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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 28 Nov 2014 18:52:33 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/28/t1417200803psuu0oi2twr4lir.htm/, Retrieved Sun, 19 May 2024 15:51:36 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261009, Retrieved Sun, 19 May 2024 15:51:36 +0000

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-       [Classical Decomposition] [] [2014-11-28 18:52:33] [39f63263aa230394eb25f176f7b01700] [Current]

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2,04
2,08
1,94
1,91
1,34
1,3
1,39
1,23
1,3
1,79
2,25
2,63
2,8
3,08
3,89
3,68
4,62
5,07
5,22
4,94
5,14
4,8
3,89
3,54
3,34
2,8
1,6
1,56
0,68
-0,11
-0,66
-0,2
-0,62
-0,59
-0,3
-0,26
-0,08
0,13
0,94
1,05
1,59
2,03
2,15
2,05
2,56
2,54
2,53
2,6
2,71
2,82
2,92
2,87
2,89
3,27
3,32
3,14
3,04
3,09
3,39
3,24
3,38
3,41
3,14
2,96
2,74
2,21
2,24
2,56
2,39
2,49
2,17
2,16
1,48
1,09
1,25
1,27
1,39
1,69
1,55
1,19
1,08
0,94
0,98
1,01

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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261009&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261009&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261009&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.04	NA	NA	4.60177	NA
2	2.08	NA	NA	4.8789	NA
3	1.94	NA	NA	5.66501	NA
4	1.91	NA	NA	5.57827	NA
5	1.34	NA	NA	5.65426	NA
6	1.3	NA	NA	5.33285	NA
7	1.39	6.38953	1.79833	3.55303	0.217543
8	1.23	7.04036	1.87167	3.76155	0.174707
9	1.3	-7.61294	1.99458	-3.81681	-0.170762
10	1.79	-51.0477	2.14958	-23.7477	-0.0350652
11	2.25	-6.95793	2.36	-2.94827	-0.323372
12	2.63	9.25404	2.65375	3.48716	0.2842
13	2.8	13.6692	2.97042	4.60177	0.204841
14	3.08	16.0252	3.28458	4.8789	0.192198
15	3.89	20.3893	3.59917	5.66501	0.190786
16	3.68	21.6693	3.88458	5.57827	0.169826
17	4.62	23.06	4.07833	5.65426	0.200347
18	5.07	22.3158	4.18458	5.33285	0.227194
19	5.22	15.0826	4.245	3.55303	0.346094
20	4.94	16.0085	4.25583	3.76155	0.308586
21	5.14	-15.835	4.14875	-3.81681	-0.324598
22	4.8	-94.1597	3.965	-23.7477	-0.0509772
23	3.89	-10.9455	3.7125	-2.94827	-0.355398
24	3.54	11.6209	3.3325	3.48716	0.304622
25	3.34	13.2147	2.87167	4.60177	0.252748
26	2.8	11.7704	2.4125	4.8789	0.237886
27	1.6	11.094	1.95833	5.66501	0.144222
28	1.56	8.33255	1.49375	5.57827	0.187218
29	0.68	6.18906	1.09458	5.65426	0.109871
30	-0.11	4.06186	0.761667	5.33285	-0.0270812
31	-0.66	1.63735	0.460833	3.55303	-0.403089
32	-0.2	0.778954	0.207083	3.76155	-0.256755
33	-0.62	-0.260815	0.0683333	-3.81681	2.37716
34	-0.59	-0.465059	0.0195833	-23.7477	1.26865
35	-0.3	-0.106875	0.03625	-2.94827	2.80702
36	-0.26	0.569569	0.163333	3.48716	-0.456486
