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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Tue, 26 Apr 2016 10:32:47 +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/26/t1461664062voap3rr7yaz6sgv.htm/, Retrieved Fri, 03 May 2024 16:42:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294837, Retrieved Fri, 03 May 2024 16:42:05 +0000

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-       [Classical Decomposition] [] [2016-04-26 09:32:47] [ac7ea8eb5659db737c8f3ddefda617c5] [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=294837&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=294837&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294837&T=0

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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	340.4	NA	NA	0.167465	NA
2	343.2	NA	NA	-0.695729	NA
3	345	NA	NA	-0.307674	NA
4	346.6	NA	NA	0.0289931	NA
5	348.7	NA	NA	0.306493	NA
6	351.1	NA	NA	-0.125174	NA
7	352.7	354.106	354.692	-0.586007	-1.40566
8	354.8	356.419	357.05	-0.631146	-1.61885
9	359.8	359.038	359.408	-0.370035	0.761701
10	364.4	362.66	361.938	0.722326	1.74017
11	366.2	365.357	364.596	0.761215	0.842951
12	368.8	368.008	367.279	0.729271	0.791562
13	369.6	370.226	370.058	0.167465	-0.625799
14	370.6	372.329	373.025	-0.695729	-1.72927
15	374.2	375.713	376.021	-0.307674	-1.51316
16	378.1	378.966	378.938	0.0289931	-0.866493
17	381	382.223	381.917	0.306493	-1.22316
18	383.2	384.887	385.013	-0.125174	-1.68733
19	387.3	387.681	388.267	-0.586007	-0.38066
20	391.4	391.106	391.737	-0.631146	0.293646
21	395.1	394.988	395.358	-0.370035	0.111701
22	399.1	399.726	399.004	0.722326	-0.626493
23	403	403.299	402.537	0.761215	-0.298715
24	406.3	406.758	406.029	0.729271	-0.458437
25	410.2	409.626	409.458	0.167465	0.574201
26	413.3	412.067	412.762	-0.695729	1.23323
27	418.4	415.68	415.987	-0.307674	2.72017
28	421.4	419.204	419.175	0.0289931	2.19601
29	422.5	422.619	422.312	0.306493	-0.118993
30	425.5	425.254	425.379	-0.125174	0.246007
31	427.3	427.797	428.383	-0.586007	-0.497326
32	430.7	430.598	431.229	-0.631146	0.101979
33	433.2	433.517	433.888	-0.370035	-0.317465
34	437.5	437.251	436.529	0.722326	0.248507
35	439.9	440.124	439.362	0.761215	-0.223715
36	443	443.058	442.329	0.729271	-0.0584375
37	445.6	445.501	445.333	0.167465	0.0992014
38	446.2	447.625	448.321	-0.695729	-1.4251
39	449.3	450.946	451.254	-0.307674	-1.64649
40	453.9	454.171	454.142	0.0289931	-0.27066
41	458	457.323	457.017	0.306493	0.67684
42	461.2	459.771	459.896	-0.125174	1.42934
43	463.7	462.164	462.75	-0.586007	1.53601
44	466	465.061	465.692	-0.631146	0.939479
45	468.3	468.351	468.721	-0.370035	-0.0507986
46	471.7	472.397	471.675	0.722326	-0.697326
47	474.7	475.295	474.533	0.761215	-0.594549
48	477.3	478.079	477.35	0.729271	-0.779271
49	479.8	480.359	480.192	0.167465	-0.559132
50	482.6	482.442	483.138	-0.695729	0.158229
