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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 16 Dec 2017 18:26:21 +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/2017/Dec/16/t1513445338vdxkvmaezq4ia83.htm/, Retrieved Wed, 15 May 2024 21:11:41 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309928, Retrieved Wed, 15 May 2024 21:11:41 +0000

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-       [Classical Decomposition] [Classical Decompo...] [2017-12-16 17:26:21] [86c18850f013301d73767c2d74663798] [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	3 seconds
R Server	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309928&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

3 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=309928&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309928&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	3 seconds
R Server	Big Analytics Cloud Computing Center

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	101.5	NA	NA	-10.9647	NA
2	110.4	NA	NA	-6.26192	NA
3	107.3	NA	NA	8.64277	NA
4	107.7	NA	NA	-7.2916	NA
5	98.3	NA	NA	-5.07337	NA
6	130.3	NA	NA	8.06985	NA
7	89.1	87.4432	104.262	-16.8193	1.65682
8	100.4	90.6622	101.692	-11.0295	9.73784
9	121.1	109.499	99.5333	9.9654	11.6013
10	109.3	109.549	97.925	11.6237	-0.248732
11	87.4	98.5311	96.2542	2.27697	-11.1311
12	101.3	111.133	94.2708	16.8617	-9.83253
13	75.6	81.027	91.9917	-10.9647	-5.42697
14	74.6	84.1423	90.4042	-6.26192	-9.54225
15	91.3	97.8053	89.1625	8.64277	-6.50527
16	85.1	80.5084	87.8	-7.2916	4.5916
17	80.8	82.3433	87.4167	-5.07337	-1.54329
18	100.2	96.4949	88.425	8.06985	3.70515
19	64.5	72.4098	89.2292	-16.8193	-7.90984
20	86.9	78.7288	89.7583	-11.0295	8.17118
21	104.8	101.04	91.075	9.9654	3.7596
22	92.9	103.47	91.8458	11.6237	-10.5696
23	94.6	94.077	91.8	2.27697	0.523028
24	118.3	109.133	92.2708	16.8617	9.16747
25	77.9	82.6436	93.6083	-10.9647	-4.74364
26	85	88.5464	94.8083	-6.26192	-3.54642
27	112.5	104.143	95.5	8.64277	8.35723
28	82.4	89.7001	96.9917	-7.2916	-7.30006
29	82.4	93.7725	98.8458	-5.07337	-11.3725
30	109.9	107.887	99.8167	8.06985	2.01348
31	86.9	84.1973	101.017	-16.8193	2.70266
32	93.3	91.5538	102.583	-11.0295	1.74618
33	115	113.29	103.325	9.9654	1.7096
34	118.5	115.115	103.492	11.6237	3.3846
35	113.5	106.706	104.429	2.27697	6.79386
36	122.7	121.558	104.696	16.8617	1.14247
37	102.3	92.6978	103.663	-10.9647	9.60219
38	98.2	96.8089	103.071	-6.26192	1.39108
39	117.1	111.314	102.671	8.64277	5.7864
40	81.8	94.8709	102.162	-7.2916	-13.0709
41	105.5	96.1933	101.267	-5.07337	9.30671
42	93.2	108.199	100.129	8.06985	-14.999
43	78.8	81.9348	98.7542	-16.8193	-3.13484
44	87.2	86.6955	97.725	-11.0295	0.504509
45	111.5	107.632	97.6667	9.9654	3.86793
46	109.8	109.67	98.0458	11.6237	0.130435
47	100.7	100.214	97.9375	2.27697	0.485528
48	108.2	115.653	98.7917	16.8617	-7.45336
49	83.8	89.3603	100.325	-10.9647	-5.56031
50	92	94.1631	100.425	-6.26192	-2.16308
51	121.9	108.084	99.4417	8.64277	13.8156
52	86.1	91.5417	98.8333	-7.2916	-5.44173
53	98.6	93.7516	98.825	-5.07337	4.84837
54	120.6	106.653	98.5833	8.06985	13.9468
55	88.2	81.5432	98.3625	-16.8193	6.65682
56	80.2	87.0747	98.1042	-11.0295	-6.87466
57	94.9	106.89	96.925	9.9654	-11.9904
58	111.8	107.628	96.0042	11.6237	4.1721
59	98.5	97.8686	95.5917	2.27697	0.631361
60	104.6	111.133	94.2708	16.8617	-6.53253
61	82.1	82.052	93.0167	-10.9647	0.0480276
62	87.5	85.9673	92.2292	-6.26192	1.53275
63	98.1	100.334	91.6917	8.64277	-2.23444
64	87.8	84.0959	91.3875	-7.2916	3.7041
