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

Sat, 29 Nov 2014 15:26:28 +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/29/t1417275069tcg06tfz5o2sq1y.htm/, Retrieved Sun, 19 May 2024 14:13:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261180, Retrieved Sun, 19 May 2024 14:13:00 +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] [] [2014-11-29 15:26:28] [c53b0bb515ebe5f6f1384250cc1174dd] [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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261180&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261180&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261180&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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	246.78	NA	NA	-1.69474	NA
2	247.91	NA	NA	-0.719069	NA
3	247.99	NA	NA	0.381847	NA
4	248.6	NA	NA	1.4621	NA
5	248.68	NA	NA	1.43785	NA
6	248.75	NA	NA	0.869431	NA
7	248.75	249.102	248.772	0.330681	-0.352347
8	249.03	248.988	249.005	-0.0162361	0.0416528
9	249.05	249.159	249.384	-0.225153	-0.109014
10	249.57	249.81	249.917	-0.106653	-0.240014
11	249.35	249.908	250.524	-0.616319	-0.557847
12	249.46	250.086	251.19	-1.10374	-0.626264
13	249.46	250.16	251.855	-1.69474	-0.700264
14	250.82	251.817	252.536	-0.719069	-0.996764
15	254.19	253.63	253.248	0.381847	0.560236
16	255.18	255.453	253.991	1.4621	-0.272931
17	256.68	256.198	254.76	1.43785	0.482153
18	256.73	256.413	255.544	0.869431	0.316819
19	256.73	256.662	256.331	0.330681	0.0680694
20	257.39	257.149	257.165	-0.0162361	0.241236
21	257.78	257.723	257.948	-0.225153	0.0572361
22	258.67	258.5	258.607	-0.106653	0.169569
23	258.71	258.58	259.197	-0.616319	0.129653
24	258.91	258.62	259.724	-1.10374	0.289569
25	258.91	258.538	260.232	-1.69474	0.372236
26	261.38	260.005	260.724	-0.719069	1.3749
27	262.42	261.586	261.204	0.381847	0.833986
28	262.77	263.201	261.739	1.4621	-0.430847
29	263.24	263.776	262.338	1.43785	-0.535764
30	262.83	263.822	262.952	0.869431	-0.991514
31	262.83	263.897	263.566	0.330681	-1.06693
32	263.09	264.18	264.197	-0.0162361	-1.09043
33	263.6	264.651	264.876	-0.225153	-1.05068
34	265.68	265.55	265.657	-0.106653	0.129986
35	266.08	265.877	266.494	-0.616319	0.202569
36	266.28	266.298	267.402	-1.10374	-0.0179306
37	266.28	266.699	268.393	-1.69474	-0.418597
38	269.14	268.649	269.368	-0.719069	0.490736
39	270.96	270.711	270.329	0.381847	0.249403
40	272.97	272.667	271.205	1.4621	0.302903
41	273.13	273.425	271.987	1.43785	-0.295347
42	274.73	273.624	272.755	0.869431	1.10557
43	274.73	273.846	273.515	0.330681	0.884319
44	274.59	274.153	274.169	-0.0162361	0.437486
45	275.15	274.394	274.62	-0.225153	0.755569
