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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 28 Nov 2016 20:53:34 +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/2016/Nov/28/t1480366441fq2cky2qywbyfl0.htm/, Retrieved Sat, 04 May 2024 11:56:10 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sat, 04 May 2024 11:56:10 +0200

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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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	89.8	NA	NA	1.01604	NA
2	101.7	NA	NA	1.03556	NA
3	92.7	NA	NA	0.89593	NA
4	116.2	NA	NA	0.92122	NA
5	134.2	NA	NA	1.00213	NA
6	153.3	NA	NA	1.06034	NA
7	129.7	136.448	144.167	0.946461	0.950544
8	137.6	147.652	154.35	0.956603	0.931923
9	158.8	174.991	163.063	1.07315	0.907475
10	197.1	190.859	170.588	1.11883	1.0327
11	171.1	178.982	177.742	1.00698	0.955964
12	184.4	177.823	183.937	0.966757	1.03699
13	216.6	191.48	188.458	1.01604	1.13119
14	219.3	198.185	191.379	1.03556	1.10654
15	184.2	173.247	193.371	0.89593	1.06322
16	205.3	177.6	192.788	0.92122	1.15597
17	216.8	189.481	189.079	1.00213	1.14418
18	219.4	195.298	184.183	1.06034	1.12341
19	172.1	168.206	177.721	0.946461	1.02315
20	165.3	162.591	169.967	0.956603	1.01666
21	178.9	173.636	161.8	1.07315	1.03032
22	163	171.102	152.929	1.11883	0.952646
23	116.2	145.361	144.354	1.00698	0.799388
24	121.8	132.369	136.921	0.966757	0.920154
25	124.1	132.952	130.854	1.01604	0.933416
26	125.7	130.886	126.392	1.03556	0.960375
27	81.8	110.647	123.5	0.89593	0.739285
28	94.8	112.489	122.108	0.92122	0.842752
29	121.5	123.558	123.296	1.00213	0.983344
30	136.3	133.943	126.321	1.06034	1.01759
31	109.6	123.639	130.633	0.946461	0.886449
32	120.7	131.553	137.521	0.956603	0.917502
33	154.1	158.138	147.358	1.07315	0.974465
34	154.4	177.256	158.429	1.11883	0.871057
35	153.3	169.797	168.621	1.00698	0.902842
36	157.3	172.385	178.312	0.966757	0.912493
37	192.1	191.485	188.463	1.01604	1.00321
38	223	205.891	198.821	1.03556	1.0831
39	220.6	186.197	207.825	0.89593	1.18477
40	221.7	199.072	216.096	0.92122	1.11367
41	239.2	224.414	223.938	1.00213	1.06589
42	251.2	242.686	228.875	1.06034	1.03508
43	238.3	216.479	228.725	0.946461	1.1008
44	240.6	213.984	223.692	0.956603	1.12438
45	250.3	231.984	216.171	1.07315	1.07895
46	256.7	232.62	207.913	1.11883	1.10352
47	239.2	199.902	198.517	1.00698	1.19659
48	189.9	181.867	188.121	0.966757	1.04417
49	155.9	180.926	178.071	1.01604	0.861677
50	138.4	174.432	168.442	1.03556	0.793434
51	124.7	142.289	158.817	0.89593	0.876387
52	119.4	137.557	149.321	0.92122	0.868002
53	116	140.381	140.083	1.00213	0.826322