65	87	85.7558	90.8292	-5.07337	1.24421
66	100.5	98.8449	90.775	8.06985	1.65515
67	78.2	74.414	91.2333	-16.8193	3.78599
68	71.3	80.1747	91.2042	-11.0295	-8.87466
69	90.9	100.795	90.8292	9.9654	-9.89457
70	108.5	102.157	90.5333	11.6237	6.34293
71	88.4	92.802	90.525	2.27697	-4.40197
72	113.4	107.02	90.1583	16.8617	6.37997
73	84.3	78.9811	89.9458	-10.9647	5.31886
74	84.6	84.2423	90.5042	-6.26192	0.35775
75	92	99.9136	91.2708	8.64277	-7.9136
76	86.8	84.2292	91.5208	-7.2916	2.57077
77	87.8	86.4891	91.5625	-5.07337	1.31087
78	90.9	100.045	91.975	8.06985	-9.14485
79	82.7	74.964	91.7833	-16.8193	7.73599
80	80.2	80.2247	91.2542	-11.0295	-0.0246576
81	100.4	101.303	91.3375	9.9654	-0.902898
82	105	103.136	91.5125	11.6237	1.86377
83	92.9	93.4603	91.1833	2.27697	-0.560306
84	118.8	108.116	91.2542	16.8617	10.6841
85	74.3	79.9811	90.9458	-10.9647	-5.68114
86	81.9	83.7089	89.9708	-6.26192	-1.80892
87	96.7	98.7636	90.1208	8.64277	-2.0636
88	86.3	83.2292	90.5208	-7.2916	3.07077
89	80.4	85.7225	90.7958	-5.07337	-5.32246
90	100	98.8407	90.7708	8.06985	1.15931
91	66.2	74.0723	90.8917	-16.8193	-7.87234
92	73.3	80.9455	91.975	-11.0295	-7.64549
93	110.9	102.449	92.4833	9.9654	8.45127
94	104.1	104.495	92.8708	11.6237	-0.394565
95	100.4	96.0561	93.7792	2.27697	4.34386
96	110.7	111.178	94.3167	16.8617	-0.478361
97	85.3	83.7645	94.7292	-10.9647	1.53553
98	96.9	89.2589	95.5208	-6.26192	7.64108
99	93.9	104.114	95.4708	8.64277	-10.2136
100	98.4	87.4959	94.7875	-7.2916	10.9041
101	90.1	89.5433	94.6167	-5.07337	0.556708
102	103.2	102.507	94.4375	8.06985	0.692646
103	72.9	77.614	94.4333	-16.8193	-4.71401
104	85.6	83.433	94.4625	-11.0295	2.16701
105	97.4	105.095	95.1292	9.9654	-7.69457
106	101.2	106.974	95.35	11.6237	-5.77373
107	99.2	96.977	94.7	2.27697	2.22303
108	107.6	111.77	94.9083	16.8617	-4.17003
109	88.3	84.4853	95.45	-10.9647	3.81469
110	94.6	89.5548	95.8167	-6.26192	5.04525
111	112.2	NA	NA	8.64277	NA
112	85.4	NA	NA	-7.2916	NA
113	87.5	NA	NA	-5.07337	NA
114	110.8	NA	NA	8.06985	NA
115	78.3	NA	NA	-16.8193	NA
116	89	NA	NA	-11.0295	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.5 & NA & NA & -10.9647 & NA \tabularnewline
2 & 110.4 & NA & NA & -6.26192 & NA \tabularnewline
3 & 107.3 & NA & NA & 8.64277 & NA \tabularnewline
4 & 107.7 & NA & NA & -7.2916 & NA \tabularnewline
5 & 98.3 & NA & NA & -5.07337 & NA \tabularnewline
6 & 130.3 & NA & NA & 8.06985 & NA \tabularnewline
7 & 89.1 & 87.4432 & 104.262 & -16.8193 & 1.65682 \tabularnewline
8 & 100.4 & 90.6622 & 101.692 & -11.0295 & 9.73784 \tabularnewline
9 & 121.1 & 109.499 & 99.5333 & 9.9654 & 11.6013 \tabularnewline
10 & 109.3 & 109.549 & 97.925 & 11.6237 & -0.248732 \tabularnewline
11 & 87.4 & 98.5311 & 96.2542 & 2.27697 & -11.1311 \tabularnewline
12 & 101.3 & 111.133 & 94.2708 & 16.8617 & -9.83253 \tabularnewline
13 & 75.6 & 81.027 & 91.9917 & -10.9647 & -5.42697 \tabularnewline
14 & 74.6 & 84.1423 & 90.4042 & -6.26192 & -9.54225 \tabularnewline
15 & 91.3 & 97.8053 & 89.1625 & 8.64277 & -6.50527 \tabularnewline
16 & 85.1 & 80.5084 & 87.8 & -7.2916 & 4.5916 \tabularnewline
17 & 80.8 & 82.3433 & 87.4167 & -5.07337 & -1.54329 \tabularnewline
18 & 100.2 & 96.4949 & 88.425 & 8.06985 & 3.70515 \tabularnewline
19 & 64.5 & 72.4098 & 89.2292 & -16.8193 & -7.90984 \tabularnewline
20 & 86.9 & 78.7288 & 89.7583 & -11.0295 & 8.17118 \tabularnewline
21 & 104.8 & 101.04 & 91.075 & 9.9654 & 3.7596 \tabularnewline
22 & 92.9 & 103.47 & 91.8458 & 11.6237 & -10.5696 \tabularnewline
23 & 94.6 & 94.077 & 91.8 & 2.27697 & 0.523028 \tabularnewline
