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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 21 Apr 2016 12:27:46 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Apr/21/t1461238114v334raksweypgvl.htm/, Retrieved Sat, 25 Apr 2026 22:50:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294567, Retrieved Sat, 25 Apr 2026 22:50:05 +0000

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Estimated Impact

419

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-       [Classical Decomposition] [] [2016-04-21 11:27:46] [62731d77c8be8d15fdc4807de050d219] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294567&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294567&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294567&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' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	91.16	NA	NA	-0.701215	NA
2	91.17	NA	NA	-0.625799	NA
3	91.17	NA	NA	-0.130382	NA
4	91.38	NA	NA	0.0858681	NA
5	92.68	NA	NA	0.440618	NA
6	92.72	NA	NA	0.472535	NA
7	92.79	92.6304	92.3287	0.301618	0.159632
8	92.81	92.7077	92.4662	0.241451	0.102299
9	92.81	92.9027	92.6037	0.298951	-0.0927014
10	92.81	92.8439	92.735	0.108868	-0.0338681
11	92.81	92.726	92.8267	-0.100632	0.0839653
12	92.81	92.5127	92.9046	-0.391882	0.297299
13	92.81	92.3067	93.0079	-0.701215	0.503299
14	92.82	92.4938	93.1196	-0.625799	0.326215
15	92.82	93.1084	93.2387	-0.130382	-0.288368
16	92.88	93.4492	93.3633	0.0858681	-0.569201
17	93.38	93.931	93.4904	0.440618	-0.551035
18	93.89	94.093	93.6204	0.472535	-0.202951
19	94.1	94.0529	93.7512	0.301618	0.0471319
20	94.18	94.1281	93.8867	0.241451	0.0518819
21	94.3	94.3285	94.0296	0.298951	-0.0285347
22	94.31	94.2951	94.1862	0.108868	0.0148819
23	94.36	94.3081	94.4088	-0.100632	0.0518819
24	94.38	94.309	94.7008	-0.391882	0.0710486
25	94.38	94.3105	95.0117	-0.701215	0.0695486
26	94.5	94.7013	95.3271	-0.625799	-0.201285
27	94.57	95.5255	95.6558	-0.130382	-0.955451
28	94.89	96.0875	96.0017	0.0858681	-1.19753
29	96.71	96.7881	96.3475	0.440618	-0.0781181
30	97.57	97.1609	96.6883	0.472535	0.409132
31	97.88	97.3308	97.0292	0.301618	0.549215
32	97.97	97.6123	97.3708	0.241451	0.357715
33	98.4	98.0085	97.7096	0.298951	0.391465
34	98.51	98.1455	98.0367	0.108868	0.364465
35	98.46	98.196	98.2967	-0.100632	0.263965
36	98.46	98.0735	98.4654	-0.391882	0.386465
37	98.48	97.8913	98.5925	-0.701215	0.588715
38	98.6	98.118	98.7437	-0.625799	0.482049
39	98.6	98.8292	98.9596	-0.130382	-0.229201
40	98.71	99.305	99.2192	0.0858681	-0.595035
41	99.13	99.9548	99.5142	0.440618	-0.824785
42	99.2	100.309	99.8367	0.472535	-1.1092
43	99.3	100.463	100.161	0.301618	-1.16287