46	275.16	274.943	275.05	-0.106653	0.217069
47	275.38	274.935	275.551	-0.616319	0.445069
48	275.4	274.879	275.982	-1.10374	0.521236
49	275.4	274.653	276.348	-1.69474	0.747236
50	275.71	275.996	276.715	-0.719069	-0.285514
51	275.21	277.454	277.072	0.381847	-2.24393
52	279.04	278.881	277.419	1.4621	0.158736
53	279.1	279.197	277.759	1.43785	-0.0970139
54	279.11	278.961	278.091	0.869431	0.149319
55	279.11	278.754	278.424	0.330681	0.355569
56	279.02	278.761	278.777	-0.0162361	0.258736
57	279.3	279.064	279.29	-0.225153	0.235569
58	279.34	279.728	279.835	-0.106653	-0.387931
59	279.36	279.691	280.307	-0.616319	-0.330764
60	279.39	279.668	280.772	-1.10374	-0.277931
61	279.39	279.502	281.197	-1.69474	-0.111931
62	280.21	280.905	281.624	-0.719069	-0.694681
63	283	282.511	282.129	0.381847	0.488986
64	284.33	284.199	282.737	1.4621	0.130819
65	285.15	284.815	283.377	1.43785	0.334653
66	284.21	284.902	284.032	0.869431	-0.691514
67	284.21	NA	NA	0.330681	NA
68	284.17	NA	NA	-0.0162361	NA
69	286.28	NA	NA	-0.225153	NA
70	286.95	NA	NA	-0.106653	NA
71	287.12	NA	NA	-0.616319	NA
72	287.34	NA	NA	-1.10374	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 246.78 & NA & NA & -1.69474 & NA \tabularnewline
2 & 247.91 & NA & NA & -0.719069 & NA \tabularnewline
3 & 247.99 & NA & NA & 0.381847 & NA \tabularnewline
4 & 248.6 & NA & NA & 1.4621 & NA \tabularnewline
5 & 248.68 & NA & NA & 1.43785 & NA \tabularnewline
6 & 248.75 & NA & NA & 0.869431 & NA \tabularnewline
7 & 248.75 & 249.102 & 248.772 & 0.330681 & -0.352347 \tabularnewline
8 & 249.03 & 248.988 & 249.005 & -0.0162361 & 0.0416528 \tabularnewline
9 & 249.05 & 249.159 & 249.384 & -0.225153 & -0.109014 \tabularnewline
10 & 249.57 & 249.81 & 249.917 & -0.106653 & -0.240014 \tabularnewline
11 & 249.35 & 249.908 & 250.524 & -0.616319 & -0.557847 \tabularnewline
12 & 249.46 & 250.086 & 251.19 & -1.10374 & -0.626264 \tabularnewline
13 & 249.46 & 250.16 & 251.855 & -1.69474 & -0.700264 \tabularnewline
14 & 250.82 & 251.817 & 252.536 & -0.719069 & -0.996764 \tabularnewline
15 & 254.19 & 253.63 & 253.248 & 0.381847 & 0.560236 \tabularnewline
16 & 255.18 & 255.453 & 253.991 & 1.4621 & -0.272931 \tabularnewline
17 & 256.68 & 256.198 & 254.76 & 1.43785 & 0.482153 \tabularnewline
18 & 256.73 & 256.413 & 255.544 & 0.869431 & 0.316819 \tabularnewline
19 & 256.73 & 256.662 & 256.331 & 0.330681 & 0.0680694 \tabularnewline
20 & 257.39 & 257.149 & 257.165 & -0.0162361 & 0.241236 \tabularnewline
21 & 257.78 & 257.723 & 257.948 & -0.225153 & 0.0572361 \tabularnewline
22 & 258.67 & 258.5 & 258.607 & -0.106653 & 0.169569 \tabularnewline
23 & 258.71 & 258.58 & 259.197 & -0.616319 & 0.129653 \tabularnewline
