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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 29 Nov 2015 13:29:08 +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/2015/Nov/29/t1448803784dwuo0nfr4jpbdts.htm/, Retrieved Mon, 18 May 2026 20:04:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284435, Retrieved Mon, 18 May 2026 20:04:52 +0000

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Estimated Impact

341

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

-       [Classical Decomposition] [classic decomp ta...] [2015-11-29 13:29:08] [4bedbbf2e5251222bc39a0f973d05821] [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=284435&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=284435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284435&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	89.56	NA	NA	-0.280486	NA
2	89.84	NA	NA	-0.234153	NA
3	89.97	NA	NA	-0.153903	NA
4	90.65	NA	NA	-0.106569	NA
5	91.17	NA	NA	0.133931	NA
6	91.35	NA	NA	0.226597	NA
7	91.41	91.1577	91.1304	0.0272639	0.252319
8	91.55	91.6256	91.3333	0.292264	-0.0755972
9	91.63	91.8693	91.5158	0.353514	-0.239347
10	91.54	91.7084	91.6587	0.0496806	-0.168431
11	91.74	91.8567	91.7708	0.0858472	-0.116681
12	91.87	91.4877	91.8817	-0.393986	0.382319
13	92.13	91.7091	91.9896	-0.280486	0.420903
14	92.14	91.8592	92.0933	-0.234153	0.280819
15	92.05	92.0411	92.195	-0.153903	0.00890278
16	92	92.188	92.2946	-0.106569	-0.188014
17	92.51	92.5185	92.3846	0.133931	-0.00851389
18	92.67	92.6695	92.4429	0.226597	0.000486111
19	92.68	92.5023	92.475	0.0272639	0.177736
20	92.77	92.7956	92.5033	0.292264	-0.0255972
21	92.85	92.891	92.5375	0.353514	-0.0410139
22	92.71	92.618	92.5683	0.0496806	0.0919861
23	92.73	92.66	92.5742	0.0858472	0.0699861
24	92.28	92.1827	92.5767	-0.393986	0.0973194
25	92.49	92.3099	92.5904	-0.280486	0.180069
26	92.46	92.3746	92.6087	-0.234153	0.0854028
27	92.55	92.474	92.6279	-0.153903	0.0759861
28	92.24	92.5343	92.6408	-0.106569	-0.294264
29	92.41	92.7893	92.6554	0.133931	-0.379347
30	92.83	92.9145	92.6879	0.226597	-0.0845139
31	92.85	92.7598	92.7325	0.0272639	0.0902361
32	93.04	93.0777	92.7854	0.292264	-0.0376806
33	93.04	93.2131	92.8596	0.353514	-0.173097
34	92.83	93.0284	92.9787	0.0496806	-0.198431
35	92.96	93.2308	93.145	0.0858472	-0.270847
36	92.83	92.9327	93.3267	-0.393986	-0.102681
37	93.01	93.2362	93.5167	-0.280486	-0.226181
38	93.21	93.4996	93.7337	-0.234153	-0.289597
39	93.58	93.8398	93.9937	-0.153903	-0.259847
40	94.07	94.1751	94.2817	-0.106569	-0.105097
41	94.57	94.7185	94.5846	0.133931	-0.148514
42	95.03	95.1128	94.8862	0.226597	-0.0828472
43	95.21	95.2348	95.2075	0.0272639	-0.0247639