44	100.18	100.757	100.515	0.241451	-0.576868
45	101.37	101.289	100.99	0.298951	0.0806319
46	101.77	101.711	101.602	0.108868	0.0590486
47	102.28	102.159	102.26	-0.100632	0.121049
48	102.38	102.531	102.922	-0.391882	-0.150618
49	102.35	102.89	103.591	-0.701215	-0.540035
50	103.23	103.598	104.224	-0.625799	-0.367951
51	105.37	104.644	104.775	-0.130382	0.725799
52	106.62	105.355	105.269	0.0858681	1.26538
53	107	106.175	105.734	0.440618	0.825215
54	107.24	106.649	106.177	0.472535	0.590799
55	107.31	106.92	106.618	0.301618	0.390465
56	107.35	107.301	107.06	0.241451	0.0485486
57	107.42	107.787	107.488	0.298951	-0.367285
58	107.58	108.001	107.892	0.108868	-0.420951
59	107.64	108.177	108.278	-0.100632	-0.537285
60	107.64	108.261	108.652	-0.391882	-0.620618
61	107.68	108.318	109.019	-0.701215	-0.637951
62	108.51	108.765	109.391	-0.625799	-0.255451
63	110.37	109.639	109.77	-0.130382	0.730799
64	111.31	110.23	110.144	0.0858681	1.07997
65	111.57	110.958	110.517	0.440618	0.612299
66	111.66	111.364	110.892	0.472535	0.295799
67	111.69	NA	NA	0.301618	NA
68	111.9	NA	NA	0.241451	NA
69	111.95	NA	NA	0.298951	NA
70	112.04	NA	NA	0.108868	NA
71	112.13	NA	NA	-0.100632	NA
72	112.14	NA	NA	-0.391882	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 91.16 & NA & NA & -0.701215 & NA \tabularnewline
2 & 91.17 & NA & NA & -0.625799 & NA \tabularnewline
3 & 91.17 & NA & NA & -0.130382 & NA \tabularnewline
4 & 91.38 & NA & NA & 0.0858681 & NA \tabularnewline
5 & 92.68 & NA & NA & 0.440618 & NA \tabularnewline
6 & 92.72 & NA & NA & 0.472535 & NA \tabularnewline
7 & 92.79 & 92.6304 & 92.3287 & 0.301618 & 0.159632 \tabularnewline
8 & 92.81 & 92.7077 & 92.4662 & 0.241451 & 0.102299 \tabularnewline
9 & 92.81 & 92.9027 & 92.6037 & 0.298951 & -0.0927014 \tabularnewline
10 & 92.81 & 92.8439 & 92.735 & 0.108868 & -0.0338681 \tabularnewline
11 & 92.81 & 92.726 & 92.8267 & -0.100632 & 0.0839653 \tabularnewline
12 & 92.81 & 92.5127 & 92.9046 & -0.391882 & 0.297299 \tabularnewline
13 & 92.81 & 92.3067 & 93.0079 & -0.701215 & 0.503299 \tabularnewline
14 & 92.82 & 92.4938 & 93.1196 & -0.625799 & 0.326215 \tabularnewline
15 & 92.82 & 93.1084 & 93.2387 & -0.130382 & -0.288368 \tabularnewline
16 & 92.88 & 93.4492 & 93.3633 & 0.0858681 & -0.569201 \tabularnewline
17 & 93.38 & 93.931 & 93.4904 & 0.440618 & -0.551035 \tabularnewline
18 & 93.89 & 94.093 & 93.6204 & 0.472535 & -0.202951 \tabularnewline
19 & 94.1 & 94.0529 & 93.7512 & 0.301618 & 0.0471319 \tabularnewline
20 & 94.18 & 94.1281 & 93.8867 & 0.241451 & 0.0518819 \tabularnewline
21 & 94.3 & 94.3285 & 94.0296 & 0.298951 & -0.0285347 \tabularnewline
22 & 94.31 & 94.2951 & 94.1862 & 0.108868 & 0.0148819 \tabularnewline