51	485.6	485.896	486.204	-0.307674	-0.296493
52	488.5	489.462	489.433	0.0289931	-0.962326
53	492	493.152	492.846	0.306493	-1.15233
54	494.8	496.3	496.425	-0.125174	-1.49983
55	498.3	499.601	500.188	-0.586007	-1.30149
56	502.1	503.477	504.108	-0.631146	-1.37719
57	505.8	507.776	508.146	-0.370035	-1.9758
58	511.7	512.993	512.271	0.722326	-1.29316
59	516.6	517.303	516.542	0.761215	-0.702882
60	521.3	521.667	520.937	0.729271	-0.366771
61	526.1	525.522	525.354	0.167465	0.578368
62	530.4	529.046	529.742	-0.695729	1.35406
63	534.7	533.763	534.071	-0.307674	0.93684
64	538.4	538.296	538.267	0.0289931	0.10434
65	544.6	542.581	542.275	0.306493	2.01851
66	547.7	545.987	546.112	-0.125174	1.71267
67	551.4	549.11	549.696	-0.586007	2.29017
68	554.3	552.398	553.029	-0.631146	1.90198
69	557.5	555.788	556.158	-0.370035	1.7117
70	560.7	559.831	559.108	0.722326	0.86934
71	563.8	562.582	561.821	0.761215	1.21795
72	566.2	565.088	564.358	0.729271	1.1124
73	567.2	567.026	566.858	0.167465	0.174201
74	569.3	568.65	569.346	-0.695729	0.649896
75	570.9	NA	NA	-0.307674	NA
76	573	NA	NA	0.0289931	NA
77	575.1	NA	NA	0.306493	NA
78	578.1	NA	NA	-0.125174	NA
79	581	NA	NA	-0.586007	NA
80	584.4	NA	NA	-0.631146	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 340.4 & NA & NA & 0.167465 & NA \tabularnewline
2 & 343.2 & NA & NA & -0.695729 & NA \tabularnewline
3 & 345 & NA & NA & -0.307674 & NA \tabularnewline
4 & 346.6 & NA & NA & 0.0289931 & NA \tabularnewline
5 & 348.7 & NA & NA & 0.306493 & NA \tabularnewline
6 & 351.1 & NA & NA & -0.125174 & NA \tabularnewline
7 & 352.7 & 354.106 & 354.692 & -0.586007 & -1.40566 \tabularnewline
8 & 354.8 & 356.419 & 357.05 & -0.631146 & -1.61885 \tabularnewline
9 & 359.8 & 359.038 & 359.408 & -0.370035 & 0.761701 \tabularnewline
10 & 364.4 & 362.66 & 361.938 & 0.722326 & 1.74017 \tabularnewline
11 & 366.2 & 365.357 & 364.596 & 0.761215 & 0.842951 \tabularnewline
12 & 368.8 & 368.008 & 367.279 & 0.729271 & 0.791562 \tabularnewline
13 & 369.6 & 370.226 & 370.058 & 0.167465 & -0.625799 \tabularnewline
14 & 370.6 & 372.329 & 373.025 & -0.695729 & -1.72927 \tabularnewline
15 & 374.2 & 375.713 & 376.021 & -0.307674 & -1.51316 \tabularnewline
16 & 378.1 & 378.966 & 378.938 & 0.0289931 & -0.866493 \tabularnewline
17 & 381 & 382.223 & 381.917 & 0.306493 & -1.22316 \tabularnewline
18 & 383.2 & 384.887 & 385.013 & -0.125174 & -1.68733 \tabularnewline
19 & 387.3 & 387.681 & 388.267 & -0.586007 & -0.38066 \tabularnewline
20 & 391.4 & 391.106 & 391.737 & -0.631146 & 0.293646 \tabularnewline
21 & 395.1 & 394.988 & 395.358 & -0.370035 & 0.111701 \tabularnewline
22 & 399.1 & 399.726 & 399.004 & 0.722326 & -0.626493 \tabularnewline
23 & 403 & 403.299 & 402.537 & 0.761215 & -0.298715 \tabularnewline
24 & 406.3 & 406.758 & 406.029 & 0.729271 & -0.458437 \tabularnewline
25 & 410.2 & 409.626 & 409.458 & 0.167465 & 0.574201 \tabularnewline
26 & 413.3 & 412.067 & 412.762 & -0.695729 & 1.23323 \tabularnewline
