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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 27 Nov 2014 11:53:46 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/27/t141708941077335jq4c6harj8.htm/, Retrieved Sun, 19 May 2024 20:29:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=259804, Retrieved Sun, 19 May 2024 20:29:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2014-11-27 11:53:46] [25af208440423f5cc2d7fa35cacd4ca5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3844,49
3720,98
3674,4
3857,62
3801,06
3504,37
3032,6
3047,03
2962,34
2197,82
2014,45
1862,83
1905,41
1810,99
1670,07
1864,44
2052,02
2029,6
2070,83
2293,41
2443,27
2513,17
2466,92
2502,66
2539,91
2482,6
2626,15
2656,32
2446,66
2467,38
2462,32
2504,58
2579,39
2649,24
2636,87
2613,94
2634,01
2711,94
2646,43
2717,79
2701,54
2572,98
2488,92
2204,91
2123,99
2149,1
2036,71
2048,32
2159,56
2267,79
2313,55
2247,3
2134,43
2114
2236,94
2345,39
2422,4
2385,96
2378,17
2457,13
2527,67
2530,03
2604,92
2596,8
2713,2
2574,82
2611,98
2768,46
2785,61
2859,27
2880,53
2824,5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259804&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259804&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259804&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
13844.49NANA-7.95463NA
23720.98NANA5.22996NA
33674.4NANA20.5781NA
43857.62NANA60.8448NA
53801.06NANA41.1554NA
63504.37NANA-31.8899NA
73032.63036.143045.87-9.73429-3.53654
83047.032917.42885.4931.9058129.631
92962.342800.352722.477.9567161.987
102197.822525.992555.83-29.8441-328.169
112014.452317.22399.91-82.7058-302.752
121862.832190.042265.58-75.542-327.21
131905.412156.12164.06-7.95463-250.695
141810.992097.812092.585.22996-286.825
151670.072060.132039.5620.5781-390.064
161864.442091.912031.0760.8448-227.473
172052.022104.222063.0641.1554-52.1958
182029.62076.682108.57-31.8899-47.083
192070.832151.942161.67-9.73429-81.1057
202293.4122482216.0931.905845.413
212443.272361.872283.9177.956781.4016
222513.172326.92356.74-29.8441186.271
232466.922323.482406.18-82.7058143.444
242502.662365.322440.87-75.542137.336
252539.912467.462475.42-7.9546372.4459
262482.62505.762500.535.22996-23.1595
272626.152535.58251520.578190.5719
282656.322587.192526.3460.844869.134
292446.662580.252539.0941.1554-133.587
302467.382518.922550.81-31.8899-51.5401
312462.322549.632559.37-9.73429-87.3132
322504.582604.752572.8431.9058-100.17
332579.392661.22583.2577.9567-81.8117
342649.242556.812586.65-29.844192.4329
352636.872517.132599.83-82.7058119.743
362613.942539.312614.85-75.54274.6295
372634.012612.412620.36-7.9546321.6038
382711.942614.212608.985.2299697.7271
392646.432598.12577.5220.578148.3302
402717.792598.552537.7160.8448119.238
412701.542533.022491.8641.1554168.523
422572.982411.42443.29-31.8899161.582
432488.922390.222399.95-9.7342998.703
442204.912393.582361.6831.9058-188.672
452123.992407.262329.377.9567-283.267
462149.12265.982295.83-29.8441-116.882
472036.712169.892252.59-82.7058-133.177
482048.322134.32209.84-75.542-85.9771
