426.643	426.46	0.183049	-0.322632
33	427.14	427.296	427.852	-0.555868	-0.156215
34	427.55	428.066	429.071	-1.00512	-0.515715
35	428.29	428.53	430.375	-1.84503	-0.239549
36	428.8	428.812	431.59	-2.77803	-0.0119653
37	428.8	428.967	432.822	-3.8542	-0.167465
38	434.87	433.333	434.086	-0.752868	1.53703
39	435.66	437.311	435.35	1.96147	-1.65147
40	440.75	439.363	436.588	2.7753	1.38678
41	440.99	440.723	437.815	2.90763	0.267368
42	441.04	441.03	439.004	2.02672	0.00953472
43	441.04	441.108	440.171	0.936965	-0.0682153
44	441.88	441.451	441.268	0.183049	0.428618
45	441.92	441.678	442.234	-0.555868	0.241701
46	442.48	442.007	443.012	-1.00512	0.472618
47	442.81	441.815	443.66	-1.84503	0.995035
48	442.81	441.524	444.302	-2.77803	1.28595
49	442.81	441.103	444.957	-3.8542	1.70712
50	447.19	444.837	445.59	-0.752868	2.35328
51	446.52	448.131	446.169	1.96147	-1.61063
52	448.57	449.543	446.767	2.7753	-0.972799
53	448.71	450.29	447.382	2.90763	-1.57972
54	448.73	450.005	447.978	2.02672	-1.27463
55	449.07	449.511	448.574	0.936965	-0.440715
56	449.03	449.278	449.095	0.183049	-0.248465
57	448.68	449.13	449.685	-0.555868	-0.449549
58	450.08	449.364	450.37	-1.00512	0.715535
59	449.96	449.177	451.023	-1.84503	0.782535
60	449.96	448.95	451.728	-2.77803	1.0097
61	449.96	448.602	452.456	-3.8542	1.35837
62	452.56	452.419	453.172	-0.752868	0.141201
63	455.31	455.894	453.932	1.96147	-0.583965
64	456.2	457.508	454.732	2.7753	-1.3078
65	456.75	458.463	455.556	2.90763	-1.71347
66	457.63	458.421	456.395	2.02672	-0.791299
67	457.63	NA	NA	0.936965	NA
68	457.65	NA	NA	0.183049	NA
69	458.32	NA	NA	-0.555868	NA
70	459.64	NA	NA	-1.00512	NA
71	460.16	NA	NA	-1.84503	NA
72	459.89	NA	NA	-2.77803	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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