27 & 418.4 & 415.68 & 415.987 & -0.307674 & 2.72017 \tabularnewline
28 & 421.4 & 419.204 & 419.175 & 0.0289931 & 2.19601 \tabularnewline
29 & 422.5 & 422.619 & 422.312 & 0.306493 & -0.118993 \tabularnewline
30 & 425.5 & 425.254 & 425.379 & -0.125174 & 0.246007 \tabularnewline
31 & 427.3 & 427.797 & 428.383 & -0.586007 & -0.497326 \tabularnewline
32 & 430.7 & 430.598 & 431.229 & -0.631146 & 0.101979 \tabularnewline
33 & 433.2 & 433.517 & 433.888 & -0.370035 & -0.317465 \tabularnewline
34 & 437.5 & 437.251 & 436.529 & 0.722326 & 0.248507 \tabularnewline
35 & 439.9 & 440.124 & 439.362 & 0.761215 & -0.223715 \tabularnewline
36 & 443 & 443.058 & 442.329 & 0.729271 & -0.0584375 \tabularnewline
37 & 445.6 & 445.501 & 445.333 & 0.167465 & 0.0992014 \tabularnewline
38 & 446.2 & 447.625 & 448.321 & -0.695729 & -1.4251 \tabularnewline
39 & 449.3 & 450.946 & 451.254 & -0.307674 & -1.64649 \tabularnewline
40 & 453.9 & 454.171 & 454.142 & 0.0289931 & -0.27066 \tabularnewline
41 & 458 & 457.323 & 457.017 & 0.306493 & 0.67684 \tabularnewline
42 & 461.2 & 459.771 & 459.896 & -0.125174 & 1.42934 \tabularnewline
43 & 463.7 & 462.164 & 462.75 & -0.586007 & 1.53601 \tabularnewline
44 & 466 & 465.061 & 465.692 & -0.631146 & 0.939479 \tabularnewline
45 & 468.3 & 468.351 & 468.721 & -0.370035 & -0.0507986 \tabularnewline
46 & 471.7 & 472.397 & 471.675 & 0.722326 & -0.697326 \tabularnewline
47 & 474.7 & 475.295 & 474.533 & 0.761215 & -0.594549 \tabularnewline
48 & 477.3 & 478.079 & 477.35 & 0.729271 & -0.779271 \tabularnewline
49 & 479.8 & 480.359 & 480.192 & 0.167465 & -0.559132 \tabularnewline
50 & 482.6 & 482.442 & 483.138 & -0.695729 & 0.158229 \tabularnewline
51 & 485.6 & 485.896 & 486.204 & -0.307674 & -0.296493 \tabularnewline
52 & 488.5 & 489.462 & 489.433 & 0.0289931 & -0.962326 \tabularnewline
53 & 492 & 493.152 & 492.846 & 0.306493 & -1.15233 \tabularnewline
54 & 494.8 & 496.3 & 496.425 & -0.125174 & -1.49983 \tabularnewline
55 & 498.3 & 499.601 & 500.188 & -0.586007 & -1.30149 \tabularnewline
56 & 502.1 & 503.477 & 504.108 & -0.631146 & -1.37719 \tabularnewline
57 & 505.8 & 507.776 & 508.146 & -0.370035 & -1.9758 \tabularnewline
58 & 511.7 & 512.993 & 512.271 & 0.722326 & -1.29316 \tabularnewline
59 & 516.6 & 517.303 & 516.542 & 0.761215 & -0.702882 \tabularnewline
60 & 521.3 & 521.667 & 520.937 & 0.729271 & -0.366771 \tabularnewline
61 & 526.1 & 525.522 & 525.354 & 0.167465 & 0.578368 \tabularnewline
62 & 530.4 & 529.046 & 529.742 & -0.695729 & 1.35406 \tabularnewline
63 & 534.7 & 533.763 & 534.071 & -0.307674 & 0.93684 \tabularnewline
64 & 538.4 & 538.296 & 538.267 & 0.0289931 & 0.10434 \tabularnewline
65 & 544.6 & 542.581 & 542.275 & 0.306493 & 2.01851 \tabularnewline
66 & 547.7 & 545.987 & 546.112 & -0.125174 & 1.71267 \tabularnewline
67 & 551.4 & 549.11 & 549.696 & -0.586007 & 2.29017 \tabularnewline