44	95.89	95.8702	95.5779	0.292264	0.0198194
45	96.43	96.3185	95.965	0.353514	0.111486
46	96.35	96.3943	96.3446	0.0496806	-0.0442639
47	96.71	96.815	96.7292	0.0858472	-0.105014
48	96.32	96.7268	97.1208	-0.393986	-0.406847
49	97.23	97.2245	97.505	-0.280486	0.00548611
50	97.88	97.6763	97.9104	-0.234153	0.203736
51	98.2	98.1944	98.3483	-0.153903	0.00556944
52	98.56	98.6959	98.8025	-0.106569	-0.135931
53	99.31	99.4102	99.2762	0.133931	-0.100181
54	99.69	99.9853	99.7588	0.226597	-0.295347
55	99.77	100.234	100.207	0.0272639	-0.464347
56	101.06	100.91	100.618	0.292264	0.150236
57	101.77	101.397	101.043	0.353514	0.373153
58	101.91	101.56	101.51	0.0496806	0.350319
59	102.52	102.066	101.98	0.0858472	0.453736
60	102.09	102.029	102.423	-0.393986	0.0610694
61	102.22	102.569	102.85	-0.280486	-0.349097
62	102.74	102.989	103.223	-0.234153	-0.249181
63	103.56	103.359	103.513	-0.153903	0.200569
64	104.4	103.646	103.752	-0.106569	0.754486
65	104.76	104.092	103.958	0.133931	0.667736
66	104.86	104.367	104.14	0.226597	0.493403
67	104.84	NA	NA	0.0272639	NA
68	104.96	NA	NA	0.292264	NA
69	104.83	NA	NA	0.353514	NA
70	104.58	NA	NA	0.0496806	NA
71	104.8	NA	NA	0.0858472	NA
72	104.17	NA	NA	-0.393986	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 89.56 & NA & NA & -0.280486 & NA \tabularnewline
2 & 89.84 & NA & NA & -0.234153 & NA \tabularnewline
3 & 89.97 & NA & NA & -0.153903 & NA \tabularnewline
4 & 90.65 & NA & NA & -0.106569 & NA \tabularnewline
5 & 91.17 & NA & NA & 0.133931 & NA \tabularnewline
6 & 91.35 & NA & NA & 0.226597 & NA \tabularnewline
7 & 91.41 & 91.1577 & 91.1304 & 0.0272639 & 0.252319 \tabularnewline
8 & 91.55 & 91.6256 & 91.3333 & 0.292264 & -0.0755972 \tabularnewline
9 & 91.63 & 91.8693 & 91.5158 & 0.353514 & -0.239347 \tabularnewline
10 & 91.54 & 91.7084 & 91.6587 & 0.0496806 & -0.168431 \tabularnewline
11 & 91.74 & 91.8567 & 91.7708 & 0.0858472 & -0.116681 \tabularnewline
12 & 91.87 & 91.4877 & 91.8817 & -0.393986 & 0.382319 \tabularnewline
13 & 92.13 & 91.7091 & 91.9896 & -0.280486 & 0.420903 \tabularnewline
14 & 92.14 & 91.8592 & 92.0933 & -0.234153 & 0.280819 \tabularnewline
15 & 92.05 & 92.0411 & 92.195 & -0.153903 & 0.00890278 \tabularnewline
16 & 92 & 92.188 & 92.2946 & -0.106569 & -0.188014 \tabularnewline
17 & 92.51 & 92.5185 & 92.3846 & 0.133931 & -0.00851389 \tabularnewline
18 & 92.67 & 92.6695 & 92.4429 & 0.226597 & 0.000486111 \tabularnewline
19 & 92.68 & 92.5023 & 92.475 & 0.0272639 & 0.177736 \tabularnewline
20 & 92.77 & 92.7956 & 92.5033 & 0.292264 & -0.0255972 \tabularnewline
21 & 92.85 & 92.891 & 92.5375 & 0.353514 & -0.0410139 \tabularnewline
22 & 92.71 & 92.618 & 92.5683 & 0.0496806 & 0.0919861 \tabularnewline