24 & 118.3 & 109.133 & 92.2708 & 16.8617 & 9.16747 \tabularnewline
25 & 77.9 & 82.6436 & 93.6083 & -10.9647 & -4.74364 \tabularnewline
26 & 85 & 88.5464 & 94.8083 & -6.26192 & -3.54642 \tabularnewline
27 & 112.5 & 104.143 & 95.5 & 8.64277 & 8.35723 \tabularnewline
28 & 82.4 & 89.7001 & 96.9917 & -7.2916 & -7.30006 \tabularnewline
29 & 82.4 & 93.7725 & 98.8458 & -5.07337 & -11.3725 \tabularnewline
30 & 109.9 & 107.887 & 99.8167 & 8.06985 & 2.01348 \tabularnewline
31 & 86.9 & 84.1973 & 101.017 & -16.8193 & 2.70266 \tabularnewline
32 & 93.3 & 91.5538 & 102.583 & -11.0295 & 1.74618 \tabularnewline
33 & 115 & 113.29 & 103.325 & 9.9654 & 1.7096 \tabularnewline
34 & 118.5 & 115.115 & 103.492 & 11.6237 & 3.3846 \tabularnewline
35 & 113.5 & 106.706 & 104.429 & 2.27697 & 6.79386 \tabularnewline
36 & 122.7 & 121.558 & 104.696 & 16.8617 & 1.14247 \tabularnewline
37 & 102.3 & 92.6978 & 103.663 & -10.9647 & 9.60219 \tabularnewline
38 & 98.2 & 96.8089 & 103.071 & -6.26192 & 1.39108 \tabularnewline
39 & 117.1 & 111.314 & 102.671 & 8.64277 & 5.7864 \tabularnewline
40 & 81.8 & 94.8709 & 102.162 & -7.2916 & -13.0709 \tabularnewline
41 & 105.5 & 96.1933 & 101.267 & -5.07337 & 9.30671 \tabularnewline
42 & 93.2 & 108.199 & 100.129 & 8.06985 & -14.999 \tabularnewline
43 & 78.8 & 81.9348 & 98.7542 & -16.8193 & -3.13484 \tabularnewline
44 & 87.2 & 86.6955 & 97.725 & -11.0295 & 0.504509 \tabularnewline
45 & 111.5 & 107.632 & 97.6667 & 9.9654 & 3.86793 \tabularnewline
46 & 109.8 & 109.67 & 98.0458 & 11.6237 & 0.130435 \tabularnewline
47 & 100.7 & 100.214 & 97.9375 & 2.27697 & 0.485528 \tabularnewline
48 & 108.2 & 115.653 & 98.7917 & 16.8617 & -7.45336 \tabularnewline
49 & 83.8 & 89.3603 & 100.325 & -10.9647 & -5.56031 \tabularnewline
50 & 92 & 94.1631 & 100.425 & -6.26192 & -2.16308 \tabularnewline
51 & 121.9 & 108.084 & 99.4417 & 8.64277 & 13.8156 \tabularnewline
52 & 86.1 & 91.5417 & 98.8333 & -7.2916 & -5.44173 \tabularnewline
53 & 98.6 & 93.7516 & 98.825 & -5.07337 & 4.84837 \tabularnewline
54 & 120.6 & 106.653 & 98.5833 & 8.06985 & 13.9468 \tabularnewline
55 & 88.2 & 81.5432 & 98.3625 & -16.8193 & 6.65682 \tabularnewline
56 & 80.2 & 87.0747 & 98.1042 & -11.0295 & -6.87466 \tabularnewline
57 & 94.9 & 106.89 & 96.925 & 9.9654 & -11.9904 \tabularnewline
58 & 111.8 & 107.628 & 96.0042 & 11.6237 & 4.1721 \tabularnewline
59 & 98.5 & 97.8686 & 95.5917 & 2.27697 & 0.631361 \tabularnewline
60 & 104.6 & 111.133 & 94.2708 & 16.8617 & -6.53253 \tabularnewline
61 & 82.1 & 82.052 & 93.0167 & -10.9647 & 0.0480276 \tabularnewline
62 & 87.5 & 85.9673 & 92.2292 & -6.26192 & 1.53275 \tabularnewline
63 & 98.1 & 100.334 & 91.6917 & 8.64277 & -2.23444 \tabularnewline
64 & 87.8 & 84.0959 & 91.3875 & -7.2916 & 3.7041 \tabularnewline
65 & 87 & 85.7558 & 90.8292 & -5.07337 & 1.24421 \tabularnewline
66 & 100.5 & 98.8449 & 90.775 & 8.06985 & 1.65515 \tabularnewline
67 & 78.2 & 74.414 & 91.2333 & -16.8193 & 3.78599 \tabularnewline
68 & 71.3 & 80.1747 & 91.2042 & -11.0295 & -8.87466 \tabularnewline
69 & 90.9 & 100.795 & 90.8292 & 9.9654 & -9.89457 \tabularnewline
70 & 108.5 & 102.157 & 90.5333 & 11.6237 & 6.34293 \tabularnewline
71 & 88.4 & 92.802 & 90.525 & 2.27697 & -4.40197 \tabularnewline
72 & 113.4 & 107.02 & 90.1583 & 16.8617 & 6.37997 \tabularnewline
73 & 84.3 & 78.9811 & 89.9458 & -10.9647 & 5.31886 \tabularnewline
74 & 84.6 & 84.2423 & 90.5042 & -6.26192 & 0.35775 \tabularnewline
75 & 92 & 99.9136 & 91.2708 & 8.64277 & -7.9136 \tabularnewline
76 & 86.8 & 84.2292 & 91.5208 & -7.2916 & 2.57077 \tabularnewline