24 & 258.91 & 258.62 & 259.724 & -1.10374 & 0.289569 \tabularnewline
25 & 258.91 & 258.538 & 260.232 & -1.69474 & 0.372236 \tabularnewline
26 & 261.38 & 260.005 & 260.724 & -0.719069 & 1.3749 \tabularnewline
27 & 262.42 & 261.586 & 261.204 & 0.381847 & 0.833986 \tabularnewline
28 & 262.77 & 263.201 & 261.739 & 1.4621 & -0.430847 \tabularnewline
29 & 263.24 & 263.776 & 262.338 & 1.43785 & -0.535764 \tabularnewline
30 & 262.83 & 263.822 & 262.952 & 0.869431 & -0.991514 \tabularnewline
31 & 262.83 & 263.897 & 263.566 & 0.330681 & -1.06693 \tabularnewline
32 & 263.09 & 264.18 & 264.197 & -0.0162361 & -1.09043 \tabularnewline
33 & 263.6 & 264.651 & 264.876 & -0.225153 & -1.05068 \tabularnewline
34 & 265.68 & 265.55 & 265.657 & -0.106653 & 0.129986 \tabularnewline
35 & 266.08 & 265.877 & 266.494 & -0.616319 & 0.202569 \tabularnewline
36 & 266.28 & 266.298 & 267.402 & -1.10374 & -0.0179306 \tabularnewline
37 & 266.28 & 266.699 & 268.393 & -1.69474 & -0.418597 \tabularnewline
38 & 269.14 & 268.649 & 269.368 & -0.719069 & 0.490736 \tabularnewline
39 & 270.96 & 270.711 & 270.329 & 0.381847 & 0.249403 \tabularnewline
40 & 272.97 & 272.667 & 271.205 & 1.4621 & 0.302903 \tabularnewline
41 & 273.13 & 273.425 & 271.987 & 1.43785 & -0.295347 \tabularnewline
42 & 274.73 & 273.624 & 272.755 & 0.869431 & 1.10557 \tabularnewline
43 & 274.73 & 273.846 & 273.515 & 0.330681 & 0.884319 \tabularnewline
44 & 274.59 & 274.153 & 274.169 & -0.0162361 & 0.437486 \tabularnewline
45 & 275.15 & 274.394 & 274.62 & -0.225153 & 0.755569 \tabularnewline
46 & 275.16 & 274.943 & 275.05 & -0.106653 & 0.217069 \tabularnewline
47 & 275.38 & 274.935 & 275.551 & -0.616319 & 0.445069 \tabularnewline
48 & 275.4 & 274.879 & 275.982 & -1.10374 & 0.521236 \tabularnewline
49 & 275.4 & 274.653 & 276.348 & -1.69474 & 0.747236 \tabularnewline
50 & 275.71 & 275.996 & 276.715 & -0.719069 & -0.285514 \tabularnewline
51 & 275.21 & 277.454 & 277.072 & 0.381847 & -2.24393 \tabularnewline
52 & 279.04 & 278.881 & 277.419 & 1.4621 & 0.158736 \tabularnewline
53 & 279.1 & 279.197 & 277.759 & 1.43785 & -0.0970139 \tabularnewline
54 & 279.11 & 278.961 & 278.091 & 0.869431 & 0.149319 \tabularnewline
55 & 279.11 & 278.754 & 278.424 & 0.330681 & 0.355569 \tabularnewline
56 & 279.02 & 278.761 & 278.777 & -0.0162361 & 0.258736 \tabularnewline
57 & 279.3 & 279.064 & 279.29 & -0.225153 & 0.235569 \tabularnewline
58 & 279.34 & 279.728 & 279.835 & -0.106653 & -0.387931 \tabularnewline
59 & 279.36 & 279.691 & 280.307 & -0.616319 & -0.330764 \tabularnewline
60 & 279.39 & 279.668 & 280.772 & -1.10374 & -0.277931 \tabularnewline
61 & 279.39 & 279.502 & 281.197 & -1.69474 & -0.111931 \tabularnewline