23 & 92.73 & 92.66 & 92.5742 & 0.0858472 & 0.0699861 \tabularnewline
24 & 92.28 & 92.1827 & 92.5767 & -0.393986 & 0.0973194 \tabularnewline
25 & 92.49 & 92.3099 & 92.5904 & -0.280486 & 0.180069 \tabularnewline
26 & 92.46 & 92.3746 & 92.6087 & -0.234153 & 0.0854028 \tabularnewline
27 & 92.55 & 92.474 & 92.6279 & -0.153903 & 0.0759861 \tabularnewline
28 & 92.24 & 92.5343 & 92.6408 & -0.106569 & -0.294264 \tabularnewline
29 & 92.41 & 92.7893 & 92.6554 & 0.133931 & -0.379347 \tabularnewline
30 & 92.83 & 92.9145 & 92.6879 & 0.226597 & -0.0845139 \tabularnewline
31 & 92.85 & 92.7598 & 92.7325 & 0.0272639 & 0.0902361 \tabularnewline
32 & 93.04 & 93.0777 & 92.7854 & 0.292264 & -0.0376806 \tabularnewline
33 & 93.04 & 93.2131 & 92.8596 & 0.353514 & -0.173097 \tabularnewline
34 & 92.83 & 93.0284 & 92.9787 & 0.0496806 & -0.198431 \tabularnewline
35 & 92.96 & 93.2308 & 93.145 & 0.0858472 & -0.270847 \tabularnewline
36 & 92.83 & 92.9327 & 93.3267 & -0.393986 & -0.102681 \tabularnewline
37 & 93.01 & 93.2362 & 93.5167 & -0.280486 & -0.226181 \tabularnewline
38 & 93.21 & 93.4996 & 93.7337 & -0.234153 & -0.289597 \tabularnewline
39 & 93.58 & 93.8398 & 93.9937 & -0.153903 & -0.259847 \tabularnewline
40 & 94.07 & 94.1751 & 94.2817 & -0.106569 & -0.105097 \tabularnewline
41 & 94.57 & 94.7185 & 94.5846 & 0.133931 & -0.148514 \tabularnewline
42 & 95.03 & 95.1128 & 94.8862 & 0.226597 & -0.0828472 \tabularnewline
43 & 95.21 & 95.2348 & 95.2075 & 0.0272639 & -0.0247639 \tabularnewline
44 & 95.89 & 95.8702 & 95.5779 & 0.292264 & 0.0198194 \tabularnewline
45 & 96.43 & 96.3185 & 95.965 & 0.353514 & 0.111486 \tabularnewline
46 & 96.35 & 96.3943 & 96.3446 & 0.0496806 & -0.0442639 \tabularnewline
47 & 96.71 & 96.815 & 96.7292 & 0.0858472 & -0.105014 \tabularnewline
48 & 96.32 & 96.7268 & 97.1208 & -0.393986 & -0.406847 \tabularnewline
49 & 97.23 & 97.2245 & 97.505 & -0.280486 & 0.00548611 \tabularnewline
50 & 97.88 & 97.6763 & 97.9104 & -0.234153 & 0.203736 \tabularnewline
51 & 98.2 & 98.1944 & 98.3483 & -0.153903 & 0.00556944 \tabularnewline
52 & 98.56 & 98.6959 & 98.8025 & -0.106569 & -0.135931 \tabularnewline
53 & 99.31 & 99.4102 & 99.2762 & 0.133931 & -0.100181 \tabularnewline
54 & 99.69 & 99.9853 & 99.7588 & 0.226597 & -0.295347 \tabularnewline
55 & 99.77 & 100.234 & 100.207 & 0.0272639 & -0.464347 \tabularnewline
56 & 101.06 & 100.91 & 100.618 & 0.292264 & 0.150236 \tabularnewline
57 & 101.77 & 101.397 & 101.043 & 0.353514 & 0.373153 \tabularnewline
58 & 101.91 & 101.56 & 101.51 & 0.0496806 & 0.350319 \tabularnewline
59 & 102.52 & 102.066 & 101.98 & 0.0858472 & 0.453736 \tabularnewline
60 & 102.09 & 102.029 & 102.423 & -0.393986 & 0.0610694 \tabularnewline