37	-0.08	1.70074	0.369583	4.60177	-0.0470385
38	0.13	2.8318	0.580417	4.8789	0.0459073
39	0.94	4.56977	0.806667	5.66501	0.205699
40	1.05	5.96643	1.06958	5.57827	0.175985
41	1.59	7.45185	1.31792	5.65426	0.21337
42	2.03	8.29259	1.555	5.33285	0.244797
43	2.15	6.3614	1.79042	3.55303	0.337976
44	2.05	7.59362	2.01875	3.76155	0.269963
45	2.56	-8.44786	2.21333	-3.81681	-0.303035
46	2.54	-56.3217	2.37167	-23.7477	-0.0450981
47	2.53	-7.3756	2.50167	-2.94827	-0.343023
48	2.6	9.09276	2.6075	3.48716	0.285942
49	2.71	12.4612	2.70792	4.60177	0.217475
50	2.82	13.6711	2.80208	4.8789	0.206275
51	2.92	16.2444	2.8675	5.66501	0.179754
52	2.87	16.2351	2.91042	5.57827	0.176777
53	2.89	16.7884	2.96917	5.65426	0.172142
54	3.27	16.1674	3.03167	5.33285	0.202258
55	3.32	10.9655	3.08625	3.55303	0.302767
56	3.14	11.8066	3.13875	3.76155	0.265954
57	3.04	-12.1088	3.1725	-3.81681	-0.251057
58	3.09	-75.6464	3.18542	-23.7477	-0.040848
59	3.39	-9.38411	3.18292	-2.94827	-0.361249
60	3.24	10.9235	3.1325	3.48716	0.296608
61	3.38	14.0047	3.04333	4.60177	0.241347
62	3.41	14.5107	2.97417	4.8789	0.235
63	3.14	16.5584	2.92292	5.66501	0.189632
64	2.96	16.0143	2.87083	5.57827	0.184835
65	2.74	15.8037	2.795	5.65426	0.173378
66	2.21	14.3943	2.69917	5.33285	0.153533
67	2.24	9.14905	2.575	3.55303	0.244834
68	2.56	9.02458	2.39917	3.76155	0.28367
69	2.39	-8.48762	2.22375	-3.81681	-0.281587
70	2.49	-49.2666	2.07458	-23.7477	-0.0505413
71	2.17	-5.74299	1.94792	-2.94827	-0.377852
72	2.16	6.52098	1.87	3.48716	0.331239
73	1.48	8.3733	1.81958	4.60177	0.176752
74	1.09	8.4588	1.73375	4.8789	0.12886
75	1.25	9.18912	1.62208	5.66501	0.13603
76	1.27	8.38368	1.50292	5.57827	0.151485
77	1.39	7.85236	1.38875	5.65426	0.177017
78	1.69	6.88605	1.29125	5.33285	0.245424
79	1.55	NA	NA	3.55303	NA
80	1.19	NA	NA	3.76155	NA
81	1.08	NA	NA	-3.81681	NA
82	0.94	NA	NA	-23.7477	NA
83	0.98	NA	NA	-2.94827	NA
84	1.01	NA	NA	3.48716	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.04 & NA & NA & 4.60177 & NA \tabularnewline
2 & 2.08 & NA & NA & 4.8789 & NA \tabularnewline
3 & 1.94 & NA & NA & 5.66501 & NA \tabularnewline
4 & 1.91 & NA & NA & 5.57827 & NA \tabularnewline
5 & 1.34 & NA & NA & 5.65426 & NA \tabularnewline
6 & 1.3 & NA & NA & 5.33285 & NA \tabularnewline
7 & 1.39 & 6.38953 & 1.79833 & 3.55303 & 0.217543 \tabularnewline
8 & 1.23 & 7.04036 & 1.87167 & 3.76155 & 0.174707 \tabularnewline
9 & 1.3 & -7.61294 & 1.99458 & -3.81681 & -0.170762 \tabularnewline
10 & 1.79 & -51.0477 & 2.14958 & -23.7477 & -0.0350652 \tabularnewline
11 & 2.25 & -6.95793 & 2.36 & -2.94827 & -0.323372 \tabularnewline
12 & 2.63 & 9.25404 & 2.65375 & 3.48716 & 0.2842 \tabularnewline