492159.562172.262180.22-7.95463-12.7012
502267.792180.82175.575.2299686.99
512313.552214.442193.8620.578199.1148
522247.322772216.1660.8448-29.7048
532134.432281.412240.2641.1554-146.982
5421142239.632271.52-31.8899-125.628
552236.942294.162303.89-9.73429-57.2153
562345.392362.062330.1531.9058-16.67
572422.42431.182353.2277.9567-8.77796
582385.962350.082379.92-29.844135.88
592378.172335.92418.6-82.705842.2737
602457.132386.382461.92-75.54270.7537
612527.672488.792496.75-7.9546338.8788
622530.032535.2325305.22996-5.20037
632604.922583.342562.7620.578121.5798
642596.82658.462597.6260.8448-61.6619
652713.22679.432638.2741.155433.7746
662574.822642.622674.51-31.8899-67.7989
672611.98NANA-9.73429NA
682768.46NANA31.9058NA
692785.61NANA77.9567NA
702859.27NANA-29.8441NA
712880.53NANA-82.7058NA
722824.5NANA-75.542NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 3844.49 & NA & NA & -7.95463 & NA \tabularnewline
2 & 3720.98 & NA & NA & 5.22996 & NA \tabularnewline
3 & 3674.4 & NA & NA & 20.5781 & NA \tabularnewline
4 & 3857.62 & NA & NA & 60.8448 & NA \tabularnewline
5 & 3801.06 & NA & NA & 41.1554 & NA \tabularnewline
6 & 3504.37 & NA & NA & -31.8899 & NA \tabularnewline
7 & 3032.6 & 3036.14 & 3045.87 & -9.73429 & -3.53654 \tabularnewline
8 & 3047.03 & 2917.4 & 2885.49 & 31.9058 & 129.631 \tabularnewline
9 & 2962.34 & 2800.35 & 2722.4 & 77.9567 & 161.987 \tabularnewline
10 & 2197.82 & 2525.99 & 2555.83 & -29.8441 & -328.169 \tabularnewline
11 & 2014.45 & 2317.2 & 2399.91 & -82.7058 & -302.752 \tabularnewline
12 & 1862.83 & 2190.04 & 2265.58 & -75.542 & -327.21 \tabularnewline
13 & 1905.41 & 2156.1 & 2164.06 & -7.95463 & -250.695 \tabularnewline
14 & 1810.99 & 2097.81 & 2092.58 & 5.22996 & -286.825 \tabularnewline
15 & 1670.07 & 2060.13 & 2039.56 & 20.5781 & -390.064 \tabularnewline
16 & 1864.44 & 2091.91 & 2031.07 & 60.8448 & -227.473 \tabularnewline
17 & 2052.02 & 2104.22 & 2063.06 & 41.1554 & -52.1958 \tabularnewline
18 & 2029.6 & 2076.68 & 2108.57 & -31.8899 & -47.083 \tabularnewline
19 & 2070.83 & 2151.94 & 2161.67 & -9.73429 & -81.1057 \tabularnewline
20 & 2293.41 & 2248 & 2216.09 & 31.9058 & 45.413 \tabularnewline
21 & 2443.27 & 2361.87 & 2283.91 & 77.9567 & 81.4016 \tabularnewline
22 & 2513.17 & 2326.9 & 2356.74 & -29.8441 & 186.271 \tabularnewline
23 & 2466.92 & 2323.48 & 2406.18 & -82.7058 & 143.444 \tabularnewline
24 & 2502.66 & 2365.32 & 2440.87 & -75.542 & 137.336 \tabularnewline
25 & 2539.91 & 2467.46 & 2475.42 & -7.95463 & 72.4459 \tabularnewline
26 & 2482.6 & 2505.76 & 2500.53 & 5.22996 & -23.1595 \tabularnewline
27 & 2626.15 & 2535.58 & 2515 & 20.5781 & 90.5719 \tabularnewline
28 & 2656.32 & 2587.19 & 2526.34 & 60.8448 & 69.134 \tabularnewline
29 & 2446.66 & 2580.25 & 2539.09 & 41.1554 & -133.587 \tabularnewline
30 & 2467.38 & 2518.92 & 2550.81 & -31.8899 & -51.5401 \tabularnewline
31 & 2462.32 & 2549.63 & 2559.37 & -9.73429 & -87.3132 \tabularnewline
32 & 2504.58 & 2604.75 & 2572.84 & 31.9058 & -100.17 \tabularnewline
