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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 18 Aug 2014 09:06:30 +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/2014/Aug/18/t1408349231smsdqq89en47qrl.htm/, Retrieved Thu, 16 May 2024 07:03:40 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235691, Retrieved Thu, 16 May 2024 07:03:40 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

144

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

-     [Notched Boxplots] [] [2013-02-26 20:31:34] [f974b105a61ab974a820d469d59cfaf7]
- RMPD  [Harrell-Davis Quantiles] [] [2014-08-18 05:22:13] [f974b105a61ab974a820d469d59cfaf7]
- RMP     [(Partial) Autocorrelation Function] [] [2014-08-18 06:01:25] [f974b105a61ab974a820d469d59cfaf7]
- RMPD      [Univariate Data Series] [] [2014-08-18 07:05:48] [f85cc8f00ef4b762f0a6fdfddc793773]
- RM          [Mean versus Median] [] [2014-08-18 07:29:41] [f974b105a61ab974a820d469d59cfaf7]
- RM            [(Partial) Autocorrelation Function] [] [2014-08-18 07:41:46] [f974b105a61ab974a820d469d59cfaf7]
- RM                [Classical Decomposition] [] [2014-08-18 08:06:30] [8f84a338303fe8d74ac0d8ad91c8b331] [Current]

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Dataseries X:

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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	'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235691&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235691&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	840	NA	NA	0.953733	NA
2	880	NA	NA	0.875125	NA
3	930	NA	NA	1.01538	NA
4	920	NA	NA	1.1192	NA
5	940	NA	NA	1.12165	NA
6	880	NA	NA	0.872525	NA
7	980	1139.49	912.083	1.24933	0.860031
8	860	822.711	912.5	0.901602	1.04532
9	900	787.434	911.667	0.86373	1.14295
10	930	866.976	914.167	0.948378	1.07269
11	870	1050.59	919.583	1.14247	0.828103
12	1000	863.497	921.667	0.936886	1.15808
13	870	884.587	927.5	0.953733	0.98351
14	860	818.242	935	0.875125	1.05103
15	930	945.993	931.667	1.01538	0.983094
16	980	1036.66	926.25	1.1192	0.945345
17	1010	1038.92	926.25	1.12165	0.972159
18	860	809.267	927.5	0.872525	1.06269
19	1140	1159.8	928.333	1.24933	0.982932
20	880	838.865	930.417	0.901602	1.04904
21	800	802.55	929.167	0.86373	0.996823
22	900	879.621	927.5	0.948378	1.02317
23	900	1062.5	930	1.14247	0.847063
24	1000	870.133	928.75	0.936886	1.14925
25	890	883.792	926.667	0.953733	1.00702
26	890	809.855	925.417	0.875125	1.09896
27	870	934.57	920.417	1.01538	0.930909
28	1000	1029.2	919.583	1.1192	0.971631
29	1050	1037.52	925	1.12165	1.01203
30	790	806.722	924.583	0.872525	0.979272
31	1160	1147.82	918.75	1.24933	1.01061
32	830	825.341	915.417	0.901602	1.00564
33	730	789.953	914.583	0.86373	0.924105
34	950	868.951	916.25	0.948378	1.09327
35	980	1048.69	917.917	1.14247	0.934499
36	910	859.593	917.5	0.936886	1.05864
37	840	873.46	915.833	0.953733	0.961692
38	860	802.927	917.5	0.875125	1.07108
39	880	934.57	920.417	1.01538	0.941609
40	1030	1026.4	917.083	1.1192	1.00351
41	1060	1027.71	916.25	1.12165	1.03142
42	770	799.451	916.25	0.872525	0.963161
43	1140	1139.49	912.083	1.24933	1.00044
44	890	820.082	909.583	0.901602	1.08526
45	740	785.995	910	0.86373	0.941482
46	860	866.185	913.333	0.948378	0.992859
47	1050	1044.41	914.167	1.14247	1.00536
48	840	854.518	912.083	0.936886	0.98301