68 & 554.3 & 552.398 & 553.029 & -0.631146 & 1.90198 \tabularnewline
69 & 557.5 & 555.788 & 556.158 & -0.370035 & 1.7117 \tabularnewline
70 & 560.7 & 559.831 & 559.108 & 0.722326 & 0.86934 \tabularnewline
71 & 563.8 & 562.582 & 561.821 & 0.761215 & 1.21795 \tabularnewline
72 & 566.2 & 565.088 & 564.358 & 0.729271 & 1.1124 \tabularnewline
73 & 567.2 & 567.026 & 566.858 & 0.167465 & 0.174201 \tabularnewline
74 & 569.3 & 568.65 & 569.346 & -0.695729 & 0.649896 \tabularnewline
75 & 570.9 & NA & NA & -0.307674 & NA \tabularnewline
76 & 573 & NA & NA & 0.0289931 & NA \tabularnewline
77 & 575.1 & NA & NA & 0.306493 & NA \tabularnewline
78 & 578.1 & NA & NA & -0.125174 & NA \tabularnewline
79 & 581 & NA & NA & -0.586007 & NA \tabularnewline
80 & 584.4 & NA & NA & -0.631146 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294837&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]340.4[/C][C]NA[/C][C]NA[/C][C]0.167465[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]343.2[/C][C]NA[/C][C]NA[/C][C]-0.695729[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]345[/C][C]NA[/C][C]NA[/C][C]-0.307674[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]346.6[/C][C]NA[/C][C]NA[/C][C]0.0289931[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]348.7[/C][C]NA[/C][C]NA[/C][C]0.306493[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]351.1[/C][C]NA[/C][C]NA[/C][C]-0.125174[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]352.7[/C][C]354.106[/C][C]354.692[/C][C]-0.586007[/C][C]-1.40566[/C][/ROW]
[ROW][C]8[/C][C]354.8[/C][C]356.419[/C][C]357.05[/C][C]-0.631146[/C][C]-1.61885[/C][/ROW]
[ROW][C]9[/C][C]359.8[/C][C]359.038[/C][C]359.408[/C][C]-0.370035[/C][C]0.761701[/C][/ROW]
[ROW][C]10[/C][C]364.4[/C][C]362.66[/C][C]361.938[/C][C]0.722326[/C][C]1.74017[/C][/ROW]
[ROW][C]11[/C][C]366.2[/C][C]365.357[/C][C]364.596[/C][C]0.761215[/C][C]0.842951[/C][/ROW]
[ROW][C]12[/C][C]368.8[/C][C]368.008[/C][C]367.279[/C][C]0.729271[/C][C]0.791562[/C][/ROW]
[ROW][C]13[/C][C]369.6[/C][C]370.226[/C][C]370.058[/C][C]0.167465[/C][C]-0.625799[/C][/ROW]
[ROW][C]14[/C][C]370.6[/C][C]372.329[/C][C]373.025[/C][C]-0.695729[/C][C]-1.72927[/C][/ROW]
[ROW][C]15[/C][C]374.2[/C][C]375.713[/C][C]376.021[/C][C]-0.307674[/C][C]-1.51316[/C][/ROW]
[ROW][C]16[/C][C]378.1[/C][C]378.966[/C][C]378.938[/C][C]0.0289931[/C][C]-0.866493[/C][/ROW]
[ROW][C]17[/C][C]381[/C][C]382.223[/C][C]381.917[/C][C]0.306493[/C][C]-1.22316[/C][/ROW]
[ROW][C]18[/C][C]383.2[/C][C]384.887[/C][C]385.013[/C][C]-0.125174[/C][C]-1.68733[/C][/ROW]
[ROW][C]19[/C][C]387.3[/C][C]387.681[/C][C]388.267[/C][C]-0.586007[/C][C]-0.38066[/C][/ROW]
[ROW][C]20[/C][C]391.4[/C][C]391.106[/C][C]391.737[/C][C]-0.631146[/C][C]0.293646[/C][/ROW]
[ROW][C]21[/C][C]395.1[/C][C]394.988[/C][C]395.358[/C][C]-0.370035[/C][C]0.111701[/C][/ROW]
[ROW][C]22[/C][C]399.1[/C][C]399.726[/C][C]399.004[/C][C]0.722326[/C][C]-0.626493[/C][/ROW]