33 & 2579.39 & 2661.2 & 2583.25 & 77.9567 & -81.8117 \tabularnewline
34 & 2649.24 & 2556.81 & 2586.65 & -29.8441 & 92.4329 \tabularnewline
35 & 2636.87 & 2517.13 & 2599.83 & -82.7058 & 119.743 \tabularnewline
36 & 2613.94 & 2539.31 & 2614.85 & -75.542 & 74.6295 \tabularnewline
37 & 2634.01 & 2612.41 & 2620.36 & -7.95463 & 21.6038 \tabularnewline
38 & 2711.94 & 2614.21 & 2608.98 & 5.22996 & 97.7271 \tabularnewline
39 & 2646.43 & 2598.1 & 2577.52 & 20.5781 & 48.3302 \tabularnewline
40 & 2717.79 & 2598.55 & 2537.71 & 60.8448 & 119.238 \tabularnewline
41 & 2701.54 & 2533.02 & 2491.86 & 41.1554 & 168.523 \tabularnewline
42 & 2572.98 & 2411.4 & 2443.29 & -31.8899 & 161.582 \tabularnewline
43 & 2488.92 & 2390.22 & 2399.95 & -9.73429 & 98.703 \tabularnewline
44 & 2204.91 & 2393.58 & 2361.68 & 31.9058 & -188.672 \tabularnewline
45 & 2123.99 & 2407.26 & 2329.3 & 77.9567 & -283.267 \tabularnewline
46 & 2149.1 & 2265.98 & 2295.83 & -29.8441 & -116.882 \tabularnewline
47 & 2036.71 & 2169.89 & 2252.59 & -82.7058 & -133.177 \tabularnewline
48 & 2048.32 & 2134.3 & 2209.84 & -75.542 & -85.9771 \tabularnewline
49 & 2159.56 & 2172.26 & 2180.22 & -7.95463 & -12.7012 \tabularnewline
50 & 2267.79 & 2180.8 & 2175.57 & 5.22996 & 86.99 \tabularnewline
51 & 2313.55 & 2214.44 & 2193.86 & 20.5781 & 99.1148 \tabularnewline
52 & 2247.3 & 2277 & 2216.16 & 60.8448 & -29.7048 \tabularnewline
53 & 2134.43 & 2281.41 & 2240.26 & 41.1554 & -146.982 \tabularnewline
54 & 2114 & 2239.63 & 2271.52 & -31.8899 & -125.628 \tabularnewline
55 & 2236.94 & 2294.16 & 2303.89 & -9.73429 & -57.2153 \tabularnewline
56 & 2345.39 & 2362.06 & 2330.15 & 31.9058 & -16.67 \tabularnewline
57 & 2422.4 & 2431.18 & 2353.22 & 77.9567 & -8.77796 \tabularnewline
58 & 2385.96 & 2350.08 & 2379.92 & -29.8441 & 35.88 \tabularnewline
59 & 2378.17 & 2335.9 & 2418.6 & -82.7058 & 42.2737 \tabularnewline
60 & 2457.13 & 2386.38 & 2461.92 & -75.542 & 70.7537 \tabularnewline
61 & 2527.67 & 2488.79 & 2496.75 & -7.95463 & 38.8788 \tabularnewline
62 & 2530.03 & 2535.23 & 2530 & 5.22996 & -5.20037 \tabularnewline
63 & 2604.92 & 2583.34 & 2562.76 & 20.5781 & 21.5798 \tabularnewline
64 & 2596.8 & 2658.46 & 2597.62 & 60.8448 & -61.6619 \tabularnewline
65 & 2713.2 & 2679.43 & 2638.27 & 41.1554 & 33.7746 \tabularnewline
66 & 2574.82 & 2642.62 & 2674.51 & -31.8899 & -67.7989 \tabularnewline
67 & 2611.98 & NA & NA & -9.73429 & NA \tabularnewline
68 & 2768.46 & NA & NA & 31.9058 & NA \tabularnewline
69 & 2785.61 & NA & NA & 77.9567 & NA \tabularnewline
70 & 2859.27 & NA & NA & -29.8441 & NA \tabularnewline
71 & 2880.53 & NA & NA & -82.7058 & NA \tabularnewline
72 & 2824.5 & NA & NA & -75.542 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259804&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]3844.49[/C][C]NA[/C][C]NA[/C][C]-7.95463[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3720.98[/C][C]NA[/C][C]NA[/C][C]5.22996[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3674.4[/C][C]NA[/C][C]NA[/C][C]20.5781[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3857.62[/C][C]NA[/C][C]NA[/C][C]60.8448[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3801.06[/C][C]NA[/C][C]NA[/C][C]41.1554[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3504.37[/C][C]NA[/C][C]NA[/C][C]-31.8899[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3032.6[/C][C]3036.14[/C][C]3045.87[/C][C]-9.73429[/C][C]-3.53654[/C][/ROW]
