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rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 19 Dec 2010 20:09:32 +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/2010/Dec/19/t129278923699r8l1ym2yp4xhz.htm/, Retrieved Sun, 05 May 2024 05:38:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112729, Retrieved Sun, 05 May 2024 05:38:16 +0000

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Estimated Impact

137

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

-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
-  M D  [Classical Decomposition] [WS8 - Decompositi...] [2010-11-27 10:08:48] [4a7069087cf9e0eda253aeed7d8c30d6]
-    D    [Classical Decomposition] [Paper - Ontleden ...] [2010-11-28 19:03:27] [4a7069087cf9e0eda253aeed7d8c30d6]
- R  D        [Classical Decomposition] [Classical Decompo...] [2010-12-19 20:09:32] [039869833c16fe697975601e6b065e0f] [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	'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112729&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112729&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112729&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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1038	NA	NA	83.3981481481482	NA
2	934	NA	NA	-119.837962962963	NA
3	988	NA	NA	4.84259259259255	NA
4	870	NA	NA	-66.9351851851852	NA
5	854	NA	NA	-83.3657407407408	NA
6	834	NA	NA	-105.060185185185	NA
7	872	911.62037037037	961.25	-49.6296296296296	-39.6203703703703
8	954	862.662037037037	950.791666666667	-88.1296296296296	91.337962962963
9	870	928.912037037037	948.541666666667	-19.6296296296296	-58.912037037037
10	1238	1140.77314814815	954	186.773148148148	97.226851851852
11	1082	1086.28703703704	961.458333333333	124.828703703704	-4.28703703703695
12	1053	1099.7037037037	966.958333333333	132.74537037037	-46.7037037037036
13	934	1047.89814814815	964.5	83.3981481481482	-113.898148148148
14	787	838.49537037037	958.333333333333	-119.837962962963	-51.4953703703703
15	1081	959.800925925926	954.958333333333	4.84259259259255	121.199074074074
16	908	882.731481481482	949.666666666667	-66.9351851851852	25.2685185185185
17	995	856.467592592593	939.833333333333	-83.3657407407408	138.532407407408
18	825	826.064814814815	931.125	-105.060185185185	-1.06481481481478
19	822	883.412037037037	933.041666666667	-49.6296296296296	-61.412037037037
20	856	857.162037037037	945.291666666667	-88.1296296296296	-1.16203703703695
21	887	924.662037037037	944.291666666667	-19.6296296296296	-37.662037037037
22	1094	1124.56481481481	937.791666666667	186.773148148148	-30.5648148148148
23	990	1058.5787037037	933.75	124.828703703704	-68.5787037037037
24	936	1068.5787037037	935.833333333333	132.74537037037	-132.578703703704
25	1097	1036.35648148148	952.958333333333	83.3981481481482	60.6435185185185
26	918	850.162037037037	970	-119.837962962963	67.8379629629633
27	926	988.50925925926	983.666666666667	4.84259259259255	-62.5092592592591
28	907	928.398148148148	995.333333333333	-66.9351851851852	-21.398148148148
29	899	921.217592592592	1004.58333333333	-83.3657407407408	-22.2175925925925
30	971	910.356481481481	1015.41666666667	-105.060185185185	60.6435185185187
31	1087	980.412037037037	1030.04166666667	-49.6296296296296	106.587962962963
32	1000	957.203703703704	1045.33333333333	-88.1296296296296	42.7962962962963