77 & 87.8 & 86.4891 & 91.5625 & -5.07337 & 1.31087 \tabularnewline
78 & 90.9 & 100.045 & 91.975 & 8.06985 & -9.14485 \tabularnewline
79 & 82.7 & 74.964 & 91.7833 & -16.8193 & 7.73599 \tabularnewline
80 & 80.2 & 80.2247 & 91.2542 & -11.0295 & -0.0246576 \tabularnewline
81 & 100.4 & 101.303 & 91.3375 & 9.9654 & -0.902898 \tabularnewline
82 & 105 & 103.136 & 91.5125 & 11.6237 & 1.86377 \tabularnewline
83 & 92.9 & 93.4603 & 91.1833 & 2.27697 & -0.560306 \tabularnewline
84 & 118.8 & 108.116 & 91.2542 & 16.8617 & 10.6841 \tabularnewline
85 & 74.3 & 79.9811 & 90.9458 & -10.9647 & -5.68114 \tabularnewline
86 & 81.9 & 83.7089 & 89.9708 & -6.26192 & -1.80892 \tabularnewline
87 & 96.7 & 98.7636 & 90.1208 & 8.64277 & -2.0636 \tabularnewline
88 & 86.3 & 83.2292 & 90.5208 & -7.2916 & 3.07077 \tabularnewline
89 & 80.4 & 85.7225 & 90.7958 & -5.07337 & -5.32246 \tabularnewline
90 & 100 & 98.8407 & 90.7708 & 8.06985 & 1.15931 \tabularnewline
91 & 66.2 & 74.0723 & 90.8917 & -16.8193 & -7.87234 \tabularnewline
92 & 73.3 & 80.9455 & 91.975 & -11.0295 & -7.64549 \tabularnewline
93 & 110.9 & 102.449 & 92.4833 & 9.9654 & 8.45127 \tabularnewline
94 & 104.1 & 104.495 & 92.8708 & 11.6237 & -0.394565 \tabularnewline
95 & 100.4 & 96.0561 & 93.7792 & 2.27697 & 4.34386 \tabularnewline
96 & 110.7 & 111.178 & 94.3167 & 16.8617 & -0.478361 \tabularnewline
97 & 85.3 & 83.7645 & 94.7292 & -10.9647 & 1.53553 \tabularnewline
98 & 96.9 & 89.2589 & 95.5208 & -6.26192 & 7.64108 \tabularnewline
99 & 93.9 & 104.114 & 95.4708 & 8.64277 & -10.2136 \tabularnewline
100 & 98.4 & 87.4959 & 94.7875 & -7.2916 & 10.9041 \tabularnewline
101 & 90.1 & 89.5433 & 94.6167 & -5.07337 & 0.556708 \tabularnewline
102 & 103.2 & 102.507 & 94.4375 & 8.06985 & 0.692646 \tabularnewline
103 & 72.9 & 77.614 & 94.4333 & -16.8193 & -4.71401 \tabularnewline
104 & 85.6 & 83.433 & 94.4625 & -11.0295 & 2.16701 \tabularnewline
105 & 97.4 & 105.095 & 95.1292 & 9.9654 & -7.69457 \tabularnewline
106 & 101.2 & 106.974 & 95.35 & 11.6237 & -5.77373 \tabularnewline
107 & 99.2 & 96.977 & 94.7 & 2.27697 & 2.22303 \tabularnewline
108 & 107.6 & 111.77 & 94.9083 & 16.8617 & -4.17003 \tabularnewline
109 & 88.3 & 84.4853 & 95.45 & -10.9647 & 3.81469 \tabularnewline
110 & 94.6 & 89.5548 & 95.8167 & -6.26192 & 5.04525 \tabularnewline
111 & 112.2 & NA & NA & 8.64277 & NA \tabularnewline
112 & 85.4 & NA & NA & -7.2916 & NA \tabularnewline
113 & 87.5 & NA & NA & -5.07337 & NA \tabularnewline
114 & 110.8 & NA & NA & 8.06985 & NA \tabularnewline
115 & 78.3 & NA & NA & -16.8193 & NA \tabularnewline
116 & 89 & NA & NA & -11.0295 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309928&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]101.5[/C][C]NA[/C][C]NA[/C][C]-10.9647[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]110.4[/C][C]NA[/C][C]NA[/C][C]-6.26192[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]107.3[/C][C]NA[/C][C]NA[/C][C]8.64277[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]107.7[/C][C]NA[/C][C]NA[/C][C]-7.2916[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98.3[/C][C]NA[/C][C]NA[/C][C]-5.07337[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]130.3[/C][C]NA[/C][C]NA[/C][C]8.06985[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]89.1[/C][C]87.4432[/C][C]104.262[/C][C]-16.8193[/C][C]1.65682[/C][/ROW]
[ROW][C]8[/C][C]100.4[/C][C]90.6622[/C][C]101.692[/C][C]-11.0295[/C][C]9.73784[/C][/ROW]
[ROW][C]9[/C][C]121.1[/C][C]109.499[/C][C]99.5333[/C][C]9.9654[/C][C]11.6013[/C][/ROW]
[ROW][C]10[/C][C]109.3[/C][C]109.549[/C][C]97.925[/C][C]11.6237[/C][C]-0.248732[/C][/ROW]