[ROW][C]23[/C][C]403[/C][C]403.299[/C][C]402.537[/C][C]0.761215[/C][C]-0.298715[/C][/ROW]
[ROW][C]24[/C][C]406.3[/C][C]406.758[/C][C]406.029[/C][C]0.729271[/C][C]-0.458437[/C][/ROW]
[ROW][C]25[/C][C]410.2[/C][C]409.626[/C][C]409.458[/C][C]0.167465[/C][C]0.574201[/C][/ROW]
[ROW][C]26[/C][C]413.3[/C][C]412.067[/C][C]412.762[/C][C]-0.695729[/C][C]1.23323[/C][/ROW]
[ROW][C]27[/C][C]418.4[/C][C]415.68[/C][C]415.987[/C][C]-0.307674[/C][C]2.72017[/C][/ROW]
[ROW][C]28[/C][C]421.4[/C][C]419.204[/C][C]419.175[/C][C]0.0289931[/C][C]2.19601[/C][/ROW]
[ROW][C]29[/C][C]422.5[/C][C]422.619[/C][C]422.312[/C][C]0.306493[/C][C]-0.118993[/C][/ROW]
[ROW][C]30[/C][C]425.5[/C][C]425.254[/C][C]425.379[/C][C]-0.125174[/C][C]0.246007[/C][/ROW]
[ROW][C]31[/C][C]427.3[/C][C]427.797[/C][C]428.383[/C][C]-0.586007[/C][C]-0.497326[/C][/ROW]
[ROW][C]32[/C][C]430.7[/C][C]430.598[/C][C]431.229[/C][C]-0.631146[/C][C]0.101979[/C][/ROW]
[ROW][C]33[/C][C]433.2[/C][C]433.517[/C][C]433.888[/C][C]-0.370035[/C][C]-0.317465[/C][/ROW]
[ROW][C]34[/C][C]437.5[/C][C]437.251[/C][C]436.529[/C][C]0.722326[/C][C]0.248507[/C][/ROW]
[ROW][C]35[/C][C]439.9[/C][C]440.124[/C][C]439.362[/C][C]0.761215[/C][C]-0.223715[/C][/ROW]
[ROW][C]36[/C][C]443[/C][C]443.058[/C][C]442.329[/C][C]0.729271[/C][C]-0.0584375[/C][/ROW]
[ROW][C]37[/C][C]445.6[/C][C]445.501[/C][C]445.333[/C][C]0.167465[/C][C]0.0992014[/C][/ROW]
[ROW][C]38[/C][C]446.2[/C][C]447.625[/C][C]448.321[/C][C]-0.695729[/C][C]-1.4251[/C][/ROW]
[ROW][C]39[/C][C]449.3[/C][C]450.946[/C][C]451.254[/C][C]-0.307674[/C][C]-1.64649[/C][/ROW]
[ROW][C]40[/C][C]453.9[/C][C]454.171[/C][C]454.142[/C][C]0.0289931[/C][C]-0.27066[/C][/ROW]
[ROW][C]41[/C][C]458[/C][C]457.323[/C][C]457.017[/C][C]0.306493[/C][C]0.67684[/C][/ROW]
[ROW][C]42[/C][C]461.2[/C][C]459.771[/C][C]459.896[/C][C]-0.125174[/C][C]1.42934[/C][/ROW]
[ROW][C]43[/C][C]463.7[/C][C]462.164[/C][C]462.75[/C][C]-0.586007[/C][C]1.53601[/C][/ROW]
[ROW][C]44[/C][C]466[/C][C]465.061[/C][C]465.692[/C][C]-0.631146[/C][C]0.939479[/C][/ROW]
[ROW][C]45[/C][C]468.3[/C][C]468.351[/C][C]468.721[/C][C]-0.370035[/C][C]-0.0507986[/C][/ROW]
[ROW][C]46[/C][C]471.7[/C][C]472.397[/C][C]471.675[/C][C]0.722326[/C][C]-0.697326[/C][/ROW]
[ROW][C]47[/C][C]474.7[/C][C]475.295[/C][C]474.533[/C][C]0.761215[/C][C]-0.594549[/C][/ROW]
[ROW][C]48[/C][C]477.3[/C][C]478.079[/C][C]477.35[/C][C]0.729271[/C][C]-0.779271[/C][/ROW]
[ROW][C]49[/C][C]479.8[/C][C]480.359[/C][C]480.192[/C][C]0.167465[/C][C]-0.559132[/C][/ROW]
[ROW][C]50[/C][C]482.6[/C][C]482.442[/C][C]483.138[/C][C]-0.695729[/C][C]0.158229[/C][/ROW]
[ROW][C]51[/C][C]485.6[/C][C]485.896[/C][C]486.204[/C][C]-0.307674[/C][C]-0.296493[/C][/ROW]
[ROW][C]52[/C][C]488.5[/C][C]489.462[/C][C]489.433[/C][C]0.0289931[/C][C]-0.962326[/C][/ROW]
[ROW][C]53[/C][C]492[/C][C]493.152[/C][C]492.846[/C][C]0.306493[/C][C]-1.15233[/C][/ROW]
[ROW][C]54[/C][C]494.8[/C][C]496.3[/C][C]496.425[/C][C]-0.125174[/C][C]-1.49983[/C][/ROW]