54	124.9	140.5	132.504	1.06034	0.888968
55	123.4	121.033	127.879	0.946461	1.01956
56	124.4	119.938	125.379	0.956603	1.0372
57	135.5	132.718	123.671	1.07315	1.02096
58	143.6	136.353	121.871	1.11883	1.05315
59	130.6	120.9	120.062	1.00698	1.08023
60	116.6	114.178	118.104	0.966757	1.02121
61	118.2	117.551	115.696	1.01604	1.00552
62	116.1	117.087	113.067	1.03556	0.991566
63	106	98.9406	110.433	0.89593	1.07135
64	94.9	99.4111	107.912	0.92122	0.954621
65	97.1	106.088	105.862	1.00213	0.915282
66	96.8	111.27	104.937	1.06034	0.869958
67	93.7	99.5204	105.15	0.946461	0.941516
68	91	101.751	106.367	0.956603	0.894343
69	105.7	116.173	108.254	1.07315	0.909848
70	112.9	124.209	111.017	1.11883	0.90895
71	112.1	NA	NA	1.00698	NA
72	112.9	NA	NA	0.966757	NA
73	127	NA	NA	1.01604	NA
74	136.5	NA	NA	1.03556	NA
75	130.9	NA	NA	0.89593	NA
76	136.3	NA	NA	0.92122	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 89.8 & NA & NA & 1.01604 & NA \tabularnewline
2 & 101.7 & NA & NA & 1.03556 & NA \tabularnewline
3 & 92.7 & NA & NA & 0.89593 & NA \tabularnewline
4 & 116.2 & NA & NA & 0.92122 & NA \tabularnewline
5 & 134.2 & NA & NA & 1.00213 & NA \tabularnewline
6 & 153.3 & NA & NA & 1.06034 & NA \tabularnewline
7 & 129.7 & 136.448 & 144.167 & 0.946461 & 0.950544 \tabularnewline
8 & 137.6 & 147.652 & 154.35 & 0.956603 & 0.931923 \tabularnewline
9 & 158.8 & 174.991 & 163.063 & 1.07315 & 0.907475 \tabularnewline
10 & 197.1 & 190.859 & 170.588 & 1.11883 & 1.0327 \tabularnewline
11 & 171.1 & 178.982 & 177.742 & 1.00698 & 0.955964 \tabularnewline
12 & 184.4 & 177.823 & 183.937 & 0.966757 & 1.03699 \tabularnewline
13 & 216.6 & 191.48 & 188.458 & 1.01604 & 1.13119 \tabularnewline
14 & 219.3 & 198.185 & 191.379 & 1.03556 & 1.10654 \tabularnewline
15 & 184.2 & 173.247 & 193.371 & 0.89593 & 1.06322 \tabularnewline
16 & 205.3 & 177.6 & 192.788 & 0.92122 & 1.15597 \tabularnewline
17 & 216.8 & 189.481 & 189.079 & 1.00213 & 1.14418 \tabularnewline
18 & 219.4 & 195.298 & 184.183 & 1.06034 & 1.12341 \tabularnewline
19 & 172.1 & 168.206 & 177.721 & 0.946461 & 1.02315 \tabularnewline
20 & 165.3 & 162.591 & 169.967 & 0.956603 & 1.01666 \tabularnewline
21 & 178.9 & 173.636 & 161.8 & 1.07315 & 1.03032 \tabularnewline
22 & 163 & 171.102 & 152.929 & 1.11883 & 0.952646 \tabularnewline
23 & 116.2 & 145.361 & 144.354 & 1.00698 & 0.799388 \tabularnewline
24 & 121.8 & 132.369 & 136.921 & 0.966757 & 0.920154 \tabularnewline
25 & 124.1 & 132.952 & 130.854 & 1.01604 & 0.933416 \tabularnewline
26 & 125.7 & 130.886 & 126.392 & 1.03556 & 0.960375 \tabularnewline
27 & 81.8 & 110.647 & 123.5 & 0.89593 & 0.739285 \tabularnewline