49	810	873.063	915.417	0.953733	0.927768
50	830	803.657	918.333	0.875125	1.03278
51	920	932.878	918.75	1.01538	0.986196
52	1070	1028.26	918.75	1.1192	1.04059
53	1040	1029.58	917.917	1.12165	1.01012
54	740	799.087	915.833	0.872525	0.926057
55	1250	1141.58	913.75	1.24933	1.09498
56	850	824.59	914.583	0.901602	1.03082
57	790	788.874	913.333	0.86373	1.00143
58	810	863.024	910	0.948378	0.93856
59	1080	1038.69	909.167	1.14247	1.03977
60	760	854.909	912.5	0.936886	0.888984
61	840	867.897	910	0.953733	0.967857
62	820	791.624	904.583	0.875125	1.03585
63	900	917.224	903.333	1.01538	0.981221
64	1010	1011.48	903.75	1.1192	0.99854
65	1080	1016.49	906.25	1.12165	1.06248
66	780	793.997	910	0.872525	0.982371
67	1150	1141.58	913.75	1.24933	1.00738
68	820	825.341	915.417	0.901602	0.993529
69	790	792.113	917.083	0.86373	0.997333
70	820	874.879	922.5	0.948378	0.937273
71	1130	1058.21	926.25	1.14247	1.06784
72	800	870.914	929.583	0.936886	0.918575
73	890	891.343	934.583	0.953733	0.998494
74	810	818.607	935.417	0.875125	0.989486
75	950	948.955	934.583	1.01538	1.0011
76	1090	1047.85	936.25	1.1192	1.04022
77	1090	1056.22	941.667	1.12165	1.03199
78	850	825.263	945.833	0.872525	1.02997
79	1200	1183.74	947.5	1.24933	1.01374
80	790	851.638	944.583	0.901602	0.927624
81	800	814.786	943.333	0.86373	0.981853
82	850	895.822	944.583	0.948378	0.948849
83	1230	1072.49	938.75	1.14247	1.14686
84	800	875.208	934.167	0.936886	0.914068
85	930	889.753	932.917	0.953733	1.04523
86	700	813.502	929.583	0.875125	0.860478
87	1030	941.339	927.083	1.01538	1.09419
88	1040	1038.99	928.333	1.1192	1.00097
89	1000	1040.33	927.5	1.12165	0.961237
90	830	807.812	925.833	0.872525	1.02747
91	1190	1158.75	927.5	1.24933	1.02696
92	720	837.362	928.75	0.901602	0.859843
93	810	801.11	927.5	0.86373	1.0111
94	870	878.435	926.25	0.948378	0.990398
95	1190	1055.35	923.75	1.14247	1.12758
96	800	863.497	921.667	0.936886	0.926465
97	970	877.434	920	0.953733	1.1055
98	690	804.75	919.583	0.875125	0.857409
99	1010	936.262	922.083	1.01538	1.07876
100	1030	1033.86	923.75	1.1192	0.996266
101	950	1037.52	925	1.12165	0.915643
102	830	808.903	927.083	0.872525	1.02608
103	1150	NA	NA	1.24933	NA
104	750	NA	NA	0.901602	NA
105	840	NA	NA	0.86373	NA
106	880	NA	NA	0.948378	NA
107	1210	NA	NA	1.14247	NA
108	830	NA	NA	0.936886	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 840 & NA & NA & 0.953733 & NA \tabularnewline
2 & 880 & NA & NA & 0.875125 & NA \tabularnewline
3 & 930 & NA & NA & 1.01538 & NA \tabularnewline
4 & 920 & NA & NA & 1.1192 & NA \tabularnewline
5 & 940 & NA & NA & 1.12165 & NA \tabularnewline
6 & 880 & NA & NA & 0.872525 & NA \tabularnewline
7 & 980 & 1139.49 & 912.083 & 1.24933 & 0.860031 \tabularnewline
8 & 860 & 822.711 & 912.5 & 0.901602 & 1.04532 \tabularnewline
9 & 900 & 787.434 & 911.667 & 0.86373 & 1.14295 \tabularnewline
10 & 930 & 866.976 & 914.167 & 0.948378 & 1.07269 \tabularnewline
11 & 870 & 1050.59 & 919.583 & 1.14247 & 0.828103 \tabularnewline
12 & 1000 & 863.497 & 921.667 & 0.936886 & 1.15808 \tabularnewline
13 & 870 & 884.587 & 927.5 & 0.953733 & 0.98351 \tabularnewline
14 & 860 & 818.242 & 935 & 0.875125 & 1.05103 \tabularnewline
15 & 930 & 945.993 & 931.667 & 1.01538 & 0.983094 \tabularnewline
16 & 980 & 1036.66 & 926.25 & 1.1192 & 0.945345 \tabularnewline
17 & 1010 & 1038.92 & 926.25 & 1.12165 & 0.972159 \tabularnewline