[ROW][C]55[/C][C]498.3[/C][C]499.601[/C][C]500.188[/C][C]-0.586007[/C][C]-1.30149[/C][/ROW]
[ROW][C]56[/C][C]502.1[/C][C]503.477[/C][C]504.108[/C][C]-0.631146[/C][C]-1.37719[/C][/ROW]
[ROW][C]57[/C][C]505.8[/C][C]507.776[/C][C]508.146[/C][C]-0.370035[/C][C]-1.9758[/C][/ROW]
[ROW][C]58[/C][C]511.7[/C][C]512.993[/C][C]512.271[/C][C]0.722326[/C][C]-1.29316[/C][/ROW]
[ROW][C]59[/C][C]516.6[/C][C]517.303[/C][C]516.542[/C][C]0.761215[/C][C]-0.702882[/C][/ROW]
[ROW][C]60[/C][C]521.3[/C][C]521.667[/C][C]520.937[/C][C]0.729271[/C][C]-0.366771[/C][/ROW]
[ROW][C]61[/C][C]526.1[/C][C]525.522[/C][C]525.354[/C][C]0.167465[/C][C]0.578368[/C][/ROW]
[ROW][C]62[/C][C]530.4[/C][C]529.046[/C][C]529.742[/C][C]-0.695729[/C][C]1.35406[/C][/ROW]
[ROW][C]63[/C][C]534.7[/C][C]533.763[/C][C]534.071[/C][C]-0.307674[/C][C]0.93684[/C][/ROW]
[ROW][C]64[/C][C]538.4[/C][C]538.296[/C][C]538.267[/C][C]0.0289931[/C][C]0.10434[/C][/ROW]
[ROW][C]65[/C][C]544.6[/C][C]542.581[/C][C]542.275[/C][C]0.306493[/C][C]2.01851[/C][/ROW]
[ROW][C]66[/C][C]547.7[/C][C]545.987[/C][C]546.112[/C][C]-0.125174[/C][C]1.71267[/C][/ROW]
[ROW][C]67[/C][C]551.4[/C][C]549.11[/C][C]549.696[/C][C]-0.586007[/C][C]2.29017[/C][/ROW]
[ROW][C]68[/C][C]554.3[/C][C]552.398[/C][C]553.029[/C][C]-0.631146[/C][C]1.90198[/C][/ROW]
[ROW][C]69[/C][C]557.5[/C][C]555.788[/C][C]556.158[/C][C]-0.370035[/C][C]1.7117[/C][/ROW]
[ROW][C]70[/C][C]560.7[/C][C]559.831[/C][C]559.108[/C][C]0.722326[/C][C]0.86934[/C][/ROW]
[ROW][C]71[/C][C]563.8[/C][C]562.582[/C][C]561.821[/C][C]0.761215[/C][C]1.21795[/C][/ROW]
[ROW][C]72[/C][C]566.2[/C][C]565.088[/C][C]564.358[/C][C]0.729271[/C][C]1.1124[/C][/ROW]
[ROW][C]73[/C][C]567.2[/C][C]567.026[/C][C]566.858[/C][C]0.167465[/C][C]0.174201[/C][/ROW]
[ROW][C]74[/C][C]569.3[/C][C]568.65[/C][C]569.346[/C][C]-0.695729[/C][C]0.649896[/C][/ROW]
[ROW][C]75[/C][C]570.9[/C][C]NA[/C][C]NA[/C][C]-0.307674[/C][C]NA[/C][/ROW]
[ROW][C]76[/C][C]573[/C][C]NA[/C][C]NA[/C][C]0.0289931[/C][C]NA[/C][/ROW]
[ROW][C]77[/C][C]575.1[/C][C]NA[/C][C]NA[/C][C]0.306493[/C][C]NA[/C][/ROW]
[ROW][C]78[/C][C]578.1[/C][C]NA[/C][C]NA[/C][C]-0.125174[/C][C]NA[/C][/ROW]
[ROW][C]79[/C][C]581[/C][C]NA[/C][C]NA[/C][C]-0.586007[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]584.4[/C][C]NA[/C][C]NA[/C][C]-0.631146[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294837&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294837&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	340.4	NA	NA	0.167465	NA
2	343.2	NA	NA	-0.695729	NA
3	345	NA	NA	-0.307674	NA
4	346.6	NA	NA	0.0289931	NA
5	348.7	NA	NA	0.306493	NA
6	351.1	NA	NA	-0.125174	NA
7	352.7	354.106	354.692	-0.586007	-1.40566
8	354.8	356.419	357.05	-0.631146	-1.61885
9	359.8	359.038	359.408	-0.370035	0.761701
10	364.4	362.66	361.938	0.722326	1.74017
11	366.2	365.357	364.596	0.761215	0.842951
12	368.8	368.008	367.279	0.729271	0.791562