[ROW][C]8[/C][C]3047.03[/C][C]2917.4[/C][C]2885.49[/C][C]31.9058[/C][C]129.631[/C][/ROW]
[ROW][C]9[/C][C]2962.34[/C][C]2800.35[/C][C]2722.4[/C][C]77.9567[/C][C]161.987[/C][/ROW]
[ROW][C]10[/C][C]2197.82[/C][C]2525.99[/C][C]2555.83[/C][C]-29.8441[/C][C]-328.169[/C][/ROW]
[ROW][C]11[/C][C]2014.45[/C][C]2317.2[/C][C]2399.91[/C][C]-82.7058[/C][C]-302.752[/C][/ROW]
[ROW][C]12[/C][C]1862.83[/C][C]2190.04[/C][C]2265.58[/C][C]-75.542[/C][C]-327.21[/C][/ROW]
[ROW][C]13[/C][C]1905.41[/C][C]2156.1[/C][C]2164.06[/C][C]-7.95463[/C][C]-250.695[/C][/ROW]
[ROW][C]14[/C][C]1810.99[/C][C]2097.81[/C][C]2092.58[/C][C]5.22996[/C][C]-286.825[/C][/ROW]
[ROW][C]15[/C][C]1670.07[/C][C]2060.13[/C][C]2039.56[/C][C]20.5781[/C][C]-390.064[/C][/ROW]
[ROW][C]16[/C][C]1864.44[/C][C]2091.91[/C][C]2031.07[/C][C]60.8448[/C][C]-227.473[/C][/ROW]
[ROW][C]17[/C][C]2052.02[/C][C]2104.22[/C][C]2063.06[/C][C]41.1554[/C][C]-52.1958[/C][/ROW]
[ROW][C]18[/C][C]2029.6[/C][C]2076.68[/C][C]2108.57[/C][C]-31.8899[/C][C]-47.083[/C][/ROW]
[ROW][C]19[/C][C]2070.83[/C][C]2151.94[/C][C]2161.67[/C][C]-9.73429[/C][C]-81.1057[/C][/ROW]
[ROW][C]20[/C][C]2293.41[/C][C]2248[/C][C]2216.09[/C][C]31.9058[/C][C]45.413[/C][/ROW]
[ROW][C]21[/C][C]2443.27[/C][C]2361.87[/C][C]2283.91[/C][C]77.9567[/C][C]81.4016[/C][/ROW]
[ROW][C]22[/C][C]2513.17[/C][C]2326.9[/C][C]2356.74[/C][C]-29.8441[/C][C]186.271[/C][/ROW]
[ROW][C]23[/C][C]2466.92[/C][C]2323.48[/C][C]2406.18[/C][C]-82.7058[/C][C]143.444[/C][/ROW]
[ROW][C]24[/C][C]2502.66[/C][C]2365.32[/C][C]2440.87[/C][C]-75.542[/C][C]137.336[/C][/ROW]
[ROW][C]25[/C][C]2539.91[/C][C]2467.46[/C][C]2475.42[/C][C]-7.95463[/C][C]72.4459[/C][/ROW]
[ROW][C]26[/C][C]2482.6[/C][C]2505.76[/C][C]2500.53[/C][C]5.22996[/C][C]-23.1595[/C][/ROW]
[ROW][C]27[/C][C]2626.15[/C][C]2535.58[/C][C]2515[/C][C]20.5781[/C][C]90.5719[/C][/ROW]
[ROW][C]28[/C][C]2656.32[/C][C]2587.19[/C][C]2526.34[/C][C]60.8448[/C][C]69.134[/C][/ROW]
[ROW][C]29[/C][C]2446.66[/C][C]2580.25[/C][C]2539.09[/C][C]41.1554[/C][C]-133.587[/C][/ROW]
[ROW][C]30[/C][C]2467.38[/C][C]2518.92[/C][C]2550.81[/C][C]-31.8899[/C][C]-51.5401[/C][/ROW]
[ROW][C]31[/C][C]2462.32[/C][C]2549.63[/C][C]2559.37[/C][C]-9.73429[/C][C]-87.3132[/C][/ROW]
[ROW][C]32[/C][C]2504.58[/C][C]2604.75[/C][C]2572.84[/C][C]31.9058[/C][C]-100.17[/C][/ROW]
[ROW][C]33[/C][C]2579.39[/C][C]2661.2[/C][C]2583.25[/C][C]77.9567[/C][C]-81.8117[/C][/ROW]
[ROW][C]34[/C][C]2649.24[/C][C]2556.81[/C][C]2586.65[/C][C]-29.8441[/C][C]92.4329[/C][/ROW]
[ROW][C]35[/C][C]2636.87[/C][C]2517.13[/C][C]2599.83[/C][C]-82.7058[/C][C]119.743[/C][/ROW]
[ROW][C]36[/C][C]2613.94[/C][C]2539.31[/C][C]2614.85[/C][C]-75.542[/C][C]74.6295[/C][/ROW]
[ROW][C]37[/C][C]2634.01[/C][C]2612.41[/C][C]2620.36[/C][C]-7.95463[/C][C]21.6038[/C][/ROW]