18 & 860 & 809.267 & 927.5 & 0.872525 & 1.06269 \tabularnewline
19 & 1140 & 1159.8 & 928.333 & 1.24933 & 0.982932 \tabularnewline
20 & 880 & 838.865 & 930.417 & 0.901602 & 1.04904 \tabularnewline
21 & 800 & 802.55 & 929.167 & 0.86373 & 0.996823 \tabularnewline
22 & 900 & 879.621 & 927.5 & 0.948378 & 1.02317 \tabularnewline
23 & 900 & 1062.5 & 930 & 1.14247 & 0.847063 \tabularnewline
24 & 1000 & 870.133 & 928.75 & 0.936886 & 1.14925 \tabularnewline
25 & 890 & 883.792 & 926.667 & 0.953733 & 1.00702 \tabularnewline
26 & 890 & 809.855 & 925.417 & 0.875125 & 1.09896 \tabularnewline
27 & 870 & 934.57 & 920.417 & 1.01538 & 0.930909 \tabularnewline
28 & 1000 & 1029.2 & 919.583 & 1.1192 & 0.971631 \tabularnewline
29 & 1050 & 1037.52 & 925 & 1.12165 & 1.01203 \tabularnewline
30 & 790 & 806.722 & 924.583 & 0.872525 & 0.979272 \tabularnewline
31 & 1160 & 1147.82 & 918.75 & 1.24933 & 1.01061 \tabularnewline
32 & 830 & 825.341 & 915.417 & 0.901602 & 1.00564 \tabularnewline
33 & 730 & 789.953 & 914.583 & 0.86373 & 0.924105 \tabularnewline
34 & 950 & 868.951 & 916.25 & 0.948378 & 1.09327 \tabularnewline
35 & 980 & 1048.69 & 917.917 & 1.14247 & 0.934499 \tabularnewline
36 & 910 & 859.593 & 917.5 & 0.936886 & 1.05864 \tabularnewline
37 & 840 & 873.46 & 915.833 & 0.953733 & 0.961692 \tabularnewline
38 & 860 & 802.927 & 917.5 & 0.875125 & 1.07108 \tabularnewline
39 & 880 & 934.57 & 920.417 & 1.01538 & 0.941609 \tabularnewline
40 & 1030 & 1026.4 & 917.083 & 1.1192 & 1.00351 \tabularnewline
41 & 1060 & 1027.71 & 916.25 & 1.12165 & 1.03142 \tabularnewline
42 & 770 & 799.451 & 916.25 & 0.872525 & 0.963161 \tabularnewline
43 & 1140 & 1139.49 & 912.083 & 1.24933 & 1.00044 \tabularnewline
44 & 890 & 820.082 & 909.583 & 0.901602 & 1.08526 \tabularnewline
45 & 740 & 785.995 & 910 & 0.86373 & 0.941482 \tabularnewline
46 & 860 & 866.185 & 913.333 & 0.948378 & 0.992859 \tabularnewline
47 & 1050 & 1044.41 & 914.167 & 1.14247 & 1.00536 \tabularnewline
48 & 840 & 854.518 & 912.083 & 0.936886 & 0.98301 \tabularnewline
49 & 810 & 873.063 & 915.417 & 0.953733 & 0.927768 \tabularnewline
50 & 830 & 803.657 & 918.333 & 0.875125 & 1.03278 \tabularnewline
51 & 920 & 932.878 & 918.75 & 1.01538 & 0.986196 \tabularnewline
52 & 1070 & 1028.26 & 918.75 & 1.1192 & 1.04059 \tabularnewline
53 & 1040 & 1029.58 & 917.917 & 1.12165 & 1.01012 \tabularnewline
54 & 740 & 799.087 & 915.833 & 0.872525 & 0.926057 \tabularnewline
55 & 1250 & 1141.58 & 913.75 & 1.24933 & 1.09498 \tabularnewline
56 & 850 & 824.59 & 914.583 & 0.901602 & 1.03082 \tabularnewline
57 & 790 & 788.874 & 913.333 & 0.86373 & 1.00143 \tabularnewline
58 & 810 & 863.024 & 910 & 0.948378 & 0.93856 \tabularnewline
59 & 1080 & 1038.69 & 909.167 & 1.14247 & 1.03977 \tabularnewline
60 & 760 & 854.909 & 912.5 & 0.936886 & 0.888984 \tabularnewline
61 & 840 & 867.897 & 910 & 0.953733 & 0.967857 \tabularnewline
62 & 820 & 791.624 & 904.583 & 0.875125 & 1.03585 \tabularnewline
63 & 900 & 917.224 & 903.333 & 1.01538 & 0.981221 \tabularnewline
64 & 1010 & 1011.48 & 903.75 & 1.1192 & 0.99854 \tabularnewline
65 & 1080 & 1016.49 & 906.25 & 1.12165 & 1.06248 \tabularnewline
66 & 780 & 793.997 & 910 & 0.872525 & 0.982371 \tabularnewline
67 & 1150 & 1141.58 & 913.75 & 1.24933 & 1.00738 \tabularnewline