28 & 94.8 & 112.489 & 122.108 & 0.92122 & 0.842752 \tabularnewline
29 & 121.5 & 123.558 & 123.296 & 1.00213 & 0.983344 \tabularnewline
30 & 136.3 & 133.943 & 126.321 & 1.06034 & 1.01759 \tabularnewline
31 & 109.6 & 123.639 & 130.633 & 0.946461 & 0.886449 \tabularnewline
32 & 120.7 & 131.553 & 137.521 & 0.956603 & 0.917502 \tabularnewline
33 & 154.1 & 158.138 & 147.358 & 1.07315 & 0.974465 \tabularnewline
34 & 154.4 & 177.256 & 158.429 & 1.11883 & 0.871057 \tabularnewline
35 & 153.3 & 169.797 & 168.621 & 1.00698 & 0.902842 \tabularnewline
36 & 157.3 & 172.385 & 178.312 & 0.966757 & 0.912493 \tabularnewline
37 & 192.1 & 191.485 & 188.463 & 1.01604 & 1.00321 \tabularnewline
38 & 223 & 205.891 & 198.821 & 1.03556 & 1.0831 \tabularnewline
39 & 220.6 & 186.197 & 207.825 & 0.89593 & 1.18477 \tabularnewline
40 & 221.7 & 199.072 & 216.096 & 0.92122 & 1.11367 \tabularnewline
41 & 239.2 & 224.414 & 223.938 & 1.00213 & 1.06589 \tabularnewline
42 & 251.2 & 242.686 & 228.875 & 1.06034 & 1.03508 \tabularnewline
43 & 238.3 & 216.479 & 228.725 & 0.946461 & 1.1008 \tabularnewline
44 & 240.6 & 213.984 & 223.692 & 0.956603 & 1.12438 \tabularnewline
45 & 250.3 & 231.984 & 216.171 & 1.07315 & 1.07895 \tabularnewline
46 & 256.7 & 232.62 & 207.913 & 1.11883 & 1.10352 \tabularnewline
47 & 239.2 & 199.902 & 198.517 & 1.00698 & 1.19659 \tabularnewline
48 & 189.9 & 181.867 & 188.121 & 0.966757 & 1.04417 \tabularnewline
49 & 155.9 & 180.926 & 178.071 & 1.01604 & 0.861677 \tabularnewline
50 & 138.4 & 174.432 & 168.442 & 1.03556 & 0.793434 \tabularnewline
51 & 124.7 & 142.289 & 158.817 & 0.89593 & 0.876387 \tabularnewline
52 & 119.4 & 137.557 & 149.321 & 0.92122 & 0.868002 \tabularnewline
53 & 116 & 140.381 & 140.083 & 1.00213 & 0.826322 \tabularnewline
54 & 124.9 & 140.5 & 132.504 & 1.06034 & 0.888968 \tabularnewline
55 & 123.4 & 121.033 & 127.879 & 0.946461 & 1.01956 \tabularnewline
56 & 124.4 & 119.938 & 125.379 & 0.956603 & 1.0372 \tabularnewline
57 & 135.5 & 132.718 & 123.671 & 1.07315 & 1.02096 \tabularnewline
58 & 143.6 & 136.353 & 121.871 & 1.11883 & 1.05315 \tabularnewline
59 & 130.6 & 120.9 & 120.062 & 1.00698 & 1.08023 \tabularnewline
60 & 116.6 & 114.178 & 118.104 & 0.966757 & 1.02121 \tabularnewline
61 & 118.2 & 117.551 & 115.696 & 1.01604 & 1.00552 \tabularnewline
62 & 116.1 & 117.087 & 113.067 & 1.03556 & 0.991566 \tabularnewline
63 & 106 & 98.9406 & 110.433 & 0.89593 & 1.07135 \tabularnewline
64 & 94.9 & 99.4111 & 107.912 & 0.92122 & 0.954621 \tabularnewline
65 & 97.1 & 106.088 & 105.862 & 1.00213 & 0.915282 \tabularnewline