13 & 2.8 & 13.6692 & 2.97042 & 4.60177 & 0.204841 \tabularnewline
14 & 3.08 & 16.0252 & 3.28458 & 4.8789 & 0.192198 \tabularnewline
15 & 3.89 & 20.3893 & 3.59917 & 5.66501 & 0.190786 \tabularnewline
16 & 3.68 & 21.6693 & 3.88458 & 5.57827 & 0.169826 \tabularnewline
17 & 4.62 & 23.06 & 4.07833 & 5.65426 & 0.200347 \tabularnewline
18 & 5.07 & 22.3158 & 4.18458 & 5.33285 & 0.227194 \tabularnewline
19 & 5.22 & 15.0826 & 4.245 & 3.55303 & 0.346094 \tabularnewline
20 & 4.94 & 16.0085 & 4.25583 & 3.76155 & 0.308586 \tabularnewline
21 & 5.14 & -15.835 & 4.14875 & -3.81681 & -0.324598 \tabularnewline
22 & 4.8 & -94.1597 & 3.965 & -23.7477 & -0.0509772 \tabularnewline
23 & 3.89 & -10.9455 & 3.7125 & -2.94827 & -0.355398 \tabularnewline
24 & 3.54 & 11.6209 & 3.3325 & 3.48716 & 0.304622 \tabularnewline
25 & 3.34 & 13.2147 & 2.87167 & 4.60177 & 0.252748 \tabularnewline
26 & 2.8 & 11.7704 & 2.4125 & 4.8789 & 0.237886 \tabularnewline
27 & 1.6 & 11.094 & 1.95833 & 5.66501 & 0.144222 \tabularnewline
28 & 1.56 & 8.33255 & 1.49375 & 5.57827 & 0.187218 \tabularnewline
29 & 0.68 & 6.18906 & 1.09458 & 5.65426 & 0.109871 \tabularnewline
30 & -0.11 & 4.06186 & 0.761667 & 5.33285 & -0.0270812 \tabularnewline
31 & -0.66 & 1.63735 & 0.460833 & 3.55303 & -0.403089 \tabularnewline
32 & -0.2 & 0.778954 & 0.207083 & 3.76155 & -0.256755 \tabularnewline
33 & -0.62 & -0.260815 & 0.0683333 & -3.81681 & 2.37716 \tabularnewline
34 & -0.59 & -0.465059 & 0.0195833 & -23.7477 & 1.26865 \tabularnewline
35 & -0.3 & -0.106875 & 0.03625 & -2.94827 & 2.80702 \tabularnewline
36 & -0.26 & 0.569569 & 0.163333 & 3.48716 & -0.456486 \tabularnewline
37 & -0.08 & 1.70074 & 0.369583 & 4.60177 & -0.0470385 \tabularnewline
38 & 0.13 & 2.8318 & 0.580417 & 4.8789 & 0.0459073 \tabularnewline
39 & 0.94 & 4.56977 & 0.806667 & 5.66501 & 0.205699 \tabularnewline
40 & 1.05 & 5.96643 & 1.06958 & 5.57827 & 0.175985 \tabularnewline
41 & 1.59 & 7.45185 & 1.31792 & 5.65426 & 0.21337 \tabularnewline
42 & 2.03 & 8.29259 & 1.555 & 5.33285 & 0.244797 \tabularnewline
43 & 2.15 & 6.3614 & 1.79042 & 3.55303 & 0.337976 \tabularnewline
44 & 2.05 & 7.59362 & 2.01875 & 3.76155 & 0.269963 \tabularnewline
45 & 2.56 & -8.44786 & 2.21333 & -3.81681 & -0.303035 \tabularnewline
46 & 2.54 & -56.3217 & 2.37167 & -23.7477 & -0.0450981 \tabularnewline
47 & 2.53 & -7.3756 & 2.50167 & -2.94827 & -0.343023 \tabularnewline
48 & 2.6 & 9.09276 & 2.6075 & 3.48716 & 0.285942 \tabularnewline
49 & 2.71 & 12.4612 & 2.70792 & 4.60177 & 0.217475 \tabularnewline
50 & 2.82 & 13.6711 & 2.80208 & 4.8789 & 0.206275 \tabularnewline
51 & 2.92 & 16.2444 & 2.8675 & 5.66501 & 0.179754 \tabularnewline