68 & 820 & 825.341 & 915.417 & 0.901602 & 0.993529 \tabularnewline
69 & 790 & 792.113 & 917.083 & 0.86373 & 0.997333 \tabularnewline
70 & 820 & 874.879 & 922.5 & 0.948378 & 0.937273 \tabularnewline
71 & 1130 & 1058.21 & 926.25 & 1.14247 & 1.06784 \tabularnewline
72 & 800 & 870.914 & 929.583 & 0.936886 & 0.918575 \tabularnewline
73 & 890 & 891.343 & 934.583 & 0.953733 & 0.998494 \tabularnewline
74 & 810 & 818.607 & 935.417 & 0.875125 & 0.989486 \tabularnewline
75 & 950 & 948.955 & 934.583 & 1.01538 & 1.0011 \tabularnewline
76 & 1090 & 1047.85 & 936.25 & 1.1192 & 1.04022 \tabularnewline
77 & 1090 & 1056.22 & 941.667 & 1.12165 & 1.03199 \tabularnewline
78 & 850 & 825.263 & 945.833 & 0.872525 & 1.02997 \tabularnewline
79 & 1200 & 1183.74 & 947.5 & 1.24933 & 1.01374 \tabularnewline
80 & 790 & 851.638 & 944.583 & 0.901602 & 0.927624 \tabularnewline
81 & 800 & 814.786 & 943.333 & 0.86373 & 0.981853 \tabularnewline
82 & 850 & 895.822 & 944.583 & 0.948378 & 0.948849 \tabularnewline
83 & 1230 & 1072.49 & 938.75 & 1.14247 & 1.14686 \tabularnewline
84 & 800 & 875.208 & 934.167 & 0.936886 & 0.914068 \tabularnewline
85 & 930 & 889.753 & 932.917 & 0.953733 & 1.04523 \tabularnewline
86 & 700 & 813.502 & 929.583 & 0.875125 & 0.860478 \tabularnewline
87 & 1030 & 941.339 & 927.083 & 1.01538 & 1.09419 \tabularnewline
88 & 1040 & 1038.99 & 928.333 & 1.1192 & 1.00097 \tabularnewline
89 & 1000 & 1040.33 & 927.5 & 1.12165 & 0.961237 \tabularnewline
90 & 830 & 807.812 & 925.833 & 0.872525 & 1.02747 \tabularnewline
91 & 1190 & 1158.75 & 927.5 & 1.24933 & 1.02696 \tabularnewline
92 & 720 & 837.362 & 928.75 & 0.901602 & 0.859843 \tabularnewline
93 & 810 & 801.11 & 927.5 & 0.86373 & 1.0111 \tabularnewline
94 & 870 & 878.435 & 926.25 & 0.948378 & 0.990398 \tabularnewline
95 & 1190 & 1055.35 & 923.75 & 1.14247 & 1.12758 \tabularnewline
96 & 800 & 863.497 & 921.667 & 0.936886 & 0.926465 \tabularnewline
97 & 970 & 877.434 & 920 & 0.953733 & 1.1055 \tabularnewline
98 & 690 & 804.75 & 919.583 & 0.875125 & 0.857409 \tabularnewline
99 & 1010 & 936.262 & 922.083 & 1.01538 & 1.07876 \tabularnewline
100 & 1030 & 1033.86 & 923.75 & 1.1192 & 0.996266 \tabularnewline
101 & 950 & 1037.52 & 925 & 1.12165 & 0.915643 \tabularnewline
102 & 830 & 808.903 & 927.083 & 0.872525 & 1.02608 \tabularnewline
103 & 1150 & NA & NA & 1.24933 & NA \tabularnewline
104 & 750 & NA & NA & 0.901602 & NA \tabularnewline
105 & 840 & NA & NA & 0.86373 & NA \tabularnewline
106 & 880 & NA & NA & 0.948378 & NA \tabularnewline
107 & 1210 & NA & NA & 1.14247 & NA \tabularnewline
108 & 830 & NA & NA & 0.936886 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235691&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]840[/C][C]NA[/C][C]NA[/C][C]0.953733[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]880[/C][C]NA[/C][C]NA[/C][C]0.875125[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]930[/C][C]NA[/C][C]NA[/C][C]1.01538[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]920[/C][C]NA[/C][C]NA[/C][C]1.1192[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]940[/C][C]NA[/C][C]NA[/C][C]1.12165[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]880[/C][C]NA[/C][C]NA[/C][C]0.872525[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]980[/C][C]1139.49[/C][C]912.083[/C][C]1.24933[/C][C]0.860031[/C][/ROW]