61 & 102.22 & 102.569 & 102.85 & -0.280486 & -0.349097 \tabularnewline
62 & 102.74 & 102.989 & 103.223 & -0.234153 & -0.249181 \tabularnewline
63 & 103.56 & 103.359 & 103.513 & -0.153903 & 0.200569 \tabularnewline
64 & 104.4 & 103.646 & 103.752 & -0.106569 & 0.754486 \tabularnewline
65 & 104.76 & 104.092 & 103.958 & 0.133931 & 0.667736 \tabularnewline
66 & 104.86 & 104.367 & 104.14 & 0.226597 & 0.493403 \tabularnewline
67 & 104.84 & NA & NA & 0.0272639 & NA \tabularnewline
68 & 104.96 & NA & NA & 0.292264 & NA \tabularnewline
69 & 104.83 & NA & NA & 0.353514 & NA \tabularnewline
70 & 104.58 & NA & NA & 0.0496806 & NA \tabularnewline
71 & 104.8 & NA & NA & 0.0858472 & NA \tabularnewline
72 & 104.17 & NA & NA & -0.393986 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284435&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]89.56[/C][C]NA[/C][C]NA[/C][C]-0.280486[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]89.84[/C][C]NA[/C][C]NA[/C][C]-0.234153[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]89.97[/C][C]NA[/C][C]NA[/C][C]-0.153903[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]90.65[/C][C]NA[/C][C]NA[/C][C]-0.106569[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]91.17[/C][C]NA[/C][C]NA[/C][C]0.133931[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]91.35[/C][C]NA[/C][C]NA[/C][C]0.226597[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]91.41[/C][C]91.1577[/C][C]91.1304[/C][C]0.0272639[/C][C]0.252319[/C][/ROW]
[ROW][C]8[/C][C]91.55[/C][C]91.6256[/C][C]91.3333[/C][C]0.292264[/C][C]-0.0755972[/C][/ROW]
[ROW][C]9[/C][C]91.63[/C][C]91.8693[/C][C]91.5158[/C][C]0.353514[/C][C]-0.239347[/C][/ROW]
[ROW][C]10[/C][C]91.54[/C][C]91.7084[/C][C]91.6587[/C][C]0.0496806[/C][C]-0.168431[/C][/ROW]
[ROW][C]11[/C][C]91.74[/C][C]91.8567[/C][C]91.7708[/C][C]0.0858472[/C][C]-0.116681[/C][/ROW]
[ROW][C]12[/C][C]91.87[/C][C]91.4877[/C][C]91.8817[/C][C]-0.393986[/C][C]0.382319[/C][/ROW]
[ROW][C]13[/C][C]92.13[/C][C]91.7091[/C][C]91.9896[/C][C]-0.280486[/C][C]0.420903[/C][/ROW]
[ROW][C]14[/C][C]92.14[/C][C]91.8592[/C][C]92.0933[/C][C]-0.234153[/C][C]0.280819[/C][/ROW]
[ROW][C]15[/C][C]92.05[/C][C]92.0411[/C][C]92.195[/C][C]-0.153903[/C][C]0.00890278[/C][/ROW]
[ROW][C]16[/C][C]92[/C][C]92.188[/C][C]92.2946[/C][C]-0.106569[/C][C]-0.188014[/C][/ROW]
[ROW][C]17[/C][C]92.51[/C][C]92.5185[/C][C]92.3846[/C][C]0.133931[/C][C]-0.00851389[/C][/ROW]
[ROW][C]18[/C][C]92.67[/C][C]92.6695[/C][C]92.4429[/C][C]0.226597[/C][C]0.000486111[/C][/ROW]
[ROW][C]19[/C][C]92.68[/C][C]92.5023[/C][C]92.475[/C][C]0.0272639[/C][C]0.177736[/C][/ROW]
[ROW][C]20[/C][C]92.77[/C][C]92.7956[/C][C]92.5033[/C][C]0.292264[/C][C]-0.0255972[/C][/ROW]