23 & 94.36 & 94.3081 & 94.4088 & -0.100632 & 0.0518819 \tabularnewline
24 & 94.38 & 94.309 & 94.7008 & -0.391882 & 0.0710486 \tabularnewline
25 & 94.38 & 94.3105 & 95.0117 & -0.701215 & 0.0695486 \tabularnewline
26 & 94.5 & 94.7013 & 95.3271 & -0.625799 & -0.201285 \tabularnewline
27 & 94.57 & 95.5255 & 95.6558 & -0.130382 & -0.955451 \tabularnewline
28 & 94.89 & 96.0875 & 96.0017 & 0.0858681 & -1.19753 \tabularnewline
29 & 96.71 & 96.7881 & 96.3475 & 0.440618 & -0.0781181 \tabularnewline
30 & 97.57 & 97.1609 & 96.6883 & 0.472535 & 0.409132 \tabularnewline
31 & 97.88 & 97.3308 & 97.0292 & 0.301618 & 0.549215 \tabularnewline
32 & 97.97 & 97.6123 & 97.3708 & 0.241451 & 0.357715 \tabularnewline
33 & 98.4 & 98.0085 & 97.7096 & 0.298951 & 0.391465 \tabularnewline
34 & 98.51 & 98.1455 & 98.0367 & 0.108868 & 0.364465 \tabularnewline
35 & 98.46 & 98.196 & 98.2967 & -0.100632 & 0.263965 \tabularnewline
36 & 98.46 & 98.0735 & 98.4654 & -0.391882 & 0.386465 \tabularnewline
37 & 98.48 & 97.8913 & 98.5925 & -0.701215 & 0.588715 \tabularnewline
38 & 98.6 & 98.118 & 98.7437 & -0.625799 & 0.482049 \tabularnewline
39 & 98.6 & 98.8292 & 98.9596 & -0.130382 & -0.229201 \tabularnewline
40 & 98.71 & 99.305 & 99.2192 & 0.0858681 & -0.595035 \tabularnewline
41 & 99.13 & 99.9548 & 99.5142 & 0.440618 & -0.824785 \tabularnewline
42 & 99.2 & 100.309 & 99.8367 & 0.472535 & -1.1092 \tabularnewline
43 & 99.3 & 100.463 & 100.161 & 0.301618 & -1.16287 \tabularnewline
44 & 100.18 & 100.757 & 100.515 & 0.241451 & -0.576868 \tabularnewline
45 & 101.37 & 101.289 & 100.99 & 0.298951 & 0.0806319 \tabularnewline
46 & 101.77 & 101.711 & 101.602 & 0.108868 & 0.0590486 \tabularnewline
47 & 102.28 & 102.159 & 102.26 & -0.100632 & 0.121049 \tabularnewline
48 & 102.38 & 102.531 & 102.922 & -0.391882 & -0.150618 \tabularnewline
49 & 102.35 & 102.89 & 103.591 & -0.701215 & -0.540035 \tabularnewline
50 & 103.23 & 103.598 & 104.224 & -0.625799 & -0.367951 \tabularnewline
51 & 105.37 & 104.644 & 104.775 & -0.130382 & 0.725799 \tabularnewline
52 & 106.62 & 105.355 & 105.269 & 0.0858681 & 1.26538 \tabularnewline
53 & 107 & 106.175 & 105.734 & 0.440618 & 0.825215 \tabularnewline
54 & 107.24 & 106.649 & 106.177 & 0.472535 & 0.590799 \tabularnewline
55 & 107.31 & 106.92 & 106.618 & 0.301618 & 0.390465 \tabularnewline
56 & 107.35 & 107.301 & 107.06 & 0.241451 & 0.0485486 \tabularnewline
57 & 107.42 & 107.787 & 107.488 & 0.298951 & -0.367285 \tabularnewline
58 & 107.58 & 108.001 & 107.892 & 0.108868 & -0.420951 \tabularnewline
59 & 107.64 & 108.177 & 108.278 & -0.100632 & -0.537285 \tabularnewline
60 & 107.64 & 108.261 & 108.652 & -0.391882 & -0.620618 \tabularnewline