[ROW][C]38[/C][C]2711.94[/C][C]2614.21[/C][C]2608.98[/C][C]5.22996[/C][C]97.7271[/C][/ROW]
[ROW][C]39[/C][C]2646.43[/C][C]2598.1[/C][C]2577.52[/C][C]20.5781[/C][C]48.3302[/C][/ROW]
[ROW][C]40[/C][C]2717.79[/C][C]2598.55[/C][C]2537.71[/C][C]60.8448[/C][C]119.238[/C][/ROW]
[ROW][C]41[/C][C]2701.54[/C][C]2533.02[/C][C]2491.86[/C][C]41.1554[/C][C]168.523[/C][/ROW]
[ROW][C]42[/C][C]2572.98[/C][C]2411.4[/C][C]2443.29[/C][C]-31.8899[/C][C]161.582[/C][/ROW]
[ROW][C]43[/C][C]2488.92[/C][C]2390.22[/C][C]2399.95[/C][C]-9.73429[/C][C]98.703[/C][/ROW]
[ROW][C]44[/C][C]2204.91[/C][C]2393.58[/C][C]2361.68[/C][C]31.9058[/C][C]-188.672[/C][/ROW]
[ROW][C]45[/C][C]2123.99[/C][C]2407.26[/C][C]2329.3[/C][C]77.9567[/C][C]-283.267[/C][/ROW]
[ROW][C]46[/C][C]2149.1[/C][C]2265.98[/C][C]2295.83[/C][C]-29.8441[/C][C]-116.882[/C][/ROW]
[ROW][C]47[/C][C]2036.71[/C][C]2169.89[/C][C]2252.59[/C][C]-82.7058[/C][C]-133.177[/C][/ROW]
[ROW][C]48[/C][C]2048.32[/C][C]2134.3[/C][C]2209.84[/C][C]-75.542[/C][C]-85.9771[/C][/ROW]
[ROW][C]49[/C][C]2159.56[/C][C]2172.26[/C][C]2180.22[/C][C]-7.95463[/C][C]-12.7012[/C][/ROW]
[ROW][C]50[/C][C]2267.79[/C][C]2180.8[/C][C]2175.57[/C][C]5.22996[/C][C]86.99[/C][/ROW]
[ROW][C]51[/C][C]2313.55[/C][C]2214.44[/C][C]2193.86[/C][C]20.5781[/C][C]99.1148[/C][/ROW]
[ROW][C]52[/C][C]2247.3[/C][C]2277[/C][C]2216.16[/C][C]60.8448[/C][C]-29.7048[/C][/ROW]
[ROW][C]53[/C][C]2134.43[/C][C]2281.41[/C][C]2240.26[/C][C]41.1554[/C][C]-146.982[/C][/ROW]
[ROW][C]54[/C][C]2114[/C][C]2239.63[/C][C]2271.52[/C][C]-31.8899[/C][C]-125.628[/C][/ROW]
[ROW][C]55[/C][C]2236.94[/C][C]2294.16[/C][C]2303.89[/C][C]-9.73429[/C][C]-57.2153[/C][/ROW]
[ROW][C]56[/C][C]2345.39[/C][C]2362.06[/C][C]2330.15[/C][C]31.9058[/C][C]-16.67[/C][/ROW]
[ROW][C]57[/C][C]2422.4[/C][C]2431.18[/C][C]2353.22[/C][C]77.9567[/C][C]-8.77796[/C][/ROW]
[ROW][C]58[/C][C]2385.96[/C][C]2350.08[/C][C]2379.92[/C][C]-29.8441[/C][C]35.88[/C][/ROW]
[ROW][C]59[/C][C]2378.17[/C][C]2335.9[/C][C]2418.6[/C][C]-82.7058[/C][C]42.2737[/C][/ROW]
[ROW][C]60[/C][C]2457.13[/C][C]2386.38[/C][C]2461.92[/C][C]-75.542[/C][C]70.7537[/C][/ROW]
[ROW][C]61[/C][C]2527.67[/C][C]2488.79[/C][C]2496.75[/C][C]-7.95463[/C][C]38.8788[/C][/ROW]
[ROW][C]62[/C][C]2530.03[/C][C]2535.23[/C][C]2530[/C][C]5.22996[/C][C]-5.20037[/C][/ROW]
[ROW][C]63[/C][C]2604.92[/C][C]2583.34[/C][C]2562.76[/C][C]20.5781[/C][C]21.5798[/C][/ROW]
[ROW][C]64[/C][C]2596.8[/C][C]2658.46[/C][C]2597.62[/C][C]60.8448[/C][C]-61.6619[/C][/ROW]
[ROW][C]65[/C][C]2713.2[/C][C]2679.43[/C][C]2638.27[/C][C]41.1554[/C][C]33.7746[/C][/ROW]
[ROW][C]66[/C][C]2574.82[/C][C]2642.62[/C][C]2674.51[/C][C]-31.8899[/C][C]-67.7989[/C][/ROW]