52 & 2.87 & 16.2351 & 2.91042 & 5.57827 & 0.176777 \tabularnewline
53 & 2.89 & 16.7884 & 2.96917 & 5.65426 & 0.172142 \tabularnewline
54 & 3.27 & 16.1674 & 3.03167 & 5.33285 & 0.202258 \tabularnewline
55 & 3.32 & 10.9655 & 3.08625 & 3.55303 & 0.302767 \tabularnewline
56 & 3.14 & 11.8066 & 3.13875 & 3.76155 & 0.265954 \tabularnewline
57 & 3.04 & -12.1088 & 3.1725 & -3.81681 & -0.251057 \tabularnewline
58 & 3.09 & -75.6464 & 3.18542 & -23.7477 & -0.040848 \tabularnewline
59 & 3.39 & -9.38411 & 3.18292 & -2.94827 & -0.361249 \tabularnewline
60 & 3.24 & 10.9235 & 3.1325 & 3.48716 & 0.296608 \tabularnewline
61 & 3.38 & 14.0047 & 3.04333 & 4.60177 & 0.241347 \tabularnewline
62 & 3.41 & 14.5107 & 2.97417 & 4.8789 & 0.235 \tabularnewline
63 & 3.14 & 16.5584 & 2.92292 & 5.66501 & 0.189632 \tabularnewline
64 & 2.96 & 16.0143 & 2.87083 & 5.57827 & 0.184835 \tabularnewline
65 & 2.74 & 15.8037 & 2.795 & 5.65426 & 0.173378 \tabularnewline
66 & 2.21 & 14.3943 & 2.69917 & 5.33285 & 0.153533 \tabularnewline
67 & 2.24 & 9.14905 & 2.575 & 3.55303 & 0.244834 \tabularnewline
68 & 2.56 & 9.02458 & 2.39917 & 3.76155 & 0.28367 \tabularnewline
69 & 2.39 & -8.48762 & 2.22375 & -3.81681 & -0.281587 \tabularnewline
70 & 2.49 & -49.2666 & 2.07458 & -23.7477 & -0.0505413 \tabularnewline
71 & 2.17 & -5.74299 & 1.94792 & -2.94827 & -0.377852 \tabularnewline
72 & 2.16 & 6.52098 & 1.87 & 3.48716 & 0.331239 \tabularnewline
73 & 1.48 & 8.3733 & 1.81958 & 4.60177 & 0.176752 \tabularnewline
74 & 1.09 & 8.4588 & 1.73375 & 4.8789 & 0.12886 \tabularnewline
75 & 1.25 & 9.18912 & 1.62208 & 5.66501 & 0.13603 \tabularnewline
76 & 1.27 & 8.38368 & 1.50292 & 5.57827 & 0.151485 \tabularnewline
77 & 1.39 & 7.85236 & 1.38875 & 5.65426 & 0.177017 \tabularnewline
78 & 1.69 & 6.88605 & 1.29125 & 5.33285 & 0.245424 \tabularnewline
79 & 1.55 & NA & NA & 3.55303 & NA \tabularnewline
80 & 1.19 & NA & NA & 3.76155 & NA \tabularnewline
81 & 1.08 & NA & NA & -3.81681 & NA \tabularnewline
82 & 0.94 & NA & NA & -23.7477 & NA \tabularnewline
83 & 0.98 & NA & NA & -2.94827 & NA \tabularnewline
84 & 1.01 & NA & NA & 3.48716 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261009&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]2.04[/C][C]NA[/C][C]NA[/C][C]4.60177[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.08[/C][C]NA[/C][C]NA[/C][C]4.8789[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.94[/C][C]NA[/C][C]NA[/C][C]5.66501[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.91[/C][C]NA[/C][C]NA[/C][C]5.57827[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.34[/C][C]NA[/C][C]NA[/C][C]5.65426[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.3[/C][C]NA[/C][C]NA[/C][C]5.33285[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.39[/C][C]6.38953[/C][C]1.79833[/C][C]3.55303[/C][C]0.217543[/C][/ROW]