66 & 96.8 & 111.27 & 104.937 & 1.06034 & 0.869958 \tabularnewline
67 & 93.7 & 99.5204 & 105.15 & 0.946461 & 0.941516 \tabularnewline
68 & 91 & 101.751 & 106.367 & 0.956603 & 0.894343 \tabularnewline
69 & 105.7 & 116.173 & 108.254 & 1.07315 & 0.909848 \tabularnewline
70 & 112.9 & 124.209 & 111.017 & 1.11883 & 0.90895 \tabularnewline
71 & 112.1 & NA & NA & 1.00698 & NA \tabularnewline
72 & 112.9 & NA & NA & 0.966757 & NA \tabularnewline
73 & 127 & NA & NA & 1.01604 & NA \tabularnewline
74 & 136.5 & NA & NA & 1.03556 & NA \tabularnewline
75 & 130.9 & NA & NA & 0.89593 & NA \tabularnewline
76 & 136.3 & NA & NA & 0.92122 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]89.8[/C][C]NA[/C][C]NA[/C][C]1.01604[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]101.7[/C][C]NA[/C][C]NA[/C][C]1.03556[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]92.7[/C][C]NA[/C][C]NA[/C][C]0.89593[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]116.2[/C][C]NA[/C][C]NA[/C][C]0.92122[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]134.2[/C][C]NA[/C][C]NA[/C][C]1.00213[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]153.3[/C][C]NA[/C][C]NA[/C][C]1.06034[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]129.7[/C][C]136.448[/C][C]144.167[/C][C]0.946461[/C][C]0.950544[/C][/ROW]
[ROW][C]8[/C][C]137.6[/C][C]147.652[/C][C]154.35[/C][C]0.956603[/C][C]0.931923[/C][/ROW]
[ROW][C]9[/C][C]158.8[/C][C]174.991[/C][C]163.063[/C][C]1.07315[/C][C]0.907475[/C][/ROW]
[ROW][C]10[/C][C]197.1[/C][C]190.859[/C][C]170.588[/C][C]1.11883[/C][C]1.0327[/C][/ROW]
[ROW][C]11[/C][C]171.1[/C][C]178.982[/C][C]177.742[/C][C]1.00698[/C][C]0.955964[/C][/ROW]
[ROW][C]12[/C][C]184.4[/C][C]177.823[/C][C]183.937[/C][C]0.966757[/C][C]1.03699[/C][/ROW]
[ROW][C]13[/C][C]216.6[/C][C]191.48[/C][C]188.458[/C][C]1.01604[/C][C]1.13119[/C][/ROW]
[ROW][C]14[/C][C]219.3[/C][C]198.185[/C][C]191.379[/C][C]1.03556[/C][C]1.10654[/C][/ROW]
[ROW][C]15[/C][C]184.2[/C][C]173.247[/C][C]193.371[/C][C]0.89593[/C][C]1.06322[/C][/ROW]
[ROW][C]16[/C][C]205.3[/C][C]177.6[/C][C]192.788[/C][C]0.92122[/C][C]1.15597[/C][/ROW]
[ROW][C]17[/C][C]216.8[/C][C]189.481[/C][C]189.079[/C][C]1.00213[/C][C]1.14418[/C][/ROW]
[ROW][C]18[/C][C]219.4[/C][C]195.298[/C][C]184.183[/C][C]1.06034[/C][C]1.12341[/C][/ROW]
[ROW][C]19[/C][C]172.1[/C][C]168.206[/C][C]177.721[/C][C]0.946461[/C][C]1.02315[/C][/ROW]
[ROW][C]20[/C][C]165.3[/C][C]162.591[/C][C]169.967[/C][C]0.956603[/C][C]1.01666[/C][/ROW]
[ROW][C]21[/C][C]178.9[/C][C]173.636[/C][C]161.8[/C][C]1.07315[/C][C]1.03032[/C][/ROW]
[ROW][C]22[/C][C]163[/C][C]171.102[/C][C]152.929[/C][C]1.11883[/C][C]0.952646[/C][/ROW]