61 & 107.68 & 108.318 & 109.019 & -0.701215 & -0.637951 \tabularnewline
62 & 108.51 & 108.765 & 109.391 & -0.625799 & -0.255451 \tabularnewline
63 & 110.37 & 109.639 & 109.77 & -0.130382 & 0.730799 \tabularnewline
64 & 111.31 & 110.23 & 110.144 & 0.0858681 & 1.07997 \tabularnewline
65 & 111.57 & 110.958 & 110.517 & 0.440618 & 0.612299 \tabularnewline
66 & 111.66 & 111.364 & 110.892 & 0.472535 & 0.295799 \tabularnewline
67 & 111.69 & NA & NA & 0.301618 & NA \tabularnewline
68 & 111.9 & NA & NA & 0.241451 & NA \tabularnewline
69 & 111.95 & NA & NA & 0.298951 & NA \tabularnewline
70 & 112.04 & NA & NA & 0.108868 & NA \tabularnewline
71 & 112.13 & NA & NA & -0.100632 & NA \tabularnewline
72 & 112.14 & NA & NA & -0.391882 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294567&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]91.16[/C][C]NA[/C][C]NA[/C][C]-0.701215[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]91.17[/C][C]NA[/C][C]NA[/C][C]-0.625799[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]91.17[/C][C]NA[/C][C]NA[/C][C]-0.130382[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]91.38[/C][C]NA[/C][C]NA[/C][C]0.0858681[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.68[/C][C]NA[/C][C]NA[/C][C]0.440618[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.72[/C][C]NA[/C][C]NA[/C][C]0.472535[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]92.79[/C][C]92.6304[/C][C]92.3287[/C][C]0.301618[/C][C]0.159632[/C][/ROW]
[ROW][C]8[/C][C]92.81[/C][C]92.7077[/C][C]92.4662[/C][C]0.241451[/C][C]0.102299[/C][/ROW]
[ROW][C]9[/C][C]92.81[/C][C]92.9027[/C][C]92.6037[/C][C]0.298951[/C][C]-0.0927014[/C][/ROW]
[ROW][C]10[/C][C]92.81[/C][C]92.8439[/C][C]92.735[/C][C]0.108868[/C][C]-0.0338681[/C][/ROW]
[ROW][C]11[/C][C]92.81[/C][C]92.726[/C][C]92.8267[/C][C]-0.100632[/C][C]0.0839653[/C][/ROW]
[ROW][C]12[/C][C]92.81[/C][C]92.5127[/C][C]92.9046[/C][C]-0.391882[/C][C]0.297299[/C][/ROW]
[ROW][C]13[/C][C]92.81[/C][C]92.3067[/C][C]93.0079[/C][C]-0.701215[/C][C]0.503299[/C][/ROW]
[ROW][C]14[/C][C]92.82[/C][C]92.4938[/C][C]93.1196[/C][C]-0.625799[/C][C]0.326215[/C][/ROW]
[ROW][C]15[/C][C]92.82[/C][C]93.1084[/C][C]93.2387[/C][C]-0.130382[/C][C]-0.288368[/C][/ROW]
[ROW][C]16[/C][C]92.88[/C][C]93.4492[/C][C]93.3633[/C][C]0.0858681[/C][C]-0.569201[/C][/ROW]
[ROW][C]17[/C][C]93.38[/C][C]93.931[/C][C]93.4904[/C][C]0.440618[/C][C]-0.551035[/C][/ROW]
[ROW][C]18[/C][C]93.89[/C][C]94.093[/C][C]93.6204[/C][C]0.472535[/C][C]-0.202951[/C][/ROW]
[ROW][C]19[/C][C]94.1[/C][C]94.0529[/C][C]93.7512[/C][C]0.301618[/C][C]0.0471319[/C][/ROW]
[ROW][C]20[/C][C]94.18[/C][C]94.1281[/C][C]93.8867[/C][C]0.241451[/C][C]0.0518819[/C][/ROW]