33	1071	1042.74537037037	1062.375	-19.6296296296296	28.2546296296296
34	1190	1272.77314814815	1086	186.773148148148	-82.7731481481482
35	1116	1233.91203703704	1109.08333333333	124.828703703704	-117.912037037037
36	1070	1263.74537037037	1131	132.74537037037	-193.74537037037
37	1314	1237.56481481481	1154.16666666667	83.3981481481482	76.4351851851852
38	1068	1061.16203703704	1181	-119.837962962963	6.83796296296305
39	1185	1220.50925925926	1215.66666666667	4.84259259259255	-35.5092592592594
40	1215	1195.68981481481	1262.625	-66.9351851851852	19.3101851851852
41	1145	1238.13425925926	1321.5	-83.3657407407408	-93.1342592592591
42	1251	1287.39814814815	1392.45833333333	-105.060185185185	-36.398148148148
43	1363	1384.99537037037	1434.625	-49.6296296296296	-21.9953703703704
44	1368	1386.4537037037	1474.58333333333	-88.1296296296296	-18.4537037037037
45	1535	1502.41203703704	1522.04166666667	-19.6296296296296	32.587962962963
46	1853	1716.48148148148	1529.70833333333	186.773148148148	136.518518518519
47	1866	1656.3287037037	1531.5	124.828703703704	209.671296296296
48	2023	1673.49537037037	1540.75	132.74537037037	349.50462962963
49	1373	NA	1553.25	NA	NA
50	1968	NA	1577.45833333333	NA	NA
51	1424	NA	1609.79166666667	NA	NA
52	1160	NA	1634.54166666667	NA	NA
53	1243	NA	1649.58333333333	NA	NA
54	1375	NA	NA	NA	NA
55	1539	NA	NA	NA	NA
56	1773	NA	NA	NA	NA
57	1906	NA	NA	NA	NA
58	2076	NA	NA	NA	NA
59	2004	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1038 & NA & NA & 83.3981481481482 & NA \tabularnewline
2 & 934 & NA & NA & -119.837962962963 & NA \tabularnewline
3 & 988 & NA & NA & 4.84259259259255 & NA \tabularnewline
4 & 870 & NA & NA & -66.9351851851852 & NA \tabularnewline
5 & 854 & NA & NA & -83.3657407407408 & NA \tabularnewline
6 & 834 & NA & NA & -105.060185185185 & NA \tabularnewline
7 & 872 & 911.62037037037 & 961.25 & -49.6296296296296 & -39.6203703703703 \tabularnewline
8 & 954 & 862.662037037037 & 950.791666666667 & -88.1296296296296 & 91.337962962963 \tabularnewline
9 & 870 & 928.912037037037 & 948.541666666667 & -19.6296296296296 & -58.912037037037 \tabularnewline
10 & 1238 & 1140.77314814815 & 954 & 186.773148148148 & 97.226851851852 \tabularnewline
11 & 1082 & 1086.28703703704 & 961.458333333333 & 124.828703703704 & -4.28703703703695 \tabularnewline
12 & 1053 & 1099.7037037037 & 966.958333333333 & 132.74537037037 & -46.7037037037036 \tabularnewline
13 & 934 & 1047.89814814815 & 964.5 & 83.3981481481482 & -113.898148148148 \tabularnewline
14 & 787 & 838.49537037037 & 958.333333333333 & -119.837962962963 & -51.4953703703703 \tabularnewline
15 & 1081 & 959.800925925926 & 954.958333333333 & 4.84259259259255 & 121.199074074074 \tabularnewline
16 & 908 & 882.731481481482 & 949.666666666667 & -66.9351851851852 & 25.2685185185185 \tabularnewline
17 & 995 & 856.467592592593 & 939.833333333333 & -83.3657407407408 & 138.532407407408 \tabularnewline
18 & 825 & 826.064814814815 & 931.125 & -105.060185185185 & -1.06481481481478 \tabularnewline
19 & 822 & 883.412037037037 & 933.041666666667 & -49.6296296296296 & -61.412037037037 \tabularnewline
20 & 856 & 857.162037037037 & 945.291666666667 & -88.1296296296296 & -1.16203703703695 \tabularnewline
21 & 887 & 924.662037037037 & 944.291666666667 & -19.6296296296296 & -37.662037037037 \tabularnewline
22 & 1094 & 1124.56481481481 & 937.791666666667 & 186.773148148148 & -30.5648148148148 \tabularnewline