[ROW][C]11[/C][C]87.4[/C][C]98.5311[/C][C]96.2542[/C][C]2.27697[/C][C]-11.1311[/C][/ROW]
[ROW][C]12[/C][C]101.3[/C][C]111.133[/C][C]94.2708[/C][C]16.8617[/C][C]-9.83253[/C][/ROW]
[ROW][C]13[/C][C]75.6[/C][C]81.027[/C][C]91.9917[/C][C]-10.9647[/C][C]-5.42697[/C][/ROW]
[ROW][C]14[/C][C]74.6[/C][C]84.1423[/C][C]90.4042[/C][C]-6.26192[/C][C]-9.54225[/C][/ROW]
[ROW][C]15[/C][C]91.3[/C][C]97.8053[/C][C]89.1625[/C][C]8.64277[/C][C]-6.50527[/C][/ROW]
[ROW][C]16[/C][C]85.1[/C][C]80.5084[/C][C]87.8[/C][C]-7.2916[/C][C]4.5916[/C][/ROW]
[ROW][C]17[/C][C]80.8[/C][C]82.3433[/C][C]87.4167[/C][C]-5.07337[/C][C]-1.54329[/C][/ROW]
[ROW][C]18[/C][C]100.2[/C][C]96.4949[/C][C]88.425[/C][C]8.06985[/C][C]3.70515[/C][/ROW]
[ROW][C]19[/C][C]64.5[/C][C]72.4098[/C][C]89.2292[/C][C]-16.8193[/C][C]-7.90984[/C][/ROW]
[ROW][C]20[/C][C]86.9[/C][C]78.7288[/C][C]89.7583[/C][C]-11.0295[/C][C]8.17118[/C][/ROW]
[ROW][C]21[/C][C]104.8[/C][C]101.04[/C][C]91.075[/C][C]9.9654[/C][C]3.7596[/C][/ROW]
[ROW][C]22[/C][C]92.9[/C][C]103.47[/C][C]91.8458[/C][C]11.6237[/C][C]-10.5696[/C][/ROW]
[ROW][C]23[/C][C]94.6[/C][C]94.077[/C][C]91.8[/C][C]2.27697[/C][C]0.523028[/C][/ROW]
[ROW][C]24[/C][C]118.3[/C][C]109.133[/C][C]92.2708[/C][C]16.8617[/C][C]9.16747[/C][/ROW]
[ROW][C]25[/C][C]77.9[/C][C]82.6436[/C][C]93.6083[/C][C]-10.9647[/C][C]-4.74364[/C][/ROW]
[ROW][C]26[/C][C]85[/C][C]88.5464[/C][C]94.8083[/C][C]-6.26192[/C][C]-3.54642[/C][/ROW]
[ROW][C]27[/C][C]112.5[/C][C]104.143[/C][C]95.5[/C][C]8.64277[/C][C]8.35723[/C][/ROW]
[ROW][C]28[/C][C]82.4[/C][C]89.7001[/C][C]96.9917[/C][C]-7.2916[/C][C]-7.30006[/C][/ROW]
[ROW][C]29[/C][C]82.4[/C][C]93.7725[/C][C]98.8458[/C][C]-5.07337[/C][C]-11.3725[/C][/ROW]
[ROW][C]30[/C][C]109.9[/C][C]107.887[/C][C]99.8167[/C][C]8.06985[/C][C]2.01348[/C][/ROW]
[ROW][C]31[/C][C]86.9[/C][C]84.1973[/C][C]101.017[/C][C]-16.8193[/C][C]2.70266[/C][/ROW]
[ROW][C]32[/C][C]93.3[/C][C]91.5538[/C][C]102.583[/C][C]-11.0295[/C][C]1.74618[/C][/ROW]
[ROW][C]33[/C][C]115[/C][C]113.29[/C][C]103.325[/C][C]9.9654[/C][C]1.7096[/C][/ROW]
[ROW][C]34[/C][C]118.5[/C][C]115.115[/C][C]103.492[/C][C]11.6237[/C][C]3.3846[/C][/ROW]
[ROW][C]35[/C][C]113.5[/C][C]106.706[/C][C]104.429[/C][C]2.27697[/C][C]6.79386[/C][/ROW]
[ROW][C]36[/C][C]122.7[/C][C]121.558[/C][C]104.696[/C][C]16.8617[/C][C]1.14247[/C][/ROW]
[ROW][C]37[/C][C]102.3[/C][C]92.6978[/C][C]103.663[/C][C]-10.9647[/C][C]9.60219[/C][/ROW]
[ROW][C]38[/C][C]98.2[/C][C]96.8089[/C][C]103.071[/C][C]-6.26192[/C][C]1.39108[/C][/ROW]
[ROW][C]39[/C][C]117.1[/C][C]111.314[/C][C]102.671[/C][C]8.64277[/C][C]5.7864[/C][/ROW]
[ROW][C]40[/C][C]81.8[/C][C]94.8709[/C][C]102.162[/C][C]-7.2916[/C][C]-13.0709[/C][/ROW]
[ROW][C]41[/C][C]105.5[/C][C]96.1933[/C][C]101.267[/C][C]-5.07337[/C][C]9.30671[/C][/ROW]
[ROW][C]42[/C][C]93.2[/C][C]108.199[/C][C]100.129[/C][C]8.06985[/C][C]-14.999[/C][/ROW]
[ROW][C]43[/C][C]78.8[/C][C]81.9348[/C][C]98.7542[/C][C]-16.8193[/C][C]-3.13484[/C][/ROW]
[ROW][C]44[/C][C]87.2[/C][C]86.6955[/C][C]97.725[/C][C]-11.0295[/C][C]0.504509[/C][/ROW]
[ROW][C]45[/C][C]111.5[/C][C]107.632[/C][C]97.6667[/C][C]9.9654[/C][C]3.86793[/C][/ROW]
[ROW][C]46[/C][C]109.8[/C][C]109.67[/C][C]98.0458[/C][C]11.6237[/C][C]0.130435[/C][/ROW]
[ROW][C]47[/C][C]100.7[/C][C]100.214[/C][C]97.9375[/C][C]2.27697[/C][C]0.485528[/C][/ROW]
[ROW][C]48[/C][C]108.2[/C][C]115.653[/C][C]98.7917[/C][C]16.8617[/C][C]-7.45336[/C][/ROW]
[ROW][C]49[/C][C]83.8[/C][C]89.3603[/C][C]100.325[/C][C]-10.9647[/C][C]-5.56031[/C][/ROW]
