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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationFri, 25 Nov 2011 09:59:47 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/25/t1322233250wrwq1yj8zkkuznb.htm/, Retrieved Mon, 04 Mar 2024 04:53:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147332, Retrieved Mon, 04 Mar 2024 04:53:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD    [Classical Decomposition] [] [2011-11-25 14:59:47] [75a32e1bc492240bc1028714aca23077] [Current]
- R         [Classical Decomposition] [] [2011-12-21 21:40:38] [493236dcc414c5f9e1823f06b33a5ad6]
- RM          [Central Tendency] [] [2011-12-22 00:40:07] [493236dcc414c5f9e1823f06b33a5ad6]
- RM D          [Mean Plot] [] [2011-12-22 00:58:52] [493236dcc414c5f9e1823f06b33a5ad6]
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Dataseries X:
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.457




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147332&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147332&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147332&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
11.0622NANA0.0228980902777777NA
21.0773NANA0.0138199652777777NA
31.0807NANA0.00977309027777779NA
41.0848NANA0.00397204861111112NA
51.1582NANA0.00502517361111128NA
61.1663NANA-0.0157102430555555NA
71.13721.128238715277781.13919583333333-0.01095711805555570.00896128472222246
81.11391.140940798611111.15529583333333-0.0143550347222223-0.027040798611111
91.12221.149999131944441.1691625-0.0191633680555556-0.0277991319444442
101.16921.165108506944441.1799625-0.01485399305555560.00409149305555578
111.17021.180628298611111.18647083333333-0.00584253472222217-0.0104282986111111
121.22861.215614756944441.190220833333330.0253939236111110.0129852430555553
131.26131.218823090277781.1959250.02289809027777770.0424769097222224
141.26461.217790798611111.203970833333330.01381996527777770.046809201388889
151.22621.222214756944441.212441666666670.009773090277777790.00398524305555581
161.19851.223888715277781.219916666666670.00397204861111112-0.0253887152777779
171.20071.233637673611111.22861250.00502517361111128-0.0329376736111109
181.21381.222948090277781.23865833333333-0.0157102430555555-0.00914809027777763
191.22661.234484548611111.24544166666667-0.0109571180555557-0.00788454861111099
201.21761.234728298611111.24908333333333-0.0143550347222223-0.0171282986111108
211.22181.235365798611111.25452916666667-0.0191633680555556-0.0135657986111111
221.2491.247558506944441.2624125-0.01485399305555560.00144149305555552
231.29911.263403298611111.26924583333333-0.005842534722222170.0356967013888889
241.34081.297614756944441.272220833333330.0253939236111110.0431852430555557
251.31191.294277256944441.271379166666670.02289809027777770.0176227430555558
261.30141.284728298611111.270908333333330.01381996527777770.0166717013888891
271.32011.281323090277781.271550.009773090277777790.0387769097222224
281.29381.273701215277781.269729166666670.003972048611111120.020098784722222
291.26941.267754340277781.262729166666670.005025173611111280.0016456597222223
301.21651.235531423611111.25124166666667-0.0157102430555555-0.0190314236111111
311.20371.229584548611111.24054166666667-0.0109571180555557-0.025884548611111
321.22921.217469965277781.231825-0.01435503472222230.0117300347222224
331.22561.203257465277781.22242083333333-0.01916336805555560.0223425347222224
341.20151.199866840277781.21472083333333-0.01485399305555560.00163315972222233
351.17861.206415798611111.21225833333333-0.00584253472222217-0.0278157986111107
361.18561.239989756944441.214595833333330.025393923611111-0.0543897569444443
371.21031.242210590277781.21931250.0228980902777777-0.0319105902777779
381.19381.237990798611111.224170833333330.0138199652777777-0.044190798611111
391.2021.238068923611111.228295833333330.00977309027777779-0.0360689236111109
401.22711.236713715277781.232741666666670.00397204861111112-0.00961371527777755
411.2771.244812673611111.23978750.005025173611111280.0321873263888888
421.2651.234293923611111.25000416666667-0.01571024305555550.0307060763888891
431.26841.248434548611111.25939166666667-0.01095711805555570.0199654513888889
441.28111.253503298611111.26785833333333-0.01435503472222230.0275967013888889
451.27271.258519965277781.27768333333333-0.01916336805555560.0141800347222225