23 & 990 & 1058.5787037037 & 933.75 & 124.828703703704 & -68.5787037037037 \tabularnewline
24 & 936 & 1068.5787037037 & 935.833333333333 & 132.74537037037 & -132.578703703704 \tabularnewline
25 & 1097 & 1036.35648148148 & 952.958333333333 & 83.3981481481482 & 60.6435185185185 \tabularnewline
26 & 918 & 850.162037037037 & 970 & -119.837962962963 & 67.8379629629633 \tabularnewline
27 & 926 & 988.50925925926 & 983.666666666667 & 4.84259259259255 & -62.5092592592591 \tabularnewline
28 & 907 & 928.398148148148 & 995.333333333333 & -66.9351851851852 & -21.398148148148 \tabularnewline
29 & 899 & 921.217592592592 & 1004.58333333333 & -83.3657407407408 & -22.2175925925925 \tabularnewline
30 & 971 & 910.356481481481 & 1015.41666666667 & -105.060185185185 & 60.6435185185187 \tabularnewline
31 & 1087 & 980.412037037037 & 1030.04166666667 & -49.6296296296296 & 106.587962962963 \tabularnewline
32 & 1000 & 957.203703703704 & 1045.33333333333 & -88.1296296296296 & 42.7962962962963 \tabularnewline
33 & 1071 & 1042.74537037037 & 1062.375 & -19.6296296296296 & 28.2546296296296 \tabularnewline
34 & 1190 & 1272.77314814815 & 1086 & 186.773148148148 & -82.7731481481482 \tabularnewline
35 & 1116 & 1233.91203703704 & 1109.08333333333 & 124.828703703704 & -117.912037037037 \tabularnewline
36 & 1070 & 1263.74537037037 & 1131 & 132.74537037037 & -193.74537037037 \tabularnewline
37 & 1314 & 1237.56481481481 & 1154.16666666667 & 83.3981481481482 & 76.4351851851852 \tabularnewline
38 & 1068 & 1061.16203703704 & 1181 & -119.837962962963 & 6.83796296296305 \tabularnewline
39 & 1185 & 1220.50925925926 & 1215.66666666667 & 4.84259259259255 & -35.5092592592594 \tabularnewline
40 & 1215 & 1195.68981481481 & 1262.625 & -66.9351851851852 & 19.3101851851852 \tabularnewline
41 & 1145 & 1238.13425925926 & 1321.5 & -83.3657407407408 & -93.1342592592591 \tabularnewline
42 & 1251 & 1287.39814814815 & 1392.45833333333 & -105.060185185185 & -36.398148148148 \tabularnewline
43 & 1363 & 1384.99537037037 & 1434.625 & -49.6296296296296 & -21.9953703703704 \tabularnewline
44 & 1368 & 1386.4537037037 & 1474.58333333333 & -88.1296296296296 & -18.4537037037037 \tabularnewline
45 & 1535 & 1502.41203703704 & 1522.04166666667 & -19.6296296296296 & 32.587962962963 \tabularnewline
46 & 1853 & 1716.48148148148 & 1529.70833333333 & 186.773148148148 & 136.518518518519 \tabularnewline
47 & 1866 & 1656.3287037037 & 1531.5 & 124.828703703704 & 209.671296296296 \tabularnewline
48 & 2023 & 1673.49537037037 & 1540.75 & 132.74537037037 & 349.50462962963 \tabularnewline
49 & 1373 & NA & 1553.25 & NA & NA \tabularnewline
50 & 1968 & NA & 1577.45833333333 & NA & NA \tabularnewline
51 & 1424 & NA & 1609.79166666667 & NA & NA \tabularnewline
52 & 1160 & NA & 1634.54166666667 & NA & NA \tabularnewline
53 & 1243 & NA & 1649.58333333333 & NA & NA \tabularnewline
54 & 1375 & NA & NA & NA & NA \tabularnewline
55 & 1539 & NA & NA & NA & NA \tabularnewline
56 & 1773 & NA & NA & NA & NA \tabularnewline
57 & 1906 & NA & NA & NA & NA \tabularnewline
58 & 2076 & NA & NA & NA & NA \tabularnewline