[ROW][C]8[/C][C]860[/C][C]822.711[/C][C]912.5[/C][C]0.901602[/C][C]1.04532[/C][/ROW]
[ROW][C]9[/C][C]900[/C][C]787.434[/C][C]911.667[/C][C]0.86373[/C][C]1.14295[/C][/ROW]
[ROW][C]10[/C][C]930[/C][C]866.976[/C][C]914.167[/C][C]0.948378[/C][C]1.07269[/C][/ROW]
[ROW][C]11[/C][C]870[/C][C]1050.59[/C][C]919.583[/C][C]1.14247[/C][C]0.828103[/C][/ROW]
[ROW][C]12[/C][C]1000[/C][C]863.497[/C][C]921.667[/C][C]0.936886[/C][C]1.15808[/C][/ROW]
[ROW][C]13[/C][C]870[/C][C]884.587[/C][C]927.5[/C][C]0.953733[/C][C]0.98351[/C][/ROW]
[ROW][C]14[/C][C]860[/C][C]818.242[/C][C]935[/C][C]0.875125[/C][C]1.05103[/C][/ROW]
[ROW][C]15[/C][C]930[/C][C]945.993[/C][C]931.667[/C][C]1.01538[/C][C]0.983094[/C][/ROW]
[ROW][C]16[/C][C]980[/C][C]1036.66[/C][C]926.25[/C][C]1.1192[/C][C]0.945345[/C][/ROW]
[ROW][C]17[/C][C]1010[/C][C]1038.92[/C][C]926.25[/C][C]1.12165[/C][C]0.972159[/C][/ROW]
[ROW][C]18[/C][C]860[/C][C]809.267[/C][C]927.5[/C][C]0.872525[/C][C]1.06269[/C][/ROW]
[ROW][C]19[/C][C]1140[/C][C]1159.8[/C][C]928.333[/C][C]1.24933[/C][C]0.982932[/C][/ROW]
[ROW][C]20[/C][C]880[/C][C]838.865[/C][C]930.417[/C][C]0.901602[/C][C]1.04904[/C][/ROW]
[ROW][C]21[/C][C]800[/C][C]802.55[/C][C]929.167[/C][C]0.86373[/C][C]0.996823[/C][/ROW]
[ROW][C]22[/C][C]900[/C][C]879.621[/C][C]927.5[/C][C]0.948378[/C][C]1.02317[/C][/ROW]
[ROW][C]23[/C][C]900[/C][C]1062.5[/C][C]930[/C][C]1.14247[/C][C]0.847063[/C][/ROW]
[ROW][C]24[/C][C]1000[/C][C]870.133[/C][C]928.75[/C][C]0.936886[/C][C]1.14925[/C][/ROW]
[ROW][C]25[/C][C]890[/C][C]883.792[/C][C]926.667[/C][C]0.953733[/C][C]1.00702[/C][/ROW]
[ROW][C]26[/C][C]890[/C][C]809.855[/C][C]925.417[/C][C]0.875125[/C][C]1.09896[/C][/ROW]
[ROW][C]27[/C][C]870[/C][C]934.57[/C][C]920.417[/C][C]1.01538[/C][C]0.930909[/C][/ROW]
[ROW][C]28[/C][C]1000[/C][C]1029.2[/C][C]919.583[/C][C]1.1192[/C][C]0.971631[/C][/ROW]
[ROW][C]29[/C][C]1050[/C][C]1037.52[/C][C]925[/C][C]1.12165[/C][C]1.01203[/C][/ROW]
[ROW][C]30[/C][C]790[/C][C]806.722[/C][C]924.583[/C][C]0.872525[/C][C]0.979272[/C][/ROW]
[ROW][C]31[/C][C]1160[/C][C]1147.82[/C][C]918.75[/C][C]1.24933[/C][C]1.01061[/C][/ROW]
[ROW][C]32[/C][C]830[/C][C]825.341[/C][C]915.417[/C][C]0.901602[/C][C]1.00564[/C][/ROW]
[ROW][C]33[/C][C]730[/C][C]789.953[/C][C]914.583[/C][C]0.86373[/C][C]0.924105[/C][/ROW]
[ROW][C]34[/C][C]950[/C][C]868.951[/C][C]916.25[/C][C]0.948378[/C][C]1.09327[/C][/ROW]
[ROW][C]35[/C][C]980[/C][C]1048.69[/C][C]917.917[/C][C]1.14247[/C][C]0.934499[/C][/ROW]
[ROW][C]36[/C][C]910[/C][C]859.593[/C][C]917.5[/C][C]0.936886[/C][C]1.05864[/C][/ROW]
[ROW][C]37[/C][C]840[/C][C]873.46[/C][C]915.833[/C][C]0.953733[/C][C]0.961692[/C][/ROW]
[ROW][C]38[/C][C]860[/C][C]802.927[/C][C]917.5[/C][C]0.875125[/C][C]1.07108[/C][/ROW]
[ROW][C]39[/C][C]880[/C][C]934.57[/C][C]920.417[/C][C]1.01538[/C][C]0.941609[/C][/ROW]
[ROW][C]40[/C][C]1030[/C][C]1026.4[/C][C]917.083[/C][C]1.1192[/C][C]1.00351[/C][/ROW]
[ROW][C]41[/C][C]1060[/C][C]1027.71[/C][C]916.25[/C][C]1.12165[/C][C]1.03142[/C][/ROW]
[ROW][C]42[/C][C]770[/C][C]799.451[/C][C]916.25[/C][C]0.872525[/C][C]0.963161[/C][/ROW]
[ROW][C]43[/C][C]1140[/C][C]1139.49[/C][C]912.083[/C][C]1.24933[/C][C]1.00044[/C][/ROW]
[ROW][C]44[/C][C]890[/C][C]820.082[/C][C]909.583[/C][C]0.901602[/C][C]1.08526[/C][/ROW]
[ROW][C]45[/C][C]740[/C][C]785.995[/C][C]910[/C][C]0.86373[/C][C]0.941482[/C][/ROW]