[ROW][C]21[/C][C]94.3[/C][C]94.3285[/C][C]94.0296[/C][C]0.298951[/C][C]-0.0285347[/C][/ROW]
[ROW][C]22[/C][C]94.31[/C][C]94.2951[/C][C]94.1862[/C][C]0.108868[/C][C]0.0148819[/C][/ROW]
[ROW][C]23[/C][C]94.36[/C][C]94.3081[/C][C]94.4088[/C][C]-0.100632[/C][C]0.0518819[/C][/ROW]
[ROW][C]24[/C][C]94.38[/C][C]94.309[/C][C]94.7008[/C][C]-0.391882[/C][C]0.0710486[/C][/ROW]
[ROW][C]25[/C][C]94.38[/C][C]94.3105[/C][C]95.0117[/C][C]-0.701215[/C][C]0.0695486[/C][/ROW]
[ROW][C]26[/C][C]94.5[/C][C]94.7013[/C][C]95.3271[/C][C]-0.625799[/C][C]-0.201285[/C][/ROW]
[ROW][C]27[/C][C]94.57[/C][C]95.5255[/C][C]95.6558[/C][C]-0.130382[/C][C]-0.955451[/C][/ROW]
[ROW][C]28[/C][C]94.89[/C][C]96.0875[/C][C]96.0017[/C][C]0.0858681[/C][C]-1.19753[/C][/ROW]
[ROW][C]29[/C][C]96.71[/C][C]96.7881[/C][C]96.3475[/C][C]0.440618[/C][C]-0.0781181[/C][/ROW]
[ROW][C]30[/C][C]97.57[/C][C]97.1609[/C][C]96.6883[/C][C]0.472535[/C][C]0.409132[/C][/ROW]
[ROW][C]31[/C][C]97.88[/C][C]97.3308[/C][C]97.0292[/C][C]0.301618[/C][C]0.549215[/C][/ROW]
[ROW][C]32[/C][C]97.97[/C][C]97.6123[/C][C]97.3708[/C][C]0.241451[/C][C]0.357715[/C][/ROW]
[ROW][C]33[/C][C]98.4[/C][C]98.0085[/C][C]97.7096[/C][C]0.298951[/C][C]0.391465[/C][/ROW]
[ROW][C]34[/C][C]98.51[/C][C]98.1455[/C][C]98.0367[/C][C]0.108868[/C][C]0.364465[/C][/ROW]
[ROW][C]35[/C][C]98.46[/C][C]98.196[/C][C]98.2967[/C][C]-0.100632[/C][C]0.263965[/C][/ROW]
[ROW][C]36[/C][C]98.46[/C][C]98.0735[/C][C]98.4654[/C][C]-0.391882[/C][C]0.386465[/C][/ROW]
[ROW][C]37[/C][C]98.48[/C][C]97.8913[/C][C]98.5925[/C][C]-0.701215[/C][C]0.588715[/C][/ROW]
[ROW][C]38[/C][C]98.6[/C][C]98.118[/C][C]98.7437[/C][C]-0.625799[/C][C]0.482049[/C][/ROW]
[ROW][C]39[/C][C]98.6[/C][C]98.8292[/C][C]98.9596[/C][C]-0.130382[/C][C]-0.229201[/C][/ROW]
[ROW][C]40[/C][C]98.71[/C][C]99.305[/C][C]99.2192[/C][C]0.0858681[/C][C]-0.595035[/C][/ROW]
[ROW][C]41[/C][C]99.13[/C][C]99.9548[/C][C]99.5142[/C][C]0.440618[/C][C]-0.824785[/C][/ROW]
[ROW][C]42[/C][C]99.2[/C][C]100.309[/C][C]99.8367[/C][C]0.472535[/C][C]-1.1092[/C][/ROW]
[ROW][C]43[/C][C]99.3[/C][C]100.463[/C][C]100.161[/C][C]0.301618[/C][C]-1.16287[/C][/ROW]
[ROW][C]44[/C][C]100.18[/C][C]100.757[/C][C]100.515[/C][C]0.241451[/C][C]-0.576868[/C][/ROW]
[ROW][C]45[/C][C]101.37[/C][C]101.289[/C][C]100.99[/C][C]0.298951[/C][C]0.0806319[/C][/ROW]
[ROW][C]46[/C][C]101.77[/C][C]101.711[/C][C]101.602[/C][C]0.108868[/C][C]0.0590486[/C][/ROW]
[ROW][C]47[/C][C]102.28[/C][C]102.159[/C][C]102.26[/C][C]-0.100632[/C][C]0.121049[/C][/ROW]
[ROW][C]48[/C][C]102.38[/C][C]102.531[/C][C]102.922[/C][C]-0.391882[/C][C]-0.150618[/C][/ROW]
[ROW][C]49[/C][C]102.35[/C][C]102.89[/C][C]103.591[/C][C]-0.701215[/C][C]-0.540035[/C][/ROW]