[ROW][C]23[/C][C]116.2[/C][C]145.361[/C][C]144.354[/C][C]1.00698[/C][C]0.799388[/C][/ROW]
[ROW][C]24[/C][C]121.8[/C][C]132.369[/C][C]136.921[/C][C]0.966757[/C][C]0.920154[/C][/ROW]
[ROW][C]25[/C][C]124.1[/C][C]132.952[/C][C]130.854[/C][C]1.01604[/C][C]0.933416[/C][/ROW]
[ROW][C]26[/C][C]125.7[/C][C]130.886[/C][C]126.392[/C][C]1.03556[/C][C]0.960375[/C][/ROW]
[ROW][C]27[/C][C]81.8[/C][C]110.647[/C][C]123.5[/C][C]0.89593[/C][C]0.739285[/C][/ROW]
[ROW][C]28[/C][C]94.8[/C][C]112.489[/C][C]122.108[/C][C]0.92122[/C][C]0.842752[/C][/ROW]
[ROW][C]29[/C][C]121.5[/C][C]123.558[/C][C]123.296[/C][C]1.00213[/C][C]0.983344[/C][/ROW]
[ROW][C]30[/C][C]136.3[/C][C]133.943[/C][C]126.321[/C][C]1.06034[/C][C]1.01759[/C][/ROW]
[ROW][C]31[/C][C]109.6[/C][C]123.639[/C][C]130.633[/C][C]0.946461[/C][C]0.886449[/C][/ROW]
[ROW][C]32[/C][C]120.7[/C][C]131.553[/C][C]137.521[/C][C]0.956603[/C][C]0.917502[/C][/ROW]
[ROW][C]33[/C][C]154.1[/C][C]158.138[/C][C]147.358[/C][C]1.07315[/C][C]0.974465[/C][/ROW]
[ROW][C]34[/C][C]154.4[/C][C]177.256[/C][C]158.429[/C][C]1.11883[/C][C]0.871057[/C][/ROW]
[ROW][C]35[/C][C]153.3[/C][C]169.797[/C][C]168.621[/C][C]1.00698[/C][C]0.902842[/C][/ROW]
[ROW][C]36[/C][C]157.3[/C][C]172.385[/C][C]178.312[/C][C]0.966757[/C][C]0.912493[/C][/ROW]
[ROW][C]37[/C][C]192.1[/C][C]191.485[/C][C]188.463[/C][C]1.01604[/C][C]1.00321[/C][/ROW]
[ROW][C]38[/C][C]223[/C][C]205.891[/C][C]198.821[/C][C]1.03556[/C][C]1.0831[/C][/ROW]
[ROW][C]39[/C][C]220.6[/C][C]186.197[/C][C]207.825[/C][C]0.89593[/C][C]1.18477[/C][/ROW]
[ROW][C]40[/C][C]221.7[/C][C]199.072[/C][C]216.096[/C][C]0.92122[/C][C]1.11367[/C][/ROW]
[ROW][C]41[/C][C]239.2[/C][C]224.414[/C][C]223.938[/C][C]1.00213[/C][C]1.06589[/C][/ROW]
[ROW][C]42[/C][C]251.2[/C][C]242.686[/C][C]228.875[/C][C]1.06034[/C][C]1.03508[/C][/ROW]
[ROW][C]43[/C][C]238.3[/C][C]216.479[/C][C]228.725[/C][C]0.946461[/C][C]1.1008[/C][/ROW]
[ROW][C]44[/C][C]240.6[/C][C]213.984[/C][C]223.692[/C][C]0.956603[/C][C]1.12438[/C][/ROW]
[ROW][C]45[/C][C]250.3[/C][C]231.984[/C][C]216.171[/C][C]1.07315[/C][C]1.07895[/C][/ROW]
[ROW][C]46[/C][C]256.7[/C][C]232.62[/C][C]207.913[/C][C]1.11883[/C][C]1.10352[/C][/ROW]
[ROW][C]47[/C][C]239.2[/C][C]199.902[/C][C]198.517[/C][C]1.00698[/C][C]1.19659[/C][/ROW]
[ROW][C]48[/C][C]189.9[/C][C]181.867[/C][C]188.121[/C][C]0.966757[/C][C]1.04417[/C][/ROW]
[ROW][C]49[/C][C]155.9[/C][C]180.926[/C][C]178.071[/C][C]1.01604[/C][C]0.861677[/C][/ROW]
[ROW][C]50[/C][C]138.4[/C][C]174.432[/C][C]168.442[/C][C]1.03556[/C][C]0.793434[/C][/ROW]
[ROW][C]51[/C][C]124.7[/C][C]142.289[/C][C]158.817[/C][C]0.89593[/C][C]0.876387[/C][/ROW]