59 & 2004 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112729&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]1038[/C][C]NA[/C][C]NA[/C][C]83.3981481481482[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]934[/C][C]NA[/C][C]NA[/C][C]-119.837962962963[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]988[/C][C]NA[/C][C]NA[/C][C]4.84259259259255[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]870[/C][C]NA[/C][C]NA[/C][C]-66.9351851851852[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]854[/C][C]NA[/C][C]NA[/C][C]-83.3657407407408[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]834[/C][C]NA[/C][C]NA[/C][C]-105.060185185185[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]872[/C][C]911.62037037037[/C][C]961.25[/C][C]-49.6296296296296[/C][C]-39.6203703703703[/C][/ROW]
[ROW][C]8[/C][C]954[/C][C]862.662037037037[/C][C]950.791666666667[/C][C]-88.1296296296296[/C][C]91.337962962963[/C][/ROW]
[ROW][C]9[/C][C]870[/C][C]928.912037037037[/C][C]948.541666666667[/C][C]-19.6296296296296[/C][C]-58.912037037037[/C][/ROW]
[ROW][C]10[/C][C]1238[/C][C]1140.77314814815[/C][C]954[/C][C]186.773148148148[/C][C]97.226851851852[/C][/ROW]
[ROW][C]11[/C][C]1082[/C][C]1086.28703703704[/C][C]961.458333333333[/C][C]124.828703703704[/C][C]-4.28703703703695[/C][/ROW]
[ROW][C]12[/C][C]1053[/C][C]1099.7037037037[/C][C]966.958333333333[/C][C]132.74537037037[/C][C]-46.7037037037036[/C][/ROW]
[ROW][C]13[/C][C]934[/C][C]1047.89814814815[/C][C]964.5[/C][C]83.3981481481482[/C][C]-113.898148148148[/C][/ROW]
[ROW][C]14[/C][C]787[/C][C]838.49537037037[/C][C]958.333333333333[/C][C]-119.837962962963[/C][C]-51.4953703703703[/C][/ROW]
[ROW][C]15[/C][C]1081[/C][C]959.800925925926[/C][C]954.958333333333[/C][C]4.84259259259255[/C][C]121.199074074074[/C][/ROW]
[ROW][C]16[/C][C]908[/C][C]882.731481481482[/C][C]949.666666666667[/C][C]-66.9351851851852[/C][C]25.2685185185185[/C][/ROW]
[ROW][C]17[/C][C]995[/C][C]856.467592592593[/C][C]939.833333333333[/C][C]-83.3657407407408[/C][C]138.532407407408[/C][/ROW]
[ROW][C]18[/C][C]825[/C][C]826.064814814815[/C][C]931.125[/C][C]-105.060185185185[/C][C]-1.06481481481478[/C][/ROW]
[ROW][C]19[/C][C]822[/C][C]883.412037037037[/C][C]933.041666666667[/C][C]-49.6296296296296[/C][C]-61.412037037037[/C][/ROW]
[ROW][C]20[/C][C]856[/C][C]857.162037037037[/C][C]945.291666666667[/C][C]-88.1296296296296[/C][C]-1.16203703703695[/C][/ROW]
[ROW][C]21[/C][C]887[/C][C]924.662037037037[/C][C]944.291666666667[/C][C]-19.6296296296296[/C][C]-37.662037037037[/C][/ROW]
[ROW][C]22[/C][C]1094[/C][C]1124.56481481481[/C][C]937.791666666667[/C][C]186.773148148148[/C][C]-30.5648148148148[/C][/ROW]
[ROW][C]23[/C][C]990[/C][C]1058.5787037037[/C][C]933.75[/C][C]124.828703703704[/C][C]-68.5787037037037[/C][/ROW]
[ROW][C]24[/C][C]936[/C][C]1068.5787037037[/C][C]935.833333333333[/C][C]132.74537037037[/C][C]-132.578703703704[/C][/ROW]
[ROW][C]25[/C][C]1097[/C][C]1036.35648148148[/C][C]952.958333333333[/C][C]83.3981481481482[/C][C]60.6435185185185[/C][/ROW]
[ROW][C]26[/C][C]918[/C][C]850.162037037037[/C][C]970[/C][C]-119.837962962963[/C][C]67.8379629629633[/C][/ROW]
[ROW][C]27[/C][C]926[/C][C]988.50925925926[/C][C]983.666666666667[/C][C]4.84259259259255[/C][C]-62.5092592592591[/C][/ROW]
[ROW][C]28[/C][C]907[/C][C]928.398148148148[/C][C]995.333333333333[/C][C]-66.9351851851852[/C][C]-21.398148148148[/C][/ROW]
[ROW][C]29[/C][C]899[/C][C]921.217592592592[/C][C]1004.58333333333[/C][C]-83.3657407407408[/C][C]-22.2175925925925[/C][/ROW]
[ROW][C]30[/C][C]971[/C][C]910.356481481481[/C][C]1015.41666666667[/C][C]-105.060185185185[/C][C]60.6435185185187[/C][/ROW]