[ROW][C]8[/C][C]1.23[/C][C]7.04036[/C][C]1.87167[/C][C]3.76155[/C][C]0.174707[/C][/ROW]
[ROW][C]9[/C][C]1.3[/C][C]-7.61294[/C][C]1.99458[/C][C]-3.81681[/C][C]-0.170762[/C][/ROW]
[ROW][C]10[/C][C]1.79[/C][C]-51.0477[/C][C]2.14958[/C][C]-23.7477[/C][C]-0.0350652[/C][/ROW]
[ROW][C]11[/C][C]2.25[/C][C]-6.95793[/C][C]2.36[/C][C]-2.94827[/C][C]-0.323372[/C][/ROW]
[ROW][C]12[/C][C]2.63[/C][C]9.25404[/C][C]2.65375[/C][C]3.48716[/C][C]0.2842[/C][/ROW]
[ROW][C]13[/C][C]2.8[/C][C]13.6692[/C][C]2.97042[/C][C]4.60177[/C][C]0.204841[/C][/ROW]
[ROW][C]14[/C][C]3.08[/C][C]16.0252[/C][C]3.28458[/C][C]4.8789[/C][C]0.192198[/C][/ROW]
[ROW][C]15[/C][C]3.89[/C][C]20.3893[/C][C]3.59917[/C][C]5.66501[/C][C]0.190786[/C][/ROW]
[ROW][C]16[/C][C]3.68[/C][C]21.6693[/C][C]3.88458[/C][C]5.57827[/C][C]0.169826[/C][/ROW]
[ROW][C]17[/C][C]4.62[/C][C]23.06[/C][C]4.07833[/C][C]5.65426[/C][C]0.200347[/C][/ROW]
[ROW][C]18[/C][C]5.07[/C][C]22.3158[/C][C]4.18458[/C][C]5.33285[/C][C]0.227194[/C][/ROW]
[ROW][C]19[/C][C]5.22[/C][C]15.0826[/C][C]4.245[/C][C]3.55303[/C][C]0.346094[/C][/ROW]
[ROW][C]20[/C][C]4.94[/C][C]16.0085[/C][C]4.25583[/C][C]3.76155[/C][C]0.308586[/C][/ROW]
[ROW][C]21[/C][C]5.14[/C][C]-15.835[/C][C]4.14875[/C][C]-3.81681[/C][C]-0.324598[/C][/ROW]
[ROW][C]22[/C][C]4.8[/C][C]-94.1597[/C][C]3.965[/C][C]-23.7477[/C][C]-0.0509772[/C][/ROW]
[ROW][C]23[/C][C]3.89[/C][C]-10.9455[/C][C]3.7125[/C][C]-2.94827[/C][C]-0.355398[/C][/ROW]
[ROW][C]24[/C][C]3.54[/C][C]11.6209[/C][C]3.3325[/C][C]3.48716[/C][C]0.304622[/C][/ROW]
[ROW][C]25[/C][C]3.34[/C][C]13.2147[/C][C]2.87167[/C][C]4.60177[/C][C]0.252748[/C][/ROW]
[ROW][C]26[/C][C]2.8[/C][C]11.7704[/C][C]2.4125[/C][C]4.8789[/C][C]0.237886[/C][/ROW]
[ROW][C]27[/C][C]1.6[/C][C]11.094[/C][C]1.95833[/C][C]5.66501[/C][C]0.144222[/C][/ROW]
[ROW][C]28[/C][C]1.56[/C][C]8.33255[/C][C]1.49375[/C][C]5.57827[/C][C]0.187218[/C][/ROW]
[ROW][C]29[/C][C]0.68[/C][C]6.18906[/C][C]1.09458[/C][C]5.65426[/C][C]0.109871[/C][/ROW]
[ROW][C]30[/C][C]-0.11[/C][C]4.06186[/C][C]0.761667[/C][C]5.33285[/C][C]-0.0270812[/C][/ROW]
[ROW][C]31[/C][C]-0.66[/C][C]1.63735[/C][C]0.460833[/C][C]3.55303[/C][C]-0.403089[/C][/ROW]
[ROW][C]32[/C][C]-0.2[/C][C]0.778954[/C][C]0.207083[/C][C]3.76155[/C][C]-0.256755[/C][/ROW]
[ROW][C]33[/C][C]-0.62[/C][C]-0.260815[/C][C]0.0683333[/C][C]-3.81681[/C][C]2.37716[/C][/ROW]
[ROW][C]34[/C][C]-0.59[/C][C]-0.465059[/C][C]0.0195833[/C][C]-23.7477[/C][C]1.26865[/C][/ROW]
[ROW][C]35[/C][C]-0.3[/C][C]-0.106875[/C][C]0.03625[/C][C]-2.94827[/C][C]2.80702[/C][/ROW]