[ROW][C]50[/C][C]92[/C][C]94.1631[/C][C]100.425[/C][C]-6.26192[/C][C]-2.16308[/C][/ROW]
[ROW][C]51[/C][C]121.9[/C][C]108.084[/C][C]99.4417[/C][C]8.64277[/C][C]13.8156[/C][/ROW]
[ROW][C]52[/C][C]86.1[/C][C]91.5417[/C][C]98.8333[/C][C]-7.2916[/C][C]-5.44173[/C][/ROW]
[ROW][C]53[/C][C]98.6[/C][C]93.7516[/C][C]98.825[/C][C]-5.07337[/C][C]4.84837[/C][/ROW]
[ROW][C]54[/C][C]120.6[/C][C]106.653[/C][C]98.5833[/C][C]8.06985[/C][C]13.9468[/C][/ROW]
[ROW][C]55[/C][C]88.2[/C][C]81.5432[/C][C]98.3625[/C][C]-16.8193[/C][C]6.65682[/C][/ROW]
[ROW][C]56[/C][C]80.2[/C][C]87.0747[/C][C]98.1042[/C][C]-11.0295[/C][C]-6.87466[/C][/ROW]
[ROW][C]57[/C][C]94.9[/C][C]106.89[/C][C]96.925[/C][C]9.9654[/C][C]-11.9904[/C][/ROW]
[ROW][C]58[/C][C]111.8[/C][C]107.628[/C][C]96.0042[/C][C]11.6237[/C][C]4.1721[/C][/ROW]
[ROW][C]59[/C][C]98.5[/C][C]97.8686[/C][C]95.5917[/C][C]2.27697[/C][C]0.631361[/C][/ROW]
[ROW][C]60[/C][C]104.6[/C][C]111.133[/C][C]94.2708[/C][C]16.8617[/C][C]-6.53253[/C][/ROW]
[ROW][C]61[/C][C]82.1[/C][C]82.052[/C][C]93.0167[/C][C]-10.9647[/C][C]0.0480276[/C][/ROW]
[ROW][C]62[/C][C]87.5[/C][C]85.9673[/C][C]92.2292[/C][C]-6.26192[/C][C]1.53275[/C][/ROW]
[ROW][C]63[/C][C]98.1[/C][C]100.334[/C][C]91.6917[/C][C]8.64277[/C][C]-2.23444[/C][/ROW]
[ROW][C]64[/C][C]87.8[/C][C]84.0959[/C][C]91.3875[/C][C]-7.2916[/C][C]3.7041[/C][/ROW]
[ROW][C]65[/C][C]87[/C][C]85.7558[/C][C]90.8292[/C][C]-5.07337[/C][C]1.24421[/C][/ROW]
[ROW][C]66[/C][C]100.5[/C][C]98.8449[/C][C]90.775[/C][C]8.06985[/C][C]1.65515[/C][/ROW]
[ROW][C]67[/C][C]78.2[/C][C]74.414[/C][C]91.2333[/C][C]-16.8193[/C][C]3.78599[/C][/ROW]
[ROW][C]68[/C][C]71.3[/C][C]80.1747[/C][C]91.2042[/C][C]-11.0295[/C][C]-8.87466[/C][/ROW]
[ROW][C]69[/C][C]90.9[/C][C]100.795[/C][C]90.8292[/C][C]9.9654[/C][C]-9.89457[/C][/ROW]
[ROW][C]70[/C][C]108.5[/C][C]102.157[/C][C]90.5333[/C][C]11.6237[/C][C]6.34293[/C][/ROW]
[ROW][C]71[/C][C]88.4[/C][C]92.802[/C][C]90.525[/C][C]2.27697[/C][C]-4.40197[/C][/ROW]
[ROW][C]72[/C][C]113.4[/C][C]107.02[/C][C]90.1583[/C][C]16.8617[/C][C]6.37997[/C][/ROW]
[ROW][C]73[/C][C]84.3[/C][C]78.9811[/C][C]89.9458[/C][C]-10.9647[/C][C]5.31886[/C][/ROW]
[ROW][C]74[/C][C]84.6[/C][C]84.2423[/C][C]90.5042[/C][C]-6.26192[/C][C]0.35775[/C][/ROW]
[ROW][C]75[/C][C]92[/C][C]99.9136[/C][C]91.2708[/C][C]8.64277[/C][C]-7.9136[/C][/ROW]
[ROW][C]76[/C][C]86.8[/C][C]84.2292[/C][C]91.5208[/C][C]-7.2916[/C][C]2.57077[/C][/ROW]
[ROW][C]77[/C][C]87.8[/C][C]86.4891[/C][C]91.5625[/C][C]-5.07337[/C][C]1.31087[/C][/ROW]
[ROW][C]78[/C][C]90.9[/C][C]100.045[/C][C]91.975[/C][C]8.06985[/C][C]-9.14485[/C][/ROW]
[ROW][C]79[/C][C]82.7[/C][C]74.964[/C][C]91.7833[/C][C]-16.8193[/C][C]7.73599[/C][/ROW]
[ROW][C]80[/C][C]80.2[/C][C]80.2247[/C][C]91.2542[/C][C]-11.0295[/C][C]-0.0246576[/C][/ROW]
[ROW][C]81[/C][C]100.4[/C][C]101.303[/C][C]91.3375[/C][C]9.9654[/C][C]-0.902898[/C][/ROW]
[ROW][C]82[/C][C]105[/C][C]103.136[/C][C]91.5125[/C][C]11.6237[/C][C]1.86377[/C][/ROW]
[ROW][C]83[/C][C]92.9[/C][C]93.4603[/C][C]91.1833[/C][C]2.27697[/C][C]-0.560306[/C][/ROW]
[ROW][C]84[/C][C]118.8[/C][C]108.116[/C][C]91.2542[/C][C]16.8617[/C][C]10.6841[/C][/ROW]
[ROW][C]85[/C][C]74.3[/C][C]79.9811[/C][C]90.9458[/C][C]-10.9647[/C][C]-5.68114[/C][/ROW]
[ROW][C]86[/C][C]81.9[/C][C]83.7089[/C][C]89.9708[/C][C]-6.26192[/C][C]-1.80892[/C][/ROW]
[ROW][C]87[/C][C]96.7[/C][C]98.7636[/C][C]90.1208[/C][C]8.64277[/C][C]-2.0636[/C][/ROW]
[ROW][C]88[/C][C]86.3[/C][C]83.2292[/C][C]90.5208[/C][C]-7.2916[/C][C]3.07077[/C][/ROW]
[ROW][C]89[/C][C]80.4[/C][C]85.7225[/C][C]90.7958[/C][C]-5.07337[/C][C]-5.32246[/C][/ROW]