[ROW][C]52[/C][C]119.4[/C][C]137.557[/C][C]149.321[/C][C]0.92122[/C][C]0.868002[/C][/ROW]
[ROW][C]53[/C][C]116[/C][C]140.381[/C][C]140.083[/C][C]1.00213[/C][C]0.826322[/C][/ROW]
[ROW][C]54[/C][C]124.9[/C][C]140.5[/C][C]132.504[/C][C]1.06034[/C][C]0.888968[/C][/ROW]
[ROW][C]55[/C][C]123.4[/C][C]121.033[/C][C]127.879[/C][C]0.946461[/C][C]1.01956[/C][/ROW]
[ROW][C]56[/C][C]124.4[/C][C]119.938[/C][C]125.379[/C][C]0.956603[/C][C]1.0372[/C][/ROW]
[ROW][C]57[/C][C]135.5[/C][C]132.718[/C][C]123.671[/C][C]1.07315[/C][C]1.02096[/C][/ROW]
[ROW][C]58[/C][C]143.6[/C][C]136.353[/C][C]121.871[/C][C]1.11883[/C][C]1.05315[/C][/ROW]
[ROW][C]59[/C][C]130.6[/C][C]120.9[/C][C]120.062[/C][C]1.00698[/C][C]1.08023[/C][/ROW]
[ROW][C]60[/C][C]116.6[/C][C]114.178[/C][C]118.104[/C][C]0.966757[/C][C]1.02121[/C][/ROW]
[ROW][C]61[/C][C]118.2[/C][C]117.551[/C][C]115.696[/C][C]1.01604[/C][C]1.00552[/C][/ROW]
[ROW][C]62[/C][C]116.1[/C][C]117.087[/C][C]113.067[/C][C]1.03556[/C][C]0.991566[/C][/ROW]
[ROW][C]63[/C][C]106[/C][C]98.9406[/C][C]110.433[/C][C]0.89593[/C][C]1.07135[/C][/ROW]
[ROW][C]64[/C][C]94.9[/C][C]99.4111[/C][C]107.912[/C][C]0.92122[/C][C]0.954621[/C][/ROW]
[ROW][C]65[/C][C]97.1[/C][C]106.088[/C][C]105.862[/C][C]1.00213[/C][C]0.915282[/C][/ROW]
[ROW][C]66[/C][C]96.8[/C][C]111.27[/C][C]104.937[/C][C]1.06034[/C][C]0.869958[/C][/ROW]
[ROW][C]67[/C][C]93.7[/C][C]99.5204[/C][C]105.15[/C][C]0.946461[/C][C]0.941516[/C][/ROW]
[ROW][C]68[/C][C]91[/C][C]101.751[/C][C]106.367[/C][C]0.956603[/C][C]0.894343[/C][/ROW]
[ROW][C]69[/C][C]105.7[/C][C]116.173[/C][C]108.254[/C][C]1.07315[/C][C]0.909848[/C][/ROW]
[ROW][C]70[/C][C]112.9[/C][C]124.209[/C][C]111.017[/C][C]1.11883[/C][C]0.90895[/C][/ROW]
[ROW][C]71[/C][C]112.1[/C][C]NA[/C][C]NA[/C][C]1.00698[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]112.9[/C][C]NA[/C][C]NA[/C][C]0.966757[/C][C]NA[/C][/ROW]
[ROW][C]73[/C][C]127[/C][C]NA[/C][C]NA[/C][C]1.01604[/C][C]NA[/C][/ROW]
[ROW][C]74[/C][C]136.5[/C][C]NA[/C][C]NA[/C][C]1.03556[/C][C]NA[/C][/ROW]
[ROW][C]75[/C][C]130.9[/C][C]NA[/C][C]NA[/C][C]0.89593[/C][C]NA[/C][/ROW]
[ROW][C]76[/C][C]136.3[/C][C]NA[/C][C]NA[/C][C]0.92122[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	89.8	NA	NA	1.01604	NA
2	101.7	NA	NA	1.03556	NA
3	92.7	NA	NA	0.89593	NA
4	116.2	NA	NA	0.92122	NA
5	134.2	NA	NA	1.00213	NA
6	153.3	NA	NA	1.06034	NA
7	129.7	136.448	144.167	0.946461	0.950544
8	137.6	147.652	154.35	0.956603	0.931923
9	158.8	174.991	163.063	1.07315	0.907475
10	197.1	190.859	170.588	1.11883	1.0327
11	171.1	178.982	177.742	1.00698	0.955964
12	184.4	177.823	183.937	0.966757	1.03699