[ROW][C]36[/C][C]-0.26[/C][C]0.569569[/C][C]0.163333[/C][C]3.48716[/C][C]-0.456486[/C][/ROW]
[ROW][C]37[/C][C]-0.08[/C][C]1.70074[/C][C]0.369583[/C][C]4.60177[/C][C]-0.0470385[/C][/ROW]
[ROW][C]38[/C][C]0.13[/C][C]2.8318[/C][C]0.580417[/C][C]4.8789[/C][C]0.0459073[/C][/ROW]
[ROW][C]39[/C][C]0.94[/C][C]4.56977[/C][C]0.806667[/C][C]5.66501[/C][C]0.205699[/C][/ROW]
[ROW][C]40[/C][C]1.05[/C][C]5.96643[/C][C]1.06958[/C][C]5.57827[/C][C]0.175985[/C][/ROW]
[ROW][C]41[/C][C]1.59[/C][C]7.45185[/C][C]1.31792[/C][C]5.65426[/C][C]0.21337[/C][/ROW]
[ROW][C]42[/C][C]2.03[/C][C]8.29259[/C][C]1.555[/C][C]5.33285[/C][C]0.244797[/C][/ROW]
[ROW][C]43[/C][C]2.15[/C][C]6.3614[/C][C]1.79042[/C][C]3.55303[/C][C]0.337976[/C][/ROW]
[ROW][C]44[/C][C]2.05[/C][C]7.59362[/C][C]2.01875[/C][C]3.76155[/C][C]0.269963[/C][/ROW]
[ROW][C]45[/C][C]2.56[/C][C]-8.44786[/C][C]2.21333[/C][C]-3.81681[/C][C]-0.303035[/C][/ROW]
[ROW][C]46[/C][C]2.54[/C][C]-56.3217[/C][C]2.37167[/C][C]-23.7477[/C][C]-0.0450981[/C][/ROW]
[ROW][C]47[/C][C]2.53[/C][C]-7.3756[/C][C]2.50167[/C][C]-2.94827[/C][C]-0.343023[/C][/ROW]
[ROW][C]48[/C][C]2.6[/C][C]9.09276[/C][C]2.6075[/C][C]3.48716[/C][C]0.285942[/C][/ROW]
[ROW][C]49[/C][C]2.71[/C][C]12.4612[/C][C]2.70792[/C][C]4.60177[/C][C]0.217475[/C][/ROW]
[ROW][C]50[/C][C]2.82[/C][C]13.6711[/C][C]2.80208[/C][C]4.8789[/C][C]0.206275[/C][/ROW]
[ROW][C]51[/C][C]2.92[/C][C]16.2444[/C][C]2.8675[/C][C]5.66501[/C][C]0.179754[/C][/ROW]
[ROW][C]52[/C][C]2.87[/C][C]16.2351[/C][C]2.91042[/C][C]5.57827[/C][C]0.176777[/C][/ROW]
[ROW][C]53[/C][C]2.89[/C][C]16.7884[/C][C]2.96917[/C][C]5.65426[/C][C]0.172142[/C][/ROW]
[ROW][C]54[/C][C]3.27[/C][C]16.1674[/C][C]3.03167[/C][C]5.33285[/C][C]0.202258[/C][/ROW]
[ROW][C]55[/C][C]3.32[/C][C]10.9655[/C][C]3.08625[/C][C]3.55303[/C][C]0.302767[/C][/ROW]
[ROW][C]56[/C][C]3.14[/C][C]11.8066[/C][C]3.13875[/C][C]3.76155[/C][C]0.265954[/C][/ROW]
[ROW][C]57[/C][C]3.04[/C][C]-12.1088[/C][C]3.1725[/C][C]-3.81681[/C][C]-0.251057[/C][/ROW]
[ROW][C]58[/C][C]3.09[/C][C]-75.6464[/C][C]3.18542[/C][C]-23.7477[/C][C]-0.040848[/C][/ROW]
[ROW][C]59[/C][C]3.39[/C][C]-9.38411[/C][C]3.18292[/C][C]-2.94827[/C][C]-0.361249[/C][/ROW]
[ROW][C]60[/C][C]3.24[/C][C]10.9235[/C][C]3.1325[/C][C]3.48716[/C][C]0.296608[/C][/ROW]
[ROW][C]61[/C][C]3.38[/C][C]14.0047[/C][C]3.04333[/C][C]4.60177[/C][C]0.241347[/C][/ROW]
[ROW][C]62[/C][C]3.41[/C][C]14.5107[/C][C]2.97417[/C][C]4.8789[/C][C]0.235[/C][/ROW]
[ROW][C]63[/C][C]3.14[/C][C]16.5584[/C][C]2.92292[/C][C]5.66501[/C][C]0.189632[/C][/ROW]
[ROW][C]64[/C][C]2.96[/C][C]16.0143[/C][C]2.87083[/C][C]5.57827[/C][C]0.184835[/C][/ROW]