[ROW][C]90[/C][C]100[/C][C]98.8407[/C][C]90.7708[/C][C]8.06985[/C][C]1.15931[/C][/ROW]
[ROW][C]91[/C][C]66.2[/C][C]74.0723[/C][C]90.8917[/C][C]-16.8193[/C][C]-7.87234[/C][/ROW]
[ROW][C]92[/C][C]73.3[/C][C]80.9455[/C][C]91.975[/C][C]-11.0295[/C][C]-7.64549[/C][/ROW]
[ROW][C]93[/C][C]110.9[/C][C]102.449[/C][C]92.4833[/C][C]9.9654[/C][C]8.45127[/C][/ROW]
[ROW][C]94[/C][C]104.1[/C][C]104.495[/C][C]92.8708[/C][C]11.6237[/C][C]-0.394565[/C][/ROW]
[ROW][C]95[/C][C]100.4[/C][C]96.0561[/C][C]93.7792[/C][C]2.27697[/C][C]4.34386[/C][/ROW]
[ROW][C]96[/C][C]110.7[/C][C]111.178[/C][C]94.3167[/C][C]16.8617[/C][C]-0.478361[/C][/ROW]
[ROW][C]97[/C][C]85.3[/C][C]83.7645[/C][C]94.7292[/C][C]-10.9647[/C][C]1.53553[/C][/ROW]
[ROW][C]98[/C][C]96.9[/C][C]89.2589[/C][C]95.5208[/C][C]-6.26192[/C][C]7.64108[/C][/ROW]
[ROW][C]99[/C][C]93.9[/C][C]104.114[/C][C]95.4708[/C][C]8.64277[/C][C]-10.2136[/C][/ROW]
[ROW][C]100[/C][C]98.4[/C][C]87.4959[/C][C]94.7875[/C][C]-7.2916[/C][C]10.9041[/C][/ROW]
[ROW][C]101[/C][C]90.1[/C][C]89.5433[/C][C]94.6167[/C][C]-5.07337[/C][C]0.556708[/C][/ROW]
[ROW][C]102[/C][C]103.2[/C][C]102.507[/C][C]94.4375[/C][C]8.06985[/C][C]0.692646[/C][/ROW]
[ROW][C]103[/C][C]72.9[/C][C]77.614[/C][C]94.4333[/C][C]-16.8193[/C][C]-4.71401[/C][/ROW]
[ROW][C]104[/C][C]85.6[/C][C]83.433[/C][C]94.4625[/C][C]-11.0295[/C][C]2.16701[/C][/ROW]
[ROW][C]105[/C][C]97.4[/C][C]105.095[/C][C]95.1292[/C][C]9.9654[/C][C]-7.69457[/C][/ROW]
[ROW][C]106[/C][C]101.2[/C][C]106.974[/C][C]95.35[/C][C]11.6237[/C][C]-5.77373[/C][/ROW]
[ROW][C]107[/C][C]99.2[/C][C]96.977[/C][C]94.7[/C][C]2.27697[/C][C]2.22303[/C][/ROW]
[ROW][C]108[/C][C]107.6[/C][C]111.77[/C][C]94.9083[/C][C]16.8617[/C][C]-4.17003[/C][/ROW]
[ROW][C]109[/C][C]88.3[/C][C]84.4853[/C][C]95.45[/C][C]-10.9647[/C][C]3.81469[/C][/ROW]
[ROW][C]110[/C][C]94.6[/C][C]89.5548[/C][C]95.8167[/C][C]-6.26192[/C][C]5.04525[/C][/ROW]
[ROW][C]111[/C][C]112.2[/C][C]NA[/C][C]NA[/C][C]8.64277[/C][C]NA[/C][/ROW]
[ROW][C]112[/C][C]85.4[/C][C]NA[/C][C]NA[/C][C]-7.2916[/C][C]NA[/C][/ROW]
[ROW][C]113[/C][C]87.5[/C][C]NA[/C][C]NA[/C][C]-5.07337[/C][C]NA[/C][/ROW]
[ROW][C]114[/C][C]110.8[/C][C]NA[/C][C]NA[/C][C]8.06985[/C][C]NA[/C][/ROW]
[ROW][C]115[/C][C]78.3[/C][C]NA[/C][C]NA[/C][C]-16.8193[/C][C]NA[/C][/ROW]
[ROW][C]116[/C][C]89[/C][C]NA[/C][C]NA[/C][C]-11.0295[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309928&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309928&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	101.5	NA	NA	-10.9647	NA
2	110.4	NA	NA	-6.26192	NA
3	107.3	NA	NA	8.64277	NA
4	107.7	NA	NA	-7.2916	NA
5	98.3	NA	NA	-5.07337	NA
6	130.3	NA	NA	8.06985	NA
7	89.1	87.4432	104.262	-16.8193	1.65682
8	100.4	90.6622	101.692	-11.0295	9.73784
9	121.1	109.499	99.5333	9.9654	11.6013
10	109.3	109.549	97.925	11.6237	-0.248732
11	87.4	98.5311	96.2542	2.27697	-11.1311
12	101.3	111.133	94.2708	16.8617	-9.83253
13	75.6	81.027	91.9917	-10.9647	-5.42697
14	74.6	84.1423	90.4042	-6.26192	-9.54225
15	91.3	97.8053	89.1625	8.64277	-6.50527
16	85.1	80.5084	87.8	-7.2916	4.5916
17	80.8	82.3433	87.4167	-5.07337	-1.54329
18	100.2	96.4949	88.425	8.06985	3.70515
19	64.5	72.4098	89.2292	-16.8193	-7.90984
20	86.9	78.7288	89.7583	-11.0295	8.17118
21	104.8	101.04	91.075	9.9654	3.7596
22	92.9	103.47	91.8458	11.6237	-10.5696
23	94.6	94.077	91.8	2.27697	0.523028
24	118.3	109.133	92.2708	16.8617	9.16747
25	77.9	82.6436	93.6083	-10.9647	-4.74364
26	85	88.5464	94.8083	-6.26192	-3.54642
27	112.5	104.143	95.5	8.64277	8.35723
28	82.4	89.7001	96.9917	-7.2916	-7.30006
29	82.4	93.7725	98.8458	-5.07337	-11.3725