62 & 280.21 & 280.905 & 281.624 & -0.719069 & -0.694681 \tabularnewline
63 & 283 & 282.511 & 282.129 & 0.381847 & 0.488986 \tabularnewline
64 & 284.33 & 284.199 & 282.737 & 1.4621 & 0.130819 \tabularnewline
65 & 285.15 & 284.815 & 283.377 & 1.43785 & 0.334653 \tabularnewline
66 & 284.21 & 284.902 & 284.032 & 0.869431 & -0.691514 \tabularnewline
67 & 284.21 & NA & NA & 0.330681 & NA \tabularnewline
68 & 284.17 & NA & NA & -0.0162361 & NA \tabularnewline
69 & 286.28 & NA & NA & -0.225153 & NA \tabularnewline
70 & 286.95 & NA & NA & -0.106653 & NA \tabularnewline
71 & 287.12 & NA & NA & -0.616319 & NA \tabularnewline
72 & 287.34 & NA & NA & -1.10374 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261180&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]246.78[/C][C]NA[/C][C]NA[/C][C]-1.69474[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]247.91[/C][C]NA[/C][C]NA[/C][C]-0.719069[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]247.99[/C][C]NA[/C][C]NA[/C][C]0.381847[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]248.6[/C][C]NA[/C][C]NA[/C][C]1.4621[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]248.68[/C][C]NA[/C][C]NA[/C][C]1.43785[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]248.75[/C][C]NA[/C][C]NA[/C][C]0.869431[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]248.75[/C][C]249.102[/C][C]248.772[/C][C]0.330681[/C][C]-0.352347[/C][/ROW]
[ROW][C]8[/C][C]249.03[/C][C]248.988[/C][C]249.005[/C][C]-0.0162361[/C][C]0.0416528[/C][/ROW]
[ROW][C]9[/C][C]249.05[/C][C]249.159[/C][C]249.384[/C][C]-0.225153[/C][C]-0.109014[/C][/ROW]
[ROW][C]10[/C][C]249.57[/C][C]249.81[/C][C]249.917[/C][C]-0.106653[/C][C]-0.240014[/C][/ROW]
[ROW][C]11[/C][C]249.35[/C][C]249.908[/C][C]250.524[/C][C]-0.616319[/C][C]-0.557847[/C][/ROW]
[ROW][C]12[/C][C]249.46[/C][C]250.086[/C][C]251.19[/C][C]-1.10374[/C][C]-0.626264[/C][/ROW]
[ROW][C]13[/C][C]249.46[/C][C]250.16[/C][C]251.855[/C][C]-1.69474[/C][C]-0.700264[/C][/ROW]
[ROW][C]14[/C][C]250.82[/C][C]251.817[/C][C]252.536[/C][C]-0.719069[/C][C]-0.996764[/C][/ROW]
[ROW][C]15[/C][C]254.19[/C][C]253.63[/C][C]253.248[/C][C]0.381847[/C][C]0.560236[/C][/ROW]
[ROW][C]16[/C][C]255.18[/C][C]255.453[/C][C]253.991[/C][C]1.4621[/C][C]-0.272931[/C][/ROW]
[ROW][C]17[/C][C]256.68[/C][C]256.198[/C][C]254.76[/C][C]1.43785[/C][C]0.482153[/C][/ROW]
[ROW][C]18[/C][C]256.73[/C][C]256.413[/C][C]255.544[/C][C]0.869431[/C][C]0.316819[/C][/ROW]
[ROW][C]19[/C][C]256.73[/C][C]256.662[/C][C]256.331[/C][C]0.330681[/C][C]0.0680694[/C][/ROW]
[ROW][C]20[/C][C]257.39[/C][C]257.149[/C][C]257.165[/C][C]-0.0162361[/C][C]0.241236[/C][/ROW]