[ROW][C]31[/C][C]1087[/C][C]980.412037037037[/C][C]1030.04166666667[/C][C]-49.6296296296296[/C][C]106.587962962963[/C][/ROW]
[ROW][C]32[/C][C]1000[/C][C]957.203703703704[/C][C]1045.33333333333[/C][C]-88.1296296296296[/C][C]42.7962962962963[/C][/ROW]
[ROW][C]33[/C][C]1071[/C][C]1042.74537037037[/C][C]1062.375[/C][C]-19.6296296296296[/C][C]28.2546296296296[/C][/ROW]
[ROW][C]34[/C][C]1190[/C][C]1272.77314814815[/C][C]1086[/C][C]186.773148148148[/C][C]-82.7731481481482[/C][/ROW]
[ROW][C]35[/C][C]1116[/C][C]1233.91203703704[/C][C]1109.08333333333[/C][C]124.828703703704[/C][C]-117.912037037037[/C][/ROW]
[ROW][C]36[/C][C]1070[/C][C]1263.74537037037[/C][C]1131[/C][C]132.74537037037[/C][C]-193.74537037037[/C][/ROW]
[ROW][C]37[/C][C]1314[/C][C]1237.56481481481[/C][C]1154.16666666667[/C][C]83.3981481481482[/C][C]76.4351851851852[/C][/ROW]
[ROW][C]38[/C][C]1068[/C][C]1061.16203703704[/C][C]1181[/C][C]-119.837962962963[/C][C]6.83796296296305[/C][/ROW]
[ROW][C]39[/C][C]1185[/C][C]1220.50925925926[/C][C]1215.66666666667[/C][C]4.84259259259255[/C][C]-35.5092592592594[/C][/ROW]
[ROW][C]40[/C][C]1215[/C][C]1195.68981481481[/C][C]1262.625[/C][C]-66.9351851851852[/C][C]19.3101851851852[/C][/ROW]
[ROW][C]41[/C][C]1145[/C][C]1238.13425925926[/C][C]1321.5[/C][C]-83.3657407407408[/C][C]-93.1342592592591[/C][/ROW]
[ROW][C]42[/C][C]1251[/C][C]1287.39814814815[/C][C]1392.45833333333[/C][C]-105.060185185185[/C][C]-36.398148148148[/C][/ROW]
[ROW][C]43[/C][C]1363[/C][C]1384.99537037037[/C][C]1434.625[/C][C]-49.6296296296296[/C][C]-21.9953703703704[/C][/ROW]
[ROW][C]44[/C][C]1368[/C][C]1386.4537037037[/C][C]1474.58333333333[/C][C]-88.1296296296296[/C][C]-18.4537037037037[/C][/ROW]
[ROW][C]45[/C][C]1535[/C][C]1502.41203703704[/C][C]1522.04166666667[/C][C]-19.6296296296296[/C][C]32.587962962963[/C][/ROW]
[ROW][C]46[/C][C]1853[/C][C]1716.48148148148[/C][C]1529.70833333333[/C][C]186.773148148148[/C][C]136.518518518519[/C][/ROW]
[ROW][C]47[/C][C]1866[/C][C]1656.3287037037[/C][C]1531.5[/C][C]124.828703703704[/C][C]209.671296296296[/C][/ROW]
[ROW][C]48[/C][C]2023[/C][C]1673.49537037037[/C][C]1540.75[/C][C]132.74537037037[/C][C]349.50462962963[/C][/ROW]
[ROW][C]49[/C][C]1373[/C][C]NA[/C][C]1553.25[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]1968[/C][C]NA[/C][C]1577.45833333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]1424[/C][C]NA[/C][C]1609.79166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]1160[/C][C]NA[/C][C]1634.54166666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]1243[/C][C]NA[/C][C]1649.58333333333[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]1375[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]1539[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]1773[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]1906[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]2076[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]2004[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112729&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112729&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	1038	NA	NA	83.3981481481482	NA
2	934	NA	NA	-119.837962962963	NA
3	988	NA	NA	4.84259259259255	NA
4	870	NA	NA	-66.9351851851852	NA
5	854	NA	NA	-83.3657407407408	NA
6	834	NA	NA	-105.060185185185	NA
7	872	911.62037037037	961.25	-49.6296296296296	-39.6203703703703