30	109.9	107.887	99.8167	8.06985	2.01348
31	86.9	84.1973	101.017	-16.8193	2.70266
32	93.3	91.5538	102.583	-11.0295	1.74618
33	115	113.29	103.325	9.9654	1.7096
34	118.5	115.115	103.492	11.6237	3.3846
35	113.5	106.706	104.429	2.27697	6.79386
36	122.7	121.558	104.696	16.8617	1.14247
37	102.3	92.6978	103.663	-10.9647	9.60219
38	98.2	96.8089	103.071	-6.26192	1.39108
39	117.1	111.314	102.671	8.64277	5.7864
40	81.8	94.8709	102.162	-7.2916	-13.0709
41	105.5	96.1933	101.267	-5.07337	9.30671
42	93.2	108.199	100.129	8.06985	-14.999
43	78.8	81.9348	98.7542	-16.8193	-3.13484
44	87.2	86.6955	97.725	-11.0295	0.504509
45	111.5	107.632	97.6667	9.9654	3.86793
46	109.8	109.67	98.0458	11.6237	0.130435
47	100.7	100.214	97.9375	2.27697	0.485528
48	108.2	115.653	98.7917	16.8617	-7.45336
49	83.8	89.3603	100.325	-10.9647	-5.56031
50	92	94.1631	100.425	-6.26192	-2.16308
51	121.9	108.084	99.4417	8.64277	13.8156
52	86.1	91.5417	98.8333	-7.2916	-5.44173
53	98.6	93.7516	98.825	-5.07337	4.84837
54	120.6	106.653	98.5833	8.06985	13.9468
55	88.2	81.5432	98.3625	-16.8193	6.65682
56	80.2	87.0747	98.1042	-11.0295	-6.87466
57	94.9	106.89	96.925	9.9654	-11.9904
58	111.8	107.628	96.0042	11.6237	4.1721
59	98.5	97.8686	95.5917	2.27697	0.631361
60	104.6	111.133	94.2708	16.8617	-6.53253
61	82.1	82.052	93.0167	-10.9647	0.0480276
62	87.5	85.9673	92.2292	-6.26192	1.53275
63	98.1	100.334	91.6917	8.64277	-2.23444
64	87.8	84.0959	91.3875	-7.2916	3.7041
65	87	85.7558	90.8292	-5.07337	1.24421
66	100.5	98.8449	90.775	8.06985	1.65515
67	78.2	74.414	91.2333	-16.8193	3.78599
68	71.3	80.1747	91.2042	-11.0295	-8.87466
69	90.9	100.795	90.8292	9.9654	-9.89457
70	108.5	102.157	90.5333	11.6237	6.34293
71	88.4	92.802	90.525	2.27697	-4.40197
72	113.4	107.02	90.1583	16.8617	6.37997
73	84.3	78.9811	89.9458	-10.9647	5.31886
74	84.6	84.2423	90.5042	-6.26192	0.35775
75	92	99.9136	91.2708	8.64277	-7.9136
76	86.8	84.2292	91.5208	-7.2916	2.57077
77	87.8	86.4891	91.5625	-5.07337	1.31087
78	90.9	100.045	91.975	8.06985	-9.14485
79	82.7	74.964	91.7833	-16.8193	7.73599
80	80.2	80.2247	91.2542	-11.0295	-0.0246576
81	100.4	101.303	91.3375	9.9654	-0.902898
82	105	103.136	91.5125	11.6237	1.86377
83	92.9	93.4603	91.1833	2.27697	-0.560306
84	118.8	108.116	91.2542	16.8617	10.6841
85	74.3	79.9811	90.9458	-10.9647	-5.68114
86	81.9	83.7089	89.9708	-6.26192	-1.80892
87	96.7	98.7636	90.1208	8.64277	-2.0636
88	86.3	83.2292	90.5208	-7.2916	3.07077
89	80.4	85.7225	90.7958	-5.07337	-5.32246
90	100	98.8407	90.7708	8.06985	1.15931
91	66.2	74.0723	90.8917	-16.8193	-7.87234
92	73.3	80.9455	91.975	-11.0295	-7.64549
93	110.9	102.449	92.4833	9.9654	8.45127
94	104.1	104.495	92.8708	11.6237	-0.394565
95	100.4	96.0561	93.7792	2.27697	4.34386
96	110.7	111.178	94.3167	16.8617	-0.478361
97	85.3	83.7645	94.7292	-10.9647	1.53553
98	96.9	89.2589	95.5208	-6.26192	7.64108
99	93.9	104.114	95.4708	8.64277	-10.2136
100	98.4	87.4959	94.7875	-7.2916	10.9041
101	90.1	89.5433	94.6167	-5.07337	0.556708
102	103.2	102.507	94.4375	8.06985	0.692646
103	72.9	77.614	94.4333	-16.8193	-4.71401
104	85.6	83.433	94.4625	-11.0295	2.16701
105	97.4	105.095	95.1292	9.9654	-7.69457
106	101.2	106.974	95.35	11.6237	-5.77373
107	99.2	96.977	94.7	2.27697	2.22303
108	107.6	111.77	94.9083	16.8617	-4.17003
109	88.3	84.4853	95.45	-10.9647	3.81469
110	94.6	89.5548	95.8167	-6.26192	5.04525
111	112.2	NA	NA	8.64277	NA
112	85.4	NA	NA	-7.2916	NA
113	87.5	NA	NA	-5.07337	NA
114	110.8	NA	NA	8.06985	NA
115	78.3	NA	NA	-16.8193	NA
116	89	NA	NA	-11.0295	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