[ROW][C]65[/C][C]2.74[/C][C]15.8037[/C][C]2.795[/C][C]5.65426[/C][C]0.173378[/C][/ROW]
[ROW][C]66[/C][C]2.21[/C][C]14.3943[/C][C]2.69917[/C][C]5.33285[/C][C]0.153533[/C][/ROW]
[ROW][C]67[/C][C]2.24[/C][C]9.14905[/C][C]2.575[/C][C]3.55303[/C][C]0.244834[/C][/ROW]
[ROW][C]68[/C][C]2.56[/C][C]9.02458[/C][C]2.39917[/C][C]3.76155[/C][C]0.28367[/C][/ROW]
[ROW][C]69[/C][C]2.39[/C][C]-8.48762[/C][C]2.22375[/C][C]-3.81681[/C][C]-0.281587[/C][/ROW]
[ROW][C]70[/C][C]2.49[/C][C]-49.2666[/C][C]2.07458[/C][C]-23.7477[/C][C]-0.0505413[/C][/ROW]
[ROW][C]71[/C][C]2.17[/C][C]-5.74299[/C][C]1.94792[/C][C]-2.94827[/C][C]-0.377852[/C][/ROW]
[ROW][C]72[/C][C]2.16[/C][C]6.52098[/C][C]1.87[/C][C]3.48716[/C][C]0.331239[/C][/ROW]
[ROW][C]73[/C][C]1.48[/C][C]8.3733[/C][C]1.81958[/C][C]4.60177[/C][C]0.176752[/C][/ROW]
[ROW][C]74[/C][C]1.09[/C][C]8.4588[/C][C]1.73375[/C][C]4.8789[/C][C]0.12886[/C][/ROW]
[ROW][C]75[/C][C]1.25[/C][C]9.18912[/C][C]1.62208[/C][C]5.66501[/C][C]0.13603[/C][/ROW]
[ROW][C]76[/C][C]1.27[/C][C]8.38368[/C][C]1.50292[/C][C]5.57827[/C][C]0.151485[/C][/ROW]
[ROW][C]77[/C][C]1.39[/C][C]7.85236[/C][C]1.38875[/C][C]5.65426[/C][C]0.177017[/C][/ROW]
[ROW][C]78[/C][C]1.69[/C][C]6.88605[/C][C]1.29125[/C][C]5.33285[/C][C]0.245424[/C][/ROW]
[ROW][C]79[/C][C]1.55[/C][C]NA[/C][C]NA[/C][C]3.55303[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.19[/C][C]NA[/C][C]NA[/C][C]3.76155[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.08[/C][C]NA[/C][C]NA[/C][C]-3.81681[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]0.94[/C][C]NA[/C][C]NA[/C][C]-23.7477[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]0.98[/C][C]NA[/C][C]NA[/C][C]-2.94827[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.01[/C][C]NA[/C][C]NA[/C][C]3.48716[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261009&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261009&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	2.04	NA	NA	4.60177	NA
2	2.08	NA	NA	4.8789	NA
3	1.94	NA	NA	5.66501	NA
4	1.91	NA	NA	5.57827	NA
5	1.34	NA	NA	5.65426	NA
6	1.3	NA	NA	5.33285	NA
7	1.39	6.38953	1.79833	3.55303	0.217543
8	1.23	7.04036	1.87167	3.76155	0.174707
9	1.3	-7.61294	1.99458	-3.81681	-0.170762
10	1.79	-51.0477	2.14958	-23.7477	-0.0350652
11	2.25	-6.95793	2.36	-2.94827	-0.323372
12	2.63	9.25404	2.65375	3.48716	0.2842
13	2.8	13.6692	2.97042	4.60177	0.204841
14	3.08	16.0252	3.28458	4.8789	0.192198
15	3.89	20.3893	3.59917	5.66501	0.190786
16	3.68	21.6693	3.88458	5.57827	0.169826
17	4.62	23.06	4.07833	5.65426	0.200347
18	5.07	22.3158	4.18458	5.33285	0.227194
19	5.22	15.0826	4.245	3.55303	0.346094
20	4.94	16.0085	4.25583	3.76155	0.308586
21	5.14	-15.835	4.14875	-3.81681	-0.324598