[ROW][C]50[/C][C]103.23[/C][C]103.598[/C][C]104.224[/C][C]-0.625799[/C][C]-0.367951[/C][/ROW]
[ROW][C]51[/C][C]105.37[/C][C]104.644[/C][C]104.775[/C][C]-0.130382[/C][C]0.725799[/C][/ROW]
[ROW][C]52[/C][C]106.62[/C][C]105.355[/C][C]105.269[/C][C]0.0858681[/C][C]1.26538[/C][/ROW]
[ROW][C]53[/C][C]107[/C][C]106.175[/C][C]105.734[/C][C]0.440618[/C][C]0.825215[/C][/ROW]
[ROW][C]54[/C][C]107.24[/C][C]106.649[/C][C]106.177[/C][C]0.472535[/C][C]0.590799[/C][/ROW]
[ROW][C]55[/C][C]107.31[/C][C]106.92[/C][C]106.618[/C][C]0.301618[/C][C]0.390465[/C][/ROW]
[ROW][C]56[/C][C]107.35[/C][C]107.301[/C][C]107.06[/C][C]0.241451[/C][C]0.0485486[/C][/ROW]
[ROW][C]57[/C][C]107.42[/C][C]107.787[/C][C]107.488[/C][C]0.298951[/C][C]-0.367285[/C][/ROW]
[ROW][C]58[/C][C]107.58[/C][C]108.001[/C][C]107.892[/C][C]0.108868[/C][C]-0.420951[/C][/ROW]
[ROW][C]59[/C][C]107.64[/C][C]108.177[/C][C]108.278[/C][C]-0.100632[/C][C]-0.537285[/C][/ROW]
[ROW][C]60[/C][C]107.64[/C][C]108.261[/C][C]108.652[/C][C]-0.391882[/C][C]-0.620618[/C][/ROW]
[ROW][C]61[/C][C]107.68[/C][C]108.318[/C][C]109.019[/C][C]-0.701215[/C][C]-0.637951[/C][/ROW]
[ROW][C]62[/C][C]108.51[/C][C]108.765[/C][C]109.391[/C][C]-0.625799[/C][C]-0.255451[/C][/ROW]
[ROW][C]63[/C][C]110.37[/C][C]109.639[/C][C]109.77[/C][C]-0.130382[/C][C]0.730799[/C][/ROW]
[ROW][C]64[/C][C]111.31[/C][C]110.23[/C][C]110.144[/C][C]0.0858681[/C][C]1.07997[/C][/ROW]
[ROW][C]65[/C][C]111.57[/C][C]110.958[/C][C]110.517[/C][C]0.440618[/C][C]0.612299[/C][/ROW]
[ROW][C]66[/C][C]111.66[/C][C]111.364[/C][C]110.892[/C][C]0.472535[/C][C]0.295799[/C][/ROW]
[ROW][C]67[/C][C]111.69[/C][C]NA[/C][C]NA[/C][C]0.301618[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]111.9[/C][C]NA[/C][C]NA[/C][C]0.241451[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]111.95[/C][C]NA[/C][C]NA[/C][C]0.298951[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]112.04[/C][C]NA[/C][C]NA[/C][C]0.108868[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]112.13[/C][C]NA[/C][C]NA[/C][C]-0.100632[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]112.14[/C][C]NA[/C][C]NA[/C][C]-0.391882[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294567&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294567&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	91.16	NA	NA	-0.701215	NA
2	91.17	NA	NA	-0.625799	NA
3	91.17	NA	NA	-0.130382	NA
4	91.38	NA	NA	0.0858681	NA
5	92.68	NA	NA	0.440618	NA
6	92.72	NA	NA	0.472535	NA
7	92.79	92.6304	92.3287	0.301618	0.159632
8	92.81	92.7077	92.4662	0.241451	0.102299
9	92.81	92.9027	92.6037	0.298951	-0.0927014
10	92.81	92.8439	92.735	0.108868	-0.0338681
11	92.81	92.726	92.8267	-0.100632	0.0839653