[ROW][C]46[/C][C]860[/C][C]866.185[/C][C]913.333[/C][C]0.948378[/C][C]0.992859[/C][/ROW]
[ROW][C]47[/C][C]1050[/C][C]1044.41[/C][C]914.167[/C][C]1.14247[/C][C]1.00536[/C][/ROW]
[ROW][C]48[/C][C]840[/C][C]854.518[/C][C]912.083[/C][C]0.936886[/C][C]0.98301[/C][/ROW]
[ROW][C]49[/C][C]810[/C][C]873.063[/C][C]915.417[/C][C]0.953733[/C][C]0.927768[/C][/ROW]
[ROW][C]50[/C][C]830[/C][C]803.657[/C][C]918.333[/C][C]0.875125[/C][C]1.03278[/C][/ROW]
[ROW][C]51[/C][C]920[/C][C]932.878[/C][C]918.75[/C][C]1.01538[/C][C]0.986196[/C][/ROW]
[ROW][C]52[/C][C]1070[/C][C]1028.26[/C][C]918.75[/C][C]1.1192[/C][C]1.04059[/C][/ROW]
[ROW][C]53[/C][C]1040[/C][C]1029.58[/C][C]917.917[/C][C]1.12165[/C][C]1.01012[/C][/ROW]
[ROW][C]54[/C][C]740[/C][C]799.087[/C][C]915.833[/C][C]0.872525[/C][C]0.926057[/C][/ROW]
[ROW][C]55[/C][C]1250[/C][C]1141.58[/C][C]913.75[/C][C]1.24933[/C][C]1.09498[/C][/ROW]
[ROW][C]56[/C][C]850[/C][C]824.59[/C][C]914.583[/C][C]0.901602[/C][C]1.03082[/C][/ROW]
[ROW][C]57[/C][C]790[/C][C]788.874[/C][C]913.333[/C][C]0.86373[/C][C]1.00143[/C][/ROW]
[ROW][C]58[/C][C]810[/C][C]863.024[/C][C]910[/C][C]0.948378[/C][C]0.93856[/C][/ROW]
[ROW][C]59[/C][C]1080[/C][C]1038.69[/C][C]909.167[/C][C]1.14247[/C][C]1.03977[/C][/ROW]
[ROW][C]60[/C][C]760[/C][C]854.909[/C][C]912.5[/C][C]0.936886[/C][C]0.888984[/C][/ROW]
[ROW][C]61[/C][C]840[/C][C]867.897[/C][C]910[/C][C]0.953733[/C][C]0.967857[/C][/ROW]
[ROW][C]62[/C][C]820[/C][C]791.624[/C][C]904.583[/C][C]0.875125[/C][C]1.03585[/C][/ROW]
[ROW][C]63[/C][C]900[/C][C]917.224[/C][C]903.333[/C][C]1.01538[/C][C]0.981221[/C][/ROW]
[ROW][C]64[/C][C]1010[/C][C]1011.48[/C][C]903.75[/C][C]1.1192[/C][C]0.99854[/C][/ROW]
[ROW][C]65[/C][C]1080[/C][C]1016.49[/C][C]906.25[/C][C]1.12165[/C][C]1.06248[/C][/ROW]
[ROW][C]66[/C][C]780[/C][C]793.997[/C][C]910[/C][C]0.872525[/C][C]0.982371[/C][/ROW]
[ROW][C]67[/C][C]1150[/C][C]1141.58[/C][C]913.75[/C][C]1.24933[/C][C]1.00738[/C][/ROW]
[ROW][C]68[/C][C]820[/C][C]825.341[/C][C]915.417[/C][C]0.901602[/C][C]0.993529[/C][/ROW]
[ROW][C]69[/C][C]790[/C][C]792.113[/C][C]917.083[/C][C]0.86373[/C][C]0.997333[/C][/ROW]
[ROW][C]70[/C][C]820[/C][C]874.879[/C][C]922.5[/C][C]0.948378[/C][C]0.937273[/C][/ROW]
[ROW][C]71[/C][C]1130[/C][C]1058.21[/C][C]926.25[/C][C]1.14247[/C][C]1.06784[/C][/ROW]
[ROW][C]72[/C][C]800[/C][C]870.914[/C][C]929.583[/C][C]0.936886[/C][C]0.918575[/C][/ROW]
[ROW][C]73[/C][C]890[/C][C]891.343[/C][C]934.583[/C][C]0.953733[/C][C]0.998494[/C][/ROW]
[ROW][C]74[/C][C]810[/C][C]818.607[/C][C]935.417[/C][C]0.875125[/C][C]0.989486[/C][/ROW]
[ROW][C]75[/C][C]950[/C][C]948.955[/C][C]934.583[/C][C]1.01538[/C][C]1.0011[/C][/ROW]
[ROW][C]76[/C][C]1090[/C][C]1047.85[/C][C]936.25[/C][C]1.1192[/C][C]1.04022[/C][/ROW]
[ROW][C]77[/C][C]1090[/C][C]1056.22[/C][C]941.667[/C][C]1.12165[/C][C]1.03199[/C][/ROW]
[ROW][C]78[/C][C]850[/C][C]825.263[/C][C]945.833[/C][C]0.872525[/C][C]1.02997[/C][/ROW]
[ROW][C]79[/C][C]1200[/C][C]1183.74[/C][C]947.5[/C][C]1.24933[/C][C]1.01374[/C][/ROW]
[ROW][C]80[/C][C]790[/C][C]851.638[/C][C]944.583[/C][C]0.901602[/C][C]0.927624[/C][/ROW]
[ROW][C]81[/C][C]800[/C][C]814.786[/C][C]943.333[/C][C]0.86373[/C][C]0.981853[/C][/ROW]
[ROW][C]82[/C][C]850[/C][C]895.822[/C][C]944.583[/C][C]0.948378[/C][C]0.948849[/C][/ROW]
[ROW][C]83[/C][C]1230[/C][C]1072.49[/C][C]938.75[/C][C]1.14247[/C][C]1.14686[/C][/ROW]