[ROW][C]67[/C][C]2611.98[/C][C]NA[/C][C]NA[/C][C]-9.73429[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]2768.46[/C][C]NA[/C][C]NA[/C][C]31.9058[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]2785.61[/C][C]NA[/C][C]NA[/C][C]77.9567[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]2859.27[/C][C]NA[/C][C]NA[/C][C]-29.8441[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]2880.53[/C][C]NA[/C][C]NA[/C][C]-82.7058[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]2824.5[/C][C]NA[/C][C]NA[/C][C]-75.542[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259804&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259804&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
13844.49NANA-7.95463NA
23720.98NANA5.22996NA
33674.4NANA20.5781NA
43857.62NANA60.8448NA
53801.06NANA41.1554NA
63504.37NANA-31.8899NA
73032.63036.143045.87-9.73429-3.53654
83047.032917.42885.4931.9058129.631
92962.342800.352722.477.9567161.987
102197.822525.992555.83-29.8441-328.169
112014.452317.22399.91-82.7058-302.752
121862.832190.042265.58-75.542-327.21
131905.412156.12164.06-7.95463-250.695
141810.992097.812092.585.22996-286.825
151670.072060.132039.5620.5781-390.064
161864.442091.912031.0760.8448-227.473
172052.022104.222063.0641.1554-52.1958
182029.62076.682108.57-31.8899-47.083
192070.832151.942161.67-9.73429-81.1057
202293.4122482216.0931.905845.413
212443.272361.872283.9177.956781.4016
222513.172326.92356.74-29.8441186.271
232466.922323.482406.18-82.7058143.444
242502.662365.322440.87-75.542137.336
252539.912467.462475.42-7.9546372.4459
262482.62505.762500.535.22996-23.1595
272626.152535.58251520.578190.5719
282656.322587.192526.3460.844869.134
292446.662580.252539.0941.1554-133.587
302467.382518.922550.81-31.8899-51.5401
312462.322549.632559.37-9.73429-87.3132
322504.582604.752572.8431.9058-100.17
332579.392661.22583.2577.9567-81.8117
342649.242556.812586.65-29.844192.4329
352636.872517.132599.83-82.7058119.743
362613.942539.312614.85-75.54274.6295
372634.012612.412620.36-7.9546321.6038
382711.942614.212608.985.2299697.7271
392646.432598.12577.5220.578148.3302
402717.792598.552537.7160.8448119.238
412701.542533.022491.8641.1554168.523
422572.982411.42443.29-31.8899161.582
432488.922390.222399.95-9.7342998.703
442204.912393.582361.6831.9058-188.672
452123.992407.262329.377.9567-283.267
462149.12265.982295.83-29.8441-116.882
472036.712169.892252.59-82.7058-133.177
482048.322134.32209.84-75.542-85.9771
492159.562172.262180.22-7.95463-12.7012
502267.792180.82175.575.2299686.99
512313.552214.442193.8620.578199.1148
522247.322772216.1660.8448-29.7048
532134.432281.412240.2641.1554-146.982
5421142239.632271.52-31.8899-125.628
552236.942294.162303.89-9.73429-57.2153
562345.392362.062330.1531.9058-16.67
572422.42431.182353.2277.9567-8.77796
582385.962350.082379.92-29.844135.88
592378.172335.92418.6-82.705842.2737
602457.132386.382461.92-75.54270.7537
612527.672488.792496.75-7.9546338.8788
622530.032535.2325305.22996-5.20037
632604.922583.342562.7620.578121.5798
642596.82658.462597.6260.8448-61.6619
652713.22679.432638.2741.155433.7746
662574.822642.622674.51-31.8899-67.7989
672611.98NANA-9.73429NA
682768.46NANA31.9058NA
692785.61NANA77.9567NA
702859.27NANA-29.8441NA
712880.53NANA-82.7058NA
722824.5NANA-75.542NA


Figures (Output of Computation)

Input Parameters & R Code

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')