[ROW][C]21[/C][C]257.78[/C][C]257.723[/C][C]257.948[/C][C]-0.225153[/C][C]0.0572361[/C][/ROW]
[ROW][C]22[/C][C]258.67[/C][C]258.5[/C][C]258.607[/C][C]-0.106653[/C][C]0.169569[/C][/ROW]
[ROW][C]23[/C][C]258.71[/C][C]258.58[/C][C]259.197[/C][C]-0.616319[/C][C]0.129653[/C][/ROW]
[ROW][C]24[/C][C]258.91[/C][C]258.62[/C][C]259.724[/C][C]-1.10374[/C][C]0.289569[/C][/ROW]
[ROW][C]25[/C][C]258.91[/C][C]258.538[/C][C]260.232[/C][C]-1.69474[/C][C]0.372236[/C][/ROW]
[ROW][C]26[/C][C]261.38[/C][C]260.005[/C][C]260.724[/C][C]-0.719069[/C][C]1.3749[/C][/ROW]
[ROW][C]27[/C][C]262.42[/C][C]261.586[/C][C]261.204[/C][C]0.381847[/C][C]0.833986[/C][/ROW]
[ROW][C]28[/C][C]262.77[/C][C]263.201[/C][C]261.739[/C][C]1.4621[/C][C]-0.430847[/C][/ROW]
[ROW][C]29[/C][C]263.24[/C][C]263.776[/C][C]262.338[/C][C]1.43785[/C][C]-0.535764[/C][/ROW]
[ROW][C]30[/C][C]262.83[/C][C]263.822[/C][C]262.952[/C][C]0.869431[/C][C]-0.991514[/C][/ROW]
[ROW][C]31[/C][C]262.83[/C][C]263.897[/C][C]263.566[/C][C]0.330681[/C][C]-1.06693[/C][/ROW]
[ROW][C]32[/C][C]263.09[/C][C]264.18[/C][C]264.197[/C][C]-0.0162361[/C][C]-1.09043[/C][/ROW]
[ROW][C]33[/C][C]263.6[/C][C]264.651[/C][C]264.876[/C][C]-0.225153[/C][C]-1.05068[/C][/ROW]
[ROW][C]34[/C][C]265.68[/C][C]265.55[/C][C]265.657[/C][C]-0.106653[/C][C]0.129986[/C][/ROW]
[ROW][C]35[/C][C]266.08[/C][C]265.877[/C][C]266.494[/C][C]-0.616319[/C][C]0.202569[/C][/ROW]
[ROW][C]36[/C][C]266.28[/C][C]266.298[/C][C]267.402[/C][C]-1.10374[/C][C]-0.0179306[/C][/ROW]
[ROW][C]37[/C][C]266.28[/C][C]266.699[/C][C]268.393[/C][C]-1.69474[/C][C]-0.418597[/C][/ROW]
[ROW][C]38[/C][C]269.14[/C][C]268.649[/C][C]269.368[/C][C]-0.719069[/C][C]0.490736[/C][/ROW]
[ROW][C]39[/C][C]270.96[/C][C]270.711[/C][C]270.329[/C][C]0.381847[/C][C]0.249403[/C][/ROW]
[ROW][C]40[/C][C]272.97[/C][C]272.667[/C][C]271.205[/C][C]1.4621[/C][C]0.302903[/C][/ROW]
[ROW][C]41[/C][C]273.13[/C][C]273.425[/C][C]271.987[/C][C]1.43785[/C][C]-0.295347[/C][/ROW]
[ROW][C]42[/C][C]274.73[/C][C]273.624[/C][C]272.755[/C][C]0.869431[/C][C]1.10557[/C][/ROW]
[ROW][C]43[/C][C]274.73[/C][C]273.846[/C][C]273.515[/C][C]0.330681[/C][C]0.884319[/C][/ROW]
[ROW][C]44[/C][C]274.59[/C][C]274.153[/C][C]274.169[/C][C]-0.0162361[/C][C]0.437486[/C][/ROW]
[ROW][C]45[/C][C]275.15[/C][C]274.394[/C][C]274.62[/C][C]-0.225153[/C][C]0.755569[/C][/ROW]
[ROW][C]46[/C][C]275.16[/C][C]274.943[/C][C]275.05[/C][C]-0.106653[/C][C]0.217069[/C][/ROW]
[ROW][C]47[/C][C]275.38[/C][C]274.935[/C][C]275.551[/C][C]-0.616319[/C][C]0.445069[/C][/ROW]
[ROW][C]48[/C][C]275.4[/C][C]274.879[/C][C]275.982[/C][C]-1.10374[/C][C]0.521236[/C][/ROW]
[ROW][C]49[/C][C]275.4[/C][C]274.653[/C][C]276.348[/C][C]-1.69474[/C][C]0.747236[/C][/ROW]