[ROW][C]21[/C][C]92.85[/C][C]92.891[/C][C]92.5375[/C][C]0.353514[/C][C]-0.0410139[/C][/ROW]
[ROW][C]22[/C][C]92.71[/C][C]92.618[/C][C]92.5683[/C][C]0.0496806[/C][C]0.0919861[/C][/ROW]
[ROW][C]23[/C][C]92.73[/C][C]92.66[/C][C]92.5742[/C][C]0.0858472[/C][C]0.0699861[/C][/ROW]
[ROW][C]24[/C][C]92.28[/C][C]92.1827[/C][C]92.5767[/C][C]-0.393986[/C][C]0.0973194[/C][/ROW]
[ROW][C]25[/C][C]92.49[/C][C]92.3099[/C][C]92.5904[/C][C]-0.280486[/C][C]0.180069[/C][/ROW]
[ROW][C]26[/C][C]92.46[/C][C]92.3746[/C][C]92.6087[/C][C]-0.234153[/C][C]0.0854028[/C][/ROW]
[ROW][C]27[/C][C]92.55[/C][C]92.474[/C][C]92.6279[/C][C]-0.153903[/C][C]0.0759861[/C][/ROW]
[ROW][C]28[/C][C]92.24[/C][C]92.5343[/C][C]92.6408[/C][C]-0.106569[/C][C]-0.294264[/C][/ROW]
[ROW][C]29[/C][C]92.41[/C][C]92.7893[/C][C]92.6554[/C][C]0.133931[/C][C]-0.379347[/C][/ROW]
[ROW][C]30[/C][C]92.83[/C][C]92.9145[/C][C]92.6879[/C][C]0.226597[/C][C]-0.0845139[/C][/ROW]
[ROW][C]31[/C][C]92.85[/C][C]92.7598[/C][C]92.7325[/C][C]0.0272639[/C][C]0.0902361[/C][/ROW]
[ROW][C]32[/C][C]93.04[/C][C]93.0777[/C][C]92.7854[/C][C]0.292264[/C][C]-0.0376806[/C][/ROW]
[ROW][C]33[/C][C]93.04[/C][C]93.2131[/C][C]92.8596[/C][C]0.353514[/C][C]-0.173097[/C][/ROW]
[ROW][C]34[/C][C]92.83[/C][C]93.0284[/C][C]92.9787[/C][C]0.0496806[/C][C]-0.198431[/C][/ROW]
[ROW][C]35[/C][C]92.96[/C][C]93.2308[/C][C]93.145[/C][C]0.0858472[/C][C]-0.270847[/C][/ROW]
[ROW][C]36[/C][C]92.83[/C][C]92.9327[/C][C]93.3267[/C][C]-0.393986[/C][C]-0.102681[/C][/ROW]
[ROW][C]37[/C][C]93.01[/C][C]93.2362[/C][C]93.5167[/C][C]-0.280486[/C][C]-0.226181[/C][/ROW]
[ROW][C]38[/C][C]93.21[/C][C]93.4996[/C][C]93.7337[/C][C]-0.234153[/C][C]-0.289597[/C][/ROW]
[ROW][C]39[/C][C]93.58[/C][C]93.8398[/C][C]93.9937[/C][C]-0.153903[/C][C]-0.259847[/C][/ROW]
[ROW][C]40[/C][C]94.07[/C][C]94.1751[/C][C]94.2817[/C][C]-0.106569[/C][C]-0.105097[/C][/ROW]
[ROW][C]41[/C][C]94.57[/C][C]94.7185[/C][C]94.5846[/C][C]0.133931[/C][C]-0.148514[/C][/ROW]
[ROW][C]42[/C][C]95.03[/C][C]95.1128[/C][C]94.8862[/C][C]0.226597[/C][C]-0.0828472[/C][/ROW]
[ROW][C]43[/C][C]95.21[/C][C]95.2348[/C][C]95.2075[/C][C]0.0272639[/C][C]-0.0247639[/C][/ROW]
[ROW][C]44[/C][C]95.89[/C][C]95.8702[/C][C]95.5779[/C][C]0.292264[/C][C]0.0198194[/C][/ROW]
[ROW][C]45[/C][C]96.43[/C][C]96.3185[/C][C]95.965[/C][C]0.353514[/C][C]0.111486[/C][/ROW]
[ROW][C]46[/C][C]96.35[/C][C]96.3943[/C][C]96.3446[/C][C]0.0496806[/C][C]-0.0442639[/C][/ROW]
[ROW][C]47[/C][C]96.71[/C][C]96.815[/C][C]96.7292[/C][C]0.0858472[/C][C]-0.105014[/C][/ROW]
[ROW][C]48[/C][C]96.32[/C][C]96.7268[/C][C]97.1208[/C][C]-0.393986[/C][C]-0.406847[/C][/ROW]