[ROW][C]84[/C][C]800[/C][C]875.208[/C][C]934.167[/C][C]0.936886[/C][C]0.914068[/C][/ROW]
[ROW][C]85[/C][C]930[/C][C]889.753[/C][C]932.917[/C][C]0.953733[/C][C]1.04523[/C][/ROW]
[ROW][C]86[/C][C]700[/C][C]813.502[/C][C]929.583[/C][C]0.875125[/C][C]0.860478[/C][/ROW]
[ROW][C]87[/C][C]1030[/C][C]941.339[/C][C]927.083[/C][C]1.01538[/C][C]1.09419[/C][/ROW]
[ROW][C]88[/C][C]1040[/C][C]1038.99[/C][C]928.333[/C][C]1.1192[/C][C]1.00097[/C][/ROW]
[ROW][C]89[/C][C]1000[/C][C]1040.33[/C][C]927.5[/C][C]1.12165[/C][C]0.961237[/C][/ROW]
[ROW][C]90[/C][C]830[/C][C]807.812[/C][C]925.833[/C][C]0.872525[/C][C]1.02747[/C][/ROW]
[ROW][C]91[/C][C]1190[/C][C]1158.75[/C][C]927.5[/C][C]1.24933[/C][C]1.02696[/C][/ROW]
[ROW][C]92[/C][C]720[/C][C]837.362[/C][C]928.75[/C][C]0.901602[/C][C]0.859843[/C][/ROW]
[ROW][C]93[/C][C]810[/C][C]801.11[/C][C]927.5[/C][C]0.86373[/C][C]1.0111[/C][/ROW]
[ROW][C]94[/C][C]870[/C][C]878.435[/C][C]926.25[/C][C]0.948378[/C][C]0.990398[/C][/ROW]
[ROW][C]95[/C][C]1190[/C][C]1055.35[/C][C]923.75[/C][C]1.14247[/C][C]1.12758[/C][/ROW]
[ROW][C]96[/C][C]800[/C][C]863.497[/C][C]921.667[/C][C]0.936886[/C][C]0.926465[/C][/ROW]
[ROW][C]97[/C][C]970[/C][C]877.434[/C][C]920[/C][C]0.953733[/C][C]1.1055[/C][/ROW]
[ROW][C]98[/C][C]690[/C][C]804.75[/C][C]919.583[/C][C]0.875125[/C][C]0.857409[/C][/ROW]
[ROW][C]99[/C][C]1010[/C][C]936.262[/C][C]922.083[/C][C]1.01538[/C][C]1.07876[/C][/ROW]
[ROW][C]100[/C][C]1030[/C][C]1033.86[/C][C]923.75[/C][C]1.1192[/C][C]0.996266[/C][/ROW]
[ROW][C]101[/C][C]950[/C][C]1037.52[/C][C]925[/C][C]1.12165[/C][C]0.915643[/C][/ROW]
[ROW][C]102[/C][C]830[/C][C]808.903[/C][C]927.083[/C][C]0.872525[/C][C]1.02608[/C][/ROW]
[ROW][C]103[/C][C]1150[/C][C]NA[/C][C]NA[/C][C]1.24933[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]750[/C][C]NA[/C][C]NA[/C][C]0.901602[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]840[/C][C]NA[/C][C]NA[/C][C]0.86373[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]880[/C][C]NA[/C][C]NA[/C][C]0.948378[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]1210[/C][C]NA[/C][C]NA[/C][C]1.14247[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]830[/C][C]NA[/C][C]NA[/C][C]0.936886[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235691&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	840	NA	NA	0.953733	NA
2	880	NA	NA	0.875125	NA
3	930	NA	NA	1.01538	NA
4	920	NA	NA	1.1192	NA
5	940	NA	NA	1.12165	NA
6	880	NA	NA	0.872525	NA
7	980	1139.49	912.083	1.24933	0.860031
8	860	822.711	912.5	0.901602	1.04532
9	900	787.434	911.667	0.86373	1.14295
10	930	866.976	914.167	0.948378	1.07269
11	870	1050.59	919.583	1.14247	0.828103
12	1000	863.497	921.667	0.936886	1.15808
13	870	884.587	927.5	0.953733	0.98351
14	860	818.242	935	0.875125	1.05103
15	930	945.993	931.667	1.01538	0.983094
16	980	1036.66	926.25	1.1192	0.945345
17	1010	1038.92	926.25	1.12165	0.972159
18	860	809.267	927.5	0.872525	1.06269
19	1140	1159.8	928.333	1.24933	0.982932
20	880	838.865	930.417	0.901602	1.04904
21	800	802.55	929.167	0.86373	0.996823
22	900	879.621	927.5	0.948378	1.02317
23	900	1062.5	930	1.14247	0.847063
24	1000	870.133	928.75	0.936886	1.14925
25	890	883.792	926.667	0.953733	1.00702
26	890	809.855	925.417	0.875125	1.09896
27	870	934.57	920.417	1.01538	0.930909
28	1000	1029.2	919.583	1.1192	0.971631
29	1050	1037.52	925	1.12165	1.01203