22	4.8	-94.1597	3.965	-23.7477	-0.0509772
23	3.89	-10.9455	3.7125	-2.94827	-0.355398
24	3.54	11.6209	3.3325	3.48716	0.304622
25	3.34	13.2147	2.87167	4.60177	0.252748
26	2.8	11.7704	2.4125	4.8789	0.237886
27	1.6	11.094	1.95833	5.66501	0.144222
28	1.56	8.33255	1.49375	5.57827	0.187218
29	0.68	6.18906	1.09458	5.65426	0.109871
30	-0.11	4.06186	0.761667	5.33285	-0.0270812
31	-0.66	1.63735	0.460833	3.55303	-0.403089
32	-0.2	0.778954	0.207083	3.76155	-0.256755
33	-0.62	-0.260815	0.0683333	-3.81681	2.37716
34	-0.59	-0.465059	0.0195833	-23.7477	1.26865
35	-0.3	-0.106875	0.03625	-2.94827	2.80702
36	-0.26	0.569569	0.163333	3.48716	-0.456486
37	-0.08	1.70074	0.369583	4.60177	-0.0470385
38	0.13	2.8318	0.580417	4.8789	0.0459073
39	0.94	4.56977	0.806667	5.66501	0.205699
40	1.05	5.96643	1.06958	5.57827	0.175985
41	1.59	7.45185	1.31792	5.65426	0.21337
42	2.03	8.29259	1.555	5.33285	0.244797
43	2.15	6.3614	1.79042	3.55303	0.337976
44	2.05	7.59362	2.01875	3.76155	0.269963
45	2.56	-8.44786	2.21333	-3.81681	-0.303035
46	2.54	-56.3217	2.37167	-23.7477	-0.0450981
47	2.53	-7.3756	2.50167	-2.94827	-0.343023
48	2.6	9.09276	2.6075	3.48716	0.285942
49	2.71	12.4612	2.70792	4.60177	0.217475
50	2.82	13.6711	2.80208	4.8789	0.206275
51	2.92	16.2444	2.8675	5.66501	0.179754
52	2.87	16.2351	2.91042	5.57827	0.176777
53	2.89	16.7884	2.96917	5.65426	0.172142
54	3.27	16.1674	3.03167	5.33285	0.202258
55	3.32	10.9655	3.08625	3.55303	0.302767
56	3.14	11.8066	3.13875	3.76155	0.265954
57	3.04	-12.1088	3.1725	-3.81681	-0.251057
58	3.09	-75.6464	3.18542	-23.7477	-0.040848
59	3.39	-9.38411	3.18292	-2.94827	-0.361249
60	3.24	10.9235	3.1325	3.48716	0.296608
61	3.38	14.0047	3.04333	4.60177	0.241347
62	3.41	14.5107	2.97417	4.8789	0.235
63	3.14	16.5584	2.92292	5.66501	0.189632
64	2.96	16.0143	2.87083	5.57827	0.184835
65	2.74	15.8037	2.795	5.65426	0.173378
66	2.21	14.3943	2.69917	5.33285	0.153533
67	2.24	9.14905	2.575	3.55303	0.244834
68	2.56	9.02458	2.39917	3.76155	0.28367
69	2.39	-8.48762	2.22375	-3.81681	-0.281587
70	2.49	-49.2666	2.07458	-23.7477	-0.0505413
71	2.17	-5.74299	1.94792	-2.94827	-0.377852
72	2.16	6.52098	1.87	3.48716	0.331239
73	1.48	8.3733	1.81958	4.60177	0.176752
74	1.09	8.4588	1.73375	4.8789	0.12886
75	1.25	9.18912	1.62208	5.66501	0.13603
76	1.27	8.38368	1.50292	5.57827	0.151485
77	1.39	7.85236	1.38875	5.65426	0.177017
78	1.69	6.88605	1.29125	5.33285	0.245424
79	1.55	NA	NA	3.55303	NA
80	1.19	NA	NA	3.76155	NA
81	1.08	NA	NA	-3.81681	NA
82	0.94	NA	NA	-23.7477	NA
83	0.98	NA	NA	-2.94827	NA
84	1.01	NA	NA	3.48716	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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