[ROW][C]49[/C][C]97.23[/C][C]97.2245[/C][C]97.505[/C][C]-0.280486[/C][C]0.00548611[/C][/ROW]
[ROW][C]50[/C][C]97.88[/C][C]97.6763[/C][C]97.9104[/C][C]-0.234153[/C][C]0.203736[/C][/ROW]
[ROW][C]51[/C][C]98.2[/C][C]98.1944[/C][C]98.3483[/C][C]-0.153903[/C][C]0.00556944[/C][/ROW]
[ROW][C]52[/C][C]98.56[/C][C]98.6959[/C][C]98.8025[/C][C]-0.106569[/C][C]-0.135931[/C][/ROW]
[ROW][C]53[/C][C]99.31[/C][C]99.4102[/C][C]99.2762[/C][C]0.133931[/C][C]-0.100181[/C][/ROW]
[ROW][C]54[/C][C]99.69[/C][C]99.9853[/C][C]99.7588[/C][C]0.226597[/C][C]-0.295347[/C][/ROW]
[ROW][C]55[/C][C]99.77[/C][C]100.234[/C][C]100.207[/C][C]0.0272639[/C][C]-0.464347[/C][/ROW]
[ROW][C]56[/C][C]101.06[/C][C]100.91[/C][C]100.618[/C][C]0.292264[/C][C]0.150236[/C][/ROW]
[ROW][C]57[/C][C]101.77[/C][C]101.397[/C][C]101.043[/C][C]0.353514[/C][C]0.373153[/C][/ROW]
[ROW][C]58[/C][C]101.91[/C][C]101.56[/C][C]101.51[/C][C]0.0496806[/C][C]0.350319[/C][/ROW]
[ROW][C]59[/C][C]102.52[/C][C]102.066[/C][C]101.98[/C][C]0.0858472[/C][C]0.453736[/C][/ROW]
[ROW][C]60[/C][C]102.09[/C][C]102.029[/C][C]102.423[/C][C]-0.393986[/C][C]0.0610694[/C][/ROW]
[ROW][C]61[/C][C]102.22[/C][C]102.569[/C][C]102.85[/C][C]-0.280486[/C][C]-0.349097[/C][/ROW]
[ROW][C]62[/C][C]102.74[/C][C]102.989[/C][C]103.223[/C][C]-0.234153[/C][C]-0.249181[/C][/ROW]
[ROW][C]63[/C][C]103.56[/C][C]103.359[/C][C]103.513[/C][C]-0.153903[/C][C]0.200569[/C][/ROW]
[ROW][C]64[/C][C]104.4[/C][C]103.646[/C][C]103.752[/C][C]-0.106569[/C][C]0.754486[/C][/ROW]
[ROW][C]65[/C][C]104.76[/C][C]104.092[/C][C]103.958[/C][C]0.133931[/C][C]0.667736[/C][/ROW]
[ROW][C]66[/C][C]104.86[/C][C]104.367[/C][C]104.14[/C][C]0.226597[/C][C]0.493403[/C][/ROW]
[ROW][C]67[/C][C]104.84[/C][C]NA[/C][C]NA[/C][C]0.0272639[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]104.96[/C][C]NA[/C][C]NA[/C][C]0.292264[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]104.83[/C][C]NA[/C][C]NA[/C][C]0.353514[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]104.58[/C][C]NA[/C][C]NA[/C][C]0.0496806[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]104.8[/C][C]NA[/C][C]NA[/C][C]0.0858472[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]104.17[/C][C]NA[/C][C]NA[/C][C]-0.393986[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284435&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	89.56	NA	NA	-0.280486	NA
2	89.84	NA	NA	-0.234153	NA
3	89.97	NA	NA	-0.153903	NA
4	90.65	NA	NA	-0.106569	NA
5	91.17	NA	NA	0.133931	NA
6	91.35	NA	NA	0.226597	NA
7	91.41	91.1577	91.1304	0.0272639	0.252319
8	91.55	91.6256	91.3333	0.292264	-0.0755972
9	91.63	91.8693	91.5158	0.353514	-0.239347
10	91.54	91.7084	91.6587	0.0496806	-0.168431
11	91.74	91.8567	91.7708	0.0858472	-0.116681