[ROW][C]50[/C][C]275.71[/C][C]275.996[/C][C]276.715[/C][C]-0.719069[/C][C]-0.285514[/C][/ROW]
[ROW][C]51[/C][C]275.21[/C][C]277.454[/C][C]277.072[/C][C]0.381847[/C][C]-2.24393[/C][/ROW]
[ROW][C]52[/C][C]279.04[/C][C]278.881[/C][C]277.419[/C][C]1.4621[/C][C]0.158736[/C][/ROW]
[ROW][C]53[/C][C]279.1[/C][C]279.197[/C][C]277.759[/C][C]1.43785[/C][C]-0.0970139[/C][/ROW]
[ROW][C]54[/C][C]279.11[/C][C]278.961[/C][C]278.091[/C][C]0.869431[/C][C]0.149319[/C][/ROW]
[ROW][C]55[/C][C]279.11[/C][C]278.754[/C][C]278.424[/C][C]0.330681[/C][C]0.355569[/C][/ROW]
[ROW][C]56[/C][C]279.02[/C][C]278.761[/C][C]278.777[/C][C]-0.0162361[/C][C]0.258736[/C][/ROW]
[ROW][C]57[/C][C]279.3[/C][C]279.064[/C][C]279.29[/C][C]-0.225153[/C][C]0.235569[/C][/ROW]
[ROW][C]58[/C][C]279.34[/C][C]279.728[/C][C]279.835[/C][C]-0.106653[/C][C]-0.387931[/C][/ROW]
[ROW][C]59[/C][C]279.36[/C][C]279.691[/C][C]280.307[/C][C]-0.616319[/C][C]-0.330764[/C][/ROW]
[ROW][C]60[/C][C]279.39[/C][C]279.668[/C][C]280.772[/C][C]-1.10374[/C][C]-0.277931[/C][/ROW]
[ROW][C]61[/C][C]279.39[/C][C]279.502[/C][C]281.197[/C][C]-1.69474[/C][C]-0.111931[/C][/ROW]
[ROW][C]62[/C][C]280.21[/C][C]280.905[/C][C]281.624[/C][C]-0.719069[/C][C]-0.694681[/C][/ROW]
[ROW][C]63[/C][C]283[/C][C]282.511[/C][C]282.129[/C][C]0.381847[/C][C]0.488986[/C][/ROW]
[ROW][C]64[/C][C]284.33[/C][C]284.199[/C][C]282.737[/C][C]1.4621[/C][C]0.130819[/C][/ROW]
[ROW][C]65[/C][C]285.15[/C][C]284.815[/C][C]283.377[/C][C]1.43785[/C][C]0.334653[/C][/ROW]
[ROW][C]66[/C][C]284.21[/C][C]284.902[/C][C]284.032[/C][C]0.869431[/C][C]-0.691514[/C][/ROW]
[ROW][C]67[/C][C]284.21[/C][C]NA[/C][C]NA[/C][C]0.330681[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]284.17[/C][C]NA[/C][C]NA[/C][C]-0.0162361[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]286.28[/C][C]NA[/C][C]NA[/C][C]-0.225153[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]286.95[/C][C]NA[/C][C]NA[/C][C]-0.106653[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]287.12[/C][C]NA[/C][C]NA[/C][C]-0.616319[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]287.34[/C][C]NA[/C][C]NA[/C][C]-1.10374[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261180&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261180&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	246.78	NA	NA	-1.69474	NA
2	247.91	NA	NA	-0.719069	NA
3	247.99	NA	NA	0.381847	NA
4	248.6	NA	NA	1.4621	NA
5	248.68	NA	NA	1.43785	NA
6	248.75	NA	NA	0.869431	NA
7	248.75	249.102	248.772	0.330681	-0.352347
8	249.03	248.988	249.005	-0.0162361	0.0416528
9	249.05	249.159	249.384	-0.225153	-0.109014
10	249.57	249.81	249.917	-0.106653	-0.240014
11	249.35	249.908	250.524	-0.616319	-0.557847