13	369.6	370.226	370.058	0.167465	-0.625799
14	370.6	372.329	373.025	-0.695729	-1.72927
15	374.2	375.713	376.021	-0.307674	-1.51316
16	378.1	378.966	378.938	0.0289931	-0.866493
17	381	382.223	381.917	0.306493	-1.22316
18	383.2	384.887	385.013	-0.125174	-1.68733
19	387.3	387.681	388.267	-0.586007	-0.38066
20	391.4	391.106	391.737	-0.631146	0.293646
21	395.1	394.988	395.358	-0.370035	0.111701
22	399.1	399.726	399.004	0.722326	-0.626493
23	403	403.299	402.537	0.761215	-0.298715
24	406.3	406.758	406.029	0.729271	-0.458437
25	410.2	409.626	409.458	0.167465	0.574201
26	413.3	412.067	412.762	-0.695729	1.23323
27	418.4	415.68	415.987	-0.307674	2.72017
28	421.4	419.204	419.175	0.0289931	2.19601
29	422.5	422.619	422.312	0.306493	-0.118993
30	425.5	425.254	425.379	-0.125174	0.246007
31	427.3	427.797	428.383	-0.586007	-0.497326
32	430.7	430.598	431.229	-0.631146	0.101979
33	433.2	433.517	433.888	-0.370035	-0.317465
34	437.5	437.251	436.529	0.722326	0.248507
35	439.9	440.124	439.362	0.761215	-0.223715
36	443	443.058	442.329	0.729271	-0.0584375
37	445.6	445.501	445.333	0.167465	0.0992014
38	446.2	447.625	448.321	-0.695729	-1.4251
39	449.3	450.946	451.254	-0.307674	-1.64649
40	453.9	454.171	454.142	0.0289931	-0.27066
41	458	457.323	457.017	0.306493	0.67684
42	461.2	459.771	459.896	-0.125174	1.42934
43	463.7	462.164	462.75	-0.586007	1.53601
44	466	465.061	465.692	-0.631146	0.939479
45	468.3	468.351	468.721	-0.370035	-0.0507986
46	471.7	472.397	471.675	0.722326	-0.697326
47	474.7	475.295	474.533	0.761215	-0.594549
48	477.3	478.079	477.35	0.729271	-0.779271
49	479.8	480.359	480.192	0.167465	-0.559132
50	482.6	482.442	483.138	-0.695729	0.158229
51	485.6	485.896	486.204	-0.307674	-0.296493
52	488.5	489.462	489.433	0.0289931	-0.962326
53	492	493.152	492.846	0.306493	-1.15233
54	494.8	496.3	496.425	-0.125174	-1.49983
55	498.3	499.601	500.188	-0.586007	-1.30149
56	502.1	503.477	504.108	-0.631146	-1.37719
57	505.8	507.776	508.146	-0.370035	-1.9758
58	511.7	512.993	512.271	0.722326	-1.29316
59	516.6	517.303	516.542	0.761215	-0.702882
60	521.3	521.667	520.937	0.729271	-0.366771
61	526.1	525.522	525.354	0.167465	0.578368
62	530.4	529.046	529.742	-0.695729	1.35406
63	534.7	533.763	534.071	-0.307674	0.93684
64	538.4	538.296	538.267	0.0289931	0.10434
65	544.6	542.581	542.275	0.306493	2.01851
66	547.7	545.987	546.112	-0.125174	1.71267
67	551.4	549.11	549.696	-0.586007	2.29017
68	554.3	552.398	553.029	-0.631146	1.90198
69	557.5	555.788	556.158	-0.370035	1.7117
70	560.7	559.831	559.108	0.722326	0.86934
71	563.8	562.582	561.821	0.761215	1.21795
72	566.2	565.088	564.358	0.729271	1.1124
73	567.2	567.026	566.858	0.167465	0.174201
74	569.3	568.65	569.346	-0.695729	0.649896
75	570.9	NA	NA	-0.307674	NA
76	573	NA	NA	0.0289931	NA
77	575.1	NA	NA	0.306493	NA
78	578.1	NA	NA	-0.125174	NA
79	581	NA	NA	-0.586007	NA
80	584.4	NA	NA	-0.631146	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