8	954	862.662037037037	950.791666666667	-88.1296296296296	91.337962962963
9	870	928.912037037037	948.541666666667	-19.6296296296296	-58.912037037037
10	1238	1140.77314814815	954	186.773148148148	97.226851851852
11	1082	1086.28703703704	961.458333333333	124.828703703704	-4.28703703703695
12	1053	1099.7037037037	966.958333333333	132.74537037037	-46.7037037037036
13	934	1047.89814814815	964.5	83.3981481481482	-113.898148148148
14	787	838.49537037037	958.333333333333	-119.837962962963	-51.4953703703703
15	1081	959.800925925926	954.958333333333	4.84259259259255	121.199074074074
16	908	882.731481481482	949.666666666667	-66.9351851851852	25.2685185185185
17	995	856.467592592593	939.833333333333	-83.3657407407408	138.532407407408
18	825	826.064814814815	931.125	-105.060185185185	-1.06481481481478
19	822	883.412037037037	933.041666666667	-49.6296296296296	-61.412037037037
20	856	857.162037037037	945.291666666667	-88.1296296296296	-1.16203703703695
21	887	924.662037037037	944.291666666667	-19.6296296296296	-37.662037037037
22	1094	1124.56481481481	937.791666666667	186.773148148148	-30.5648148148148
23	990	1058.5787037037	933.75	124.828703703704	-68.5787037037037
24	936	1068.5787037037	935.833333333333	132.74537037037	-132.578703703704
25	1097	1036.35648148148	952.958333333333	83.3981481481482	60.6435185185185
26	918	850.162037037037	970	-119.837962962963	67.8379629629633
27	926	988.50925925926	983.666666666667	4.84259259259255	-62.5092592592591
28	907	928.398148148148	995.333333333333	-66.9351851851852	-21.398148148148
29	899	921.217592592592	1004.58333333333	-83.3657407407408	-22.2175925925925
30	971	910.356481481481	1015.41666666667	-105.060185185185	60.6435185185187
31	1087	980.412037037037	1030.04166666667	-49.6296296296296	106.587962962963
32	1000	957.203703703704	1045.33333333333	-88.1296296296296	42.7962962962963
33	1071	1042.74537037037	1062.375	-19.6296296296296	28.2546296296296
34	1190	1272.77314814815	1086	186.773148148148	-82.7731481481482
35	1116	1233.91203703704	1109.08333333333	124.828703703704	-117.912037037037
36	1070	1263.74537037037	1131	132.74537037037	-193.74537037037
37	1314	1237.56481481481	1154.16666666667	83.3981481481482	76.4351851851852
38	1068	1061.16203703704	1181	-119.837962962963	6.83796296296305
39	1185	1220.50925925926	1215.66666666667	4.84259259259255	-35.5092592592594
40	1215	1195.68981481481	1262.625	-66.9351851851852	19.3101851851852
41	1145	1238.13425925926	1321.5	-83.3657407407408	-93.1342592592591
42	1251	1287.39814814815	1392.45833333333	-105.060185185185	-36.398148148148
43	1363	1384.99537037037	1434.625	-49.6296296296296	-21.9953703703704
44	1368	1386.4537037037	1474.58333333333	-88.1296296296296	-18.4537037037037
45	1535	1502.41203703704	1522.04166666667	-19.6296296296296	32.587962962963
46	1853	1716.48148148148	1529.70833333333	186.773148148148	136.518518518519
47	1866	1656.3287037037	1531.5	124.828703703704	209.671296296296
48	2023	1673.49537037037	1540.75	132.74537037037	349.50462962963
49	1373	NA	1553.25	NA	NA
50	1968	NA	1577.45833333333	NA	NA
51	1424	NA	1609.79166666667	NA	NA
52	1160	NA	1634.54166666667	NA	NA
53	1243	NA	1649.58333333333	NA	NA
54	1375	NA	NA	NA	NA
55	1539	NA	NA	NA	NA
56	1773	NA	NA	NA	NA
57	1906	NA	NA	NA	NA
58	2076	NA	NA	NA	NA
59	2004	NA	NA	NA	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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