12	91.87	91.4877	91.8817	-0.393986	0.382319
13	92.13	91.7091	91.9896	-0.280486	0.420903
14	92.14	91.8592	92.0933	-0.234153	0.280819
15	92.05	92.0411	92.195	-0.153903	0.00890278
16	92	92.188	92.2946	-0.106569	-0.188014
17	92.51	92.5185	92.3846	0.133931	-0.00851389
18	92.67	92.6695	92.4429	0.226597	0.000486111
19	92.68	92.5023	92.475	0.0272639	0.177736
20	92.77	92.7956	92.5033	0.292264	-0.0255972
21	92.85	92.891	92.5375	0.353514	-0.0410139
22	92.71	92.618	92.5683	0.0496806	0.0919861
23	92.73	92.66	92.5742	0.0858472	0.0699861
24	92.28	92.1827	92.5767	-0.393986	0.0973194
25	92.49	92.3099	92.5904	-0.280486	0.180069
26	92.46	92.3746	92.6087	-0.234153	0.0854028
27	92.55	92.474	92.6279	-0.153903	0.0759861
28	92.24	92.5343	92.6408	-0.106569	-0.294264
29	92.41	92.7893	92.6554	0.133931	-0.379347
30	92.83	92.9145	92.6879	0.226597	-0.0845139
31	92.85	92.7598	92.7325	0.0272639	0.0902361
32	93.04	93.0777	92.7854	0.292264	-0.0376806
33	93.04	93.2131	92.8596	0.353514	-0.173097
34	92.83	93.0284	92.9787	0.0496806	-0.198431
35	92.96	93.2308	93.145	0.0858472	-0.270847
36	92.83	92.9327	93.3267	-0.393986	-0.102681
37	93.01	93.2362	93.5167	-0.280486	-0.226181
38	93.21	93.4996	93.7337	-0.234153	-0.289597
39	93.58	93.8398	93.9937	-0.153903	-0.259847
40	94.07	94.1751	94.2817	-0.106569	-0.105097
41	94.57	94.7185	94.5846	0.133931	-0.148514
42	95.03	95.1128	94.8862	0.226597	-0.0828472
43	95.21	95.2348	95.2075	0.0272639	-0.0247639
44	95.89	95.8702	95.5779	0.292264	0.0198194
45	96.43	96.3185	95.965	0.353514	0.111486
46	96.35	96.3943	96.3446	0.0496806	-0.0442639
47	96.71	96.815	96.7292	0.0858472	-0.105014
48	96.32	96.7268	97.1208	-0.393986	-0.406847
49	97.23	97.2245	97.505	-0.280486	0.00548611
50	97.88	97.6763	97.9104	-0.234153	0.203736
51	98.2	98.1944	98.3483	-0.153903	0.00556944
52	98.56	98.6959	98.8025	-0.106569	-0.135931
53	99.31	99.4102	99.2762	0.133931	-0.100181
54	99.69	99.9853	99.7588	0.226597	-0.295347
55	99.77	100.234	100.207	0.0272639	-0.464347
56	101.06	100.91	100.618	0.292264	0.150236
57	101.77	101.397	101.043	0.353514	0.373153
58	101.91	101.56	101.51	0.0496806	0.350319
59	102.52	102.066	101.98	0.0858472	0.453736
60	102.09	102.029	102.423	-0.393986	0.0610694
61	102.22	102.569	102.85	-0.280486	-0.349097
62	102.74	102.989	103.223	-0.234153	-0.249181
63	103.56	103.359	103.513	-0.153903	0.200569
64	104.4	103.646	103.752	-0.106569	0.754486
65	104.76	104.092	103.958	0.133931	0.667736
66	104.86	104.367	104.14	0.226597	0.493403
67	104.84	NA	NA	0.0272639	NA
68	104.96	NA	NA	0.292264	NA
69	104.83	NA	NA	0.353514	NA
70	104.58	NA	NA	0.0496806	NA
71	104.8	NA	NA	0.0858472	NA
72	104.17	NA	NA	-0.393986	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