12	92.81	92.5127	92.9046	-0.391882	0.297299
13	92.81	92.3067	93.0079	-0.701215	0.503299
14	92.82	92.4938	93.1196	-0.625799	0.326215
15	92.82	93.1084	93.2387	-0.130382	-0.288368
16	92.88	93.4492	93.3633	0.0858681	-0.569201
17	93.38	93.931	93.4904	0.440618	-0.551035
18	93.89	94.093	93.6204	0.472535	-0.202951
19	94.1	94.0529	93.7512	0.301618	0.0471319
20	94.18	94.1281	93.8867	0.241451	0.0518819
21	94.3	94.3285	94.0296	0.298951	-0.0285347
22	94.31	94.2951	94.1862	0.108868	0.0148819
23	94.36	94.3081	94.4088	-0.100632	0.0518819
24	94.38	94.309	94.7008	-0.391882	0.0710486
25	94.38	94.3105	95.0117	-0.701215	0.0695486
26	94.5	94.7013	95.3271	-0.625799	-0.201285
27	94.57	95.5255	95.6558	-0.130382	-0.955451
28	94.89	96.0875	96.0017	0.0858681	-1.19753
29	96.71	96.7881	96.3475	0.440618	-0.0781181
30	97.57	97.1609	96.6883	0.472535	0.409132
31	97.88	97.3308	97.0292	0.301618	0.549215
32	97.97	97.6123	97.3708	0.241451	0.357715
33	98.4	98.0085	97.7096	0.298951	0.391465
34	98.51	98.1455	98.0367	0.108868	0.364465
35	98.46	98.196	98.2967	-0.100632	0.263965
36	98.46	98.0735	98.4654	-0.391882	0.386465
37	98.48	97.8913	98.5925	-0.701215	0.588715
38	98.6	98.118	98.7437	-0.625799	0.482049
39	98.6	98.8292	98.9596	-0.130382	-0.229201
40	98.71	99.305	99.2192	0.0858681	-0.595035
41	99.13	99.9548	99.5142	0.440618	-0.824785
42	99.2	100.309	99.8367	0.472535	-1.1092
43	99.3	100.463	100.161	0.301618	-1.16287
44	100.18	100.757	100.515	0.241451	-0.576868
45	101.37	101.289	100.99	0.298951	0.0806319
46	101.77	101.711	101.602	0.108868	0.0590486
47	102.28	102.159	102.26	-0.100632	0.121049
48	102.38	102.531	102.922	-0.391882	-0.150618
49	102.35	102.89	103.591	-0.701215	-0.540035
50	103.23	103.598	104.224	-0.625799	-0.367951
51	105.37	104.644	104.775	-0.130382	0.725799
52	106.62	105.355	105.269	0.0858681	1.26538
53	107	106.175	105.734	0.440618	0.825215
54	107.24	106.649	106.177	0.472535	0.590799
55	107.31	106.92	106.618	0.301618	0.390465
56	107.35	107.301	107.06	0.241451	0.0485486
57	107.42	107.787	107.488	0.298951	-0.367285
58	107.58	108.001	107.892	0.108868	-0.420951
59	107.64	108.177	108.278	-0.100632	-0.537285
60	107.64	108.261	108.652	-0.391882	-0.620618
61	107.68	108.318	109.019	-0.701215	-0.637951
62	108.51	108.765	109.391	-0.625799	-0.255451
63	110.37	109.639	109.77	-0.130382	0.730799
64	111.31	110.23	110.144	0.0858681	1.07997
65	111.57	110.958	110.517	0.440618	0.612299
66	111.66	111.364	110.892	0.472535	0.295799
67	111.69	NA	NA	0.301618	NA
68	111.9	NA	NA	0.241451	NA
69	111.95	NA	NA	0.298951	NA
70	112.04	NA	NA	0.108868	NA
71	112.13	NA	NA	-0.100632	NA
72	112.14	NA	NA	-0.391882	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