13	216.6	191.48	188.458	1.01604	1.13119
14	219.3	198.185	191.379	1.03556	1.10654
15	184.2	173.247	193.371	0.89593	1.06322
16	205.3	177.6	192.788	0.92122	1.15597
17	216.8	189.481	189.079	1.00213	1.14418
18	219.4	195.298	184.183	1.06034	1.12341
19	172.1	168.206	177.721	0.946461	1.02315
20	165.3	162.591	169.967	0.956603	1.01666
21	178.9	173.636	161.8	1.07315	1.03032
22	163	171.102	152.929	1.11883	0.952646
23	116.2	145.361	144.354	1.00698	0.799388
24	121.8	132.369	136.921	0.966757	0.920154
25	124.1	132.952	130.854	1.01604	0.933416
26	125.7	130.886	126.392	1.03556	0.960375
27	81.8	110.647	123.5	0.89593	0.739285
28	94.8	112.489	122.108	0.92122	0.842752
29	121.5	123.558	123.296	1.00213	0.983344
30	136.3	133.943	126.321	1.06034	1.01759
31	109.6	123.639	130.633	0.946461	0.886449
32	120.7	131.553	137.521	0.956603	0.917502
33	154.1	158.138	147.358	1.07315	0.974465
34	154.4	177.256	158.429	1.11883	0.871057
35	153.3	169.797	168.621	1.00698	0.902842
36	157.3	172.385	178.312	0.966757	0.912493
37	192.1	191.485	188.463	1.01604	1.00321
38	223	205.891	198.821	1.03556	1.0831
39	220.6	186.197	207.825	0.89593	1.18477
40	221.7	199.072	216.096	0.92122	1.11367
41	239.2	224.414	223.938	1.00213	1.06589
42	251.2	242.686	228.875	1.06034	1.03508
43	238.3	216.479	228.725	0.946461	1.1008
44	240.6	213.984	223.692	0.956603	1.12438
45	250.3	231.984	216.171	1.07315	1.07895
46	256.7	232.62	207.913	1.11883	1.10352
47	239.2	199.902	198.517	1.00698	1.19659
48	189.9	181.867	188.121	0.966757	1.04417
49	155.9	180.926	178.071	1.01604	0.861677
50	138.4	174.432	168.442	1.03556	0.793434
51	124.7	142.289	158.817	0.89593	0.876387
52	119.4	137.557	149.321	0.92122	0.868002
53	116	140.381	140.083	1.00213	0.826322
54	124.9	140.5	132.504	1.06034	0.888968
55	123.4	121.033	127.879	0.946461	1.01956
56	124.4	119.938	125.379	0.956603	1.0372
57	135.5	132.718	123.671	1.07315	1.02096
58	143.6	136.353	121.871	1.11883	1.05315
59	130.6	120.9	120.062	1.00698	1.08023
60	116.6	114.178	118.104	0.966757	1.02121
61	118.2	117.551	115.696	1.01604	1.00552
62	116.1	117.087	113.067	1.03556	0.991566
63	106	98.9406	110.433	0.89593	1.07135
64	94.9	99.4111	107.912	0.92122	0.954621
65	97.1	106.088	105.862	1.00213	0.915282
66	96.8	111.27	104.937	1.06034	0.869958
67	93.7	99.5204	105.15	0.946461	0.941516
68	91	101.751	106.367	0.956603	0.894343
69	105.7	116.173	108.254	1.07315	0.909848
70	112.9	124.209	111.017	1.11883	0.90895
71	112.1	NA	NA	1.00698	NA
72	112.9	NA	NA	0.966757	NA
73	127	NA	NA	1.01604	NA
74	136.5	NA	NA	1.03556	NA
75	130.9	NA	NA	0.89593	NA
76	136.3	NA	NA	0.92122	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