30	790	806.722	924.583	0.872525	0.979272
31	1160	1147.82	918.75	1.24933	1.01061
32	830	825.341	915.417	0.901602	1.00564
33	730	789.953	914.583	0.86373	0.924105
34	950	868.951	916.25	0.948378	1.09327
35	980	1048.69	917.917	1.14247	0.934499
36	910	859.593	917.5	0.936886	1.05864
37	840	873.46	915.833	0.953733	0.961692
38	860	802.927	917.5	0.875125	1.07108
39	880	934.57	920.417	1.01538	0.941609
40	1030	1026.4	917.083	1.1192	1.00351
41	1060	1027.71	916.25	1.12165	1.03142
42	770	799.451	916.25	0.872525	0.963161
43	1140	1139.49	912.083	1.24933	1.00044
44	890	820.082	909.583	0.901602	1.08526
45	740	785.995	910	0.86373	0.941482
46	860	866.185	913.333	0.948378	0.992859
47	1050	1044.41	914.167	1.14247	1.00536
48	840	854.518	912.083	0.936886	0.98301
49	810	873.063	915.417	0.953733	0.927768
50	830	803.657	918.333	0.875125	1.03278
51	920	932.878	918.75	1.01538	0.986196
52	1070	1028.26	918.75	1.1192	1.04059
53	1040	1029.58	917.917	1.12165	1.01012
54	740	799.087	915.833	0.872525	0.926057
55	1250	1141.58	913.75	1.24933	1.09498
56	850	824.59	914.583	0.901602	1.03082
57	790	788.874	913.333	0.86373	1.00143
58	810	863.024	910	0.948378	0.93856
59	1080	1038.69	909.167	1.14247	1.03977
60	760	854.909	912.5	0.936886	0.888984
61	840	867.897	910	0.953733	0.967857
62	820	791.624	904.583	0.875125	1.03585
63	900	917.224	903.333	1.01538	0.981221
64	1010	1011.48	903.75	1.1192	0.99854
65	1080	1016.49	906.25	1.12165	1.06248
66	780	793.997	910	0.872525	0.982371
67	1150	1141.58	913.75	1.24933	1.00738
68	820	825.341	915.417	0.901602	0.993529
69	790	792.113	917.083	0.86373	0.997333
70	820	874.879	922.5	0.948378	0.937273
71	1130	1058.21	926.25	1.14247	1.06784
72	800	870.914	929.583	0.936886	0.918575
73	890	891.343	934.583	0.953733	0.998494
74	810	818.607	935.417	0.875125	0.989486
75	950	948.955	934.583	1.01538	1.0011
76	1090	1047.85	936.25	1.1192	1.04022
77	1090	1056.22	941.667	1.12165	1.03199
78	850	825.263	945.833	0.872525	1.02997
79	1200	1183.74	947.5	1.24933	1.01374
80	790	851.638	944.583	0.901602	0.927624
81	800	814.786	943.333	0.86373	0.981853
82	850	895.822	944.583	0.948378	0.948849
83	1230	1072.49	938.75	1.14247	1.14686
84	800	875.208	934.167	0.936886	0.914068
85	930	889.753	932.917	0.953733	1.04523
86	700	813.502	929.583	0.875125	0.860478
87	1030	941.339	927.083	1.01538	1.09419
88	1040	1038.99	928.333	1.1192	1.00097
89	1000	1040.33	927.5	1.12165	0.961237
90	830	807.812	925.833	0.872525	1.02747
91	1190	1158.75	927.5	1.24933	1.02696
92	720	837.362	928.75	0.901602	0.859843
93	810	801.11	927.5	0.86373	1.0111
94	870	878.435	926.25	0.948378	0.990398
95	1190	1055.35	923.75	1.14247	1.12758
96	800	863.497	921.667	0.936886	0.926465
97	970	877.434	920	0.953733	1.1055
98	690	804.75	919.583	0.875125	0.857409
99	1010	936.262	922.083	1.01538	1.07876
100	1030	1033.86	923.75	1.1192	0.996266
101	950	1037.52	925	1.12165	0.915643
102	830	808.903	927.083	0.872525	1.02608
103	1150	NA	NA	1.24933	NA
104	750	NA	NA	0.901602	NA
105	840	NA	NA	0.86373	NA
106	880	NA	NA	0.948378	NA
107	1210	NA	NA	1.14247	NA
108	830	NA	NA	0.936886	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 = Bezoekers Rosengart Museum ; par2 = niet gekend ; par3 = Aantal bezoekers Rosengart Museum ; par4 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- '12'
par1 <- 'additive'
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