12	249.46	250.086	251.19	-1.10374	-0.626264
13	249.46	250.16	251.855	-1.69474	-0.700264
14	250.82	251.817	252.536	-0.719069	-0.996764
15	254.19	253.63	253.248	0.381847	0.560236
16	255.18	255.453	253.991	1.4621	-0.272931
17	256.68	256.198	254.76	1.43785	0.482153
18	256.73	256.413	255.544	0.869431	0.316819
19	256.73	256.662	256.331	0.330681	0.0680694
20	257.39	257.149	257.165	-0.0162361	0.241236
21	257.78	257.723	257.948	-0.225153	0.0572361
22	258.67	258.5	258.607	-0.106653	0.169569
23	258.71	258.58	259.197	-0.616319	0.129653
24	258.91	258.62	259.724	-1.10374	0.289569
25	258.91	258.538	260.232	-1.69474	0.372236
26	261.38	260.005	260.724	-0.719069	1.3749
27	262.42	261.586	261.204	0.381847	0.833986
28	262.77	263.201	261.739	1.4621	-0.430847
29	263.24	263.776	262.338	1.43785	-0.535764
30	262.83	263.822	262.952	0.869431	-0.991514
31	262.83	263.897	263.566	0.330681	-1.06693
32	263.09	264.18	264.197	-0.0162361	-1.09043
33	263.6	264.651	264.876	-0.225153	-1.05068
34	265.68	265.55	265.657	-0.106653	0.129986
35	266.08	265.877	266.494	-0.616319	0.202569
36	266.28	266.298	267.402	-1.10374	-0.0179306
37	266.28	266.699	268.393	-1.69474	-0.418597
38	269.14	268.649	269.368	-0.719069	0.490736
39	270.96	270.711	270.329	0.381847	0.249403
40	272.97	272.667	271.205	1.4621	0.302903
41	273.13	273.425	271.987	1.43785	-0.295347
42	274.73	273.624	272.755	0.869431	1.10557
43	274.73	273.846	273.515	0.330681	0.884319
44	274.59	274.153	274.169	-0.0162361	0.437486
45	275.15	274.394	274.62	-0.225153	0.755569
46	275.16	274.943	275.05	-0.106653	0.217069
47	275.38	274.935	275.551	-0.616319	0.445069
48	275.4	274.879	275.982	-1.10374	0.521236
49	275.4	274.653	276.348	-1.69474	0.747236
50	275.71	275.996	276.715	-0.719069	-0.285514
51	275.21	277.454	277.072	0.381847	-2.24393
52	279.04	278.881	277.419	1.4621	0.158736
53	279.1	279.197	277.759	1.43785	-0.0970139
54	279.11	278.961	278.091	0.869431	0.149319
55	279.11	278.754	278.424	0.330681	0.355569
56	279.02	278.761	278.777	-0.0162361	0.258736
57	279.3	279.064	279.29	-0.225153	0.235569
58	279.34	279.728	279.835	-0.106653	-0.387931
59	279.36	279.691	280.307	-0.616319	-0.330764
60	279.39	279.668	280.772	-1.10374	-0.277931
61	279.39	279.502	281.197	-1.69474	-0.111931
62	280.21	280.905	281.624	-0.719069	-0.694681
63	283	282.511	282.129	0.381847	0.488986
64	284.33	284.199	282.737	1.4621	0.130819
65	285.15	284.815	283.377	1.43785	0.334653
66	284.21	284.902	284.032	0.869431	-0.691514
67	284.21	NA	NA	0.330681	NA
68	284.17	NA	NA	-0.0162361	NA
69	286.28	NA	NA	-0.225153	NA
70	286.95	NA	NA	-0.106653	NA
71	287.12	NA	NA	-0.616319	NA
72	287.34	NA	NA	-1.10374	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