461.26111.273108506944441.2879625-0.0148539930555556-0.0120085069444442
471.28811.290394965277781.2962375-0.00584253472222217-0.00229496527777773
481.32131.327923090277781.302529166666670.025393923611111-0.00662309027777774
491.29991.332931423611111.310033333333330.0228980902777777-0.0330314236111111
501.30741.331532465277781.31771250.0138199652777777-0.0241324652777777
511.32421.335735590277781.32596250.00977309027777779-0.0115355902777776
521.35161.341538715277781.337566666666670.003972048611111120.0100612847222223
531.35111.356837673611111.35181250.00502517361111128-0.00573767361111099
541.34191.349268923611111.36497916666667-0.0157102430555555-0.00736892361111074
551.3716NANA-0.0109571180555557NA
561.3622NANA-0.0143550347222223NA
571.3896NANA-0.0191633680555556NA
581.4227NANA-0.0148539930555556NA
591.4684NANA-0.00584253472222217NA
601.457NANA0.025393923611111NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.0622 & NA & NA & 0.0228980902777777 & NA \tabularnewline
2 & 1.0773 & NA & NA & 0.0138199652777777 & NA \tabularnewline
3 & 1.0807 & NA & NA & 0.00977309027777779 & NA \tabularnewline
4 & 1.0848 & NA & NA & 0.00397204861111112 & NA \tabularnewline
5 & 1.1582 & NA & NA & 0.00502517361111128 & NA \tabularnewline
6 & 1.1663 & NA & NA & -0.0157102430555555 & NA \tabularnewline
7 & 1.1372 & 1.12823871527778 & 1.13919583333333 & -0.0109571180555557 & 0.00896128472222246 \tabularnewline
8 & 1.1139 & 1.14094079861111 & 1.15529583333333 & -0.0143550347222223 & -0.027040798611111 \tabularnewline
9 & 1.1222 & 1.14999913194444 & 1.1691625 & -0.0191633680555556 & -0.0277991319444442 \tabularnewline
10 & 1.1692 & 1.16510850694444 & 1.1799625 & -0.0148539930555556 & 0.00409149305555578 \tabularnewline
11 & 1.1702 & 1.18062829861111 & 1.18647083333333 & -0.00584253472222217 & -0.0104282986111111 \tabularnewline
12 & 1.2286 & 1.21561475694444 & 1.19022083333333 & 0.025393923611111 & 0.0129852430555553 \tabularnewline
13 & 1.2613 & 1.21882309027778 & 1.195925 & 0.0228980902777777 & 0.0424769097222224 \tabularnewline
14 & 1.2646 & 1.21779079861111 & 1.20397083333333 & 0.0138199652777777 & 0.046809201388889 \tabularnewline
15 & 1.2262 & 1.22221475694444 & 1.21244166666667 & 0.00977309027777779 & 0.00398524305555581 \tabularnewline
16 & 1.1985 & 1.22388871527778 & 1.21991666666667 & 0.00397204861111112 & -0.0253887152777779 \tabularnewline
17 & 1.2007 & 1.23363767361111 & 1.2286125 & 0.00502517361111128 & -0.0329376736111109 \tabularnewline
18 & 1.2138 & 1.22294809027778 & 1.23865833333333 & -0.0157102430555555 & -0.00914809027777763 \tabularnewline
19 & 1.2266 & 1.23448454861111 & 1.24544166666667 & -0.0109571180555557 & -0.00788454861111099 \tabularnewline
20 & 1.2176 & 1.23472829861111 & 1.24908333333333 & -0.0143550347222223 & -0.0171282986111108 \tabularnewline
21 & 1.2218 & 1.23536579861111 & 1.25452916666667 & -0.0191633680555556 & -0.0135657986111111 \tabularnewline
22 & 1.249 & 1.24755850694444 & 1.2624125 & -0.0148539930555556 & 0.00144149305555552 \tabularnewline
23 & 1.2991 & 1.26340329861111 & 1.26924583333333 & -0.00584253472222217 & 0.0356967013888889 \tabularnewline
24 & 1.3408 & 1.29761475694444 & 1.27222083333333 & 0.025393923611111 & 0.0431852430555557 \tabularnewline
25 & 1.3119 & 1.29427725694444 & 1.27137916666667 & 0.0228980902777777 & 0.0176227430555558 \tabularnewline
26 & 1.3014 & 1.28472829861111 & 1.27090833333333 & 0.0138199652777777 & 0.0166717013888891 \tabularnewline
27 & 1.3201 & 1.28132309027778 & 1.27155 & 0.00977309027777779 & 0.0387769097222224 \tabularnewline
28 & 1.2938 & 1.27370121527778 & 1.26972916666667 & 0.00397204861111112 & 0.020098784722222 \tabularnewline
29 & 1.2694 & 1.26775434027778 & 1.26272916666667 & 0.00502517361111128 & 0.0016456597222223 \tabularnewline
30 & 1.2165 & 1.23553142361111 & 1.25124166666667 & -0.0157102430555555 & -0.0190314236111111 \tabularnewline
31 & 1.2037 & 1.22958454861111 & 1.24054166666667 & -0.0109571180555557 & -0.025884548611111 \tabularnewline
32 & 1.2292 & 1.21746996527778 & 1.231825 & -0.0143550347222223 & 0.0117300347222224 \tabularnewline
33 & 1.2256 & 1.20325746527778 & 1.22242083333333 & -0.0191633680555556 & 0.0223425347222224 \tabularnewline
34 & 1.2015 & 1.19986684027778 & 1.21472083333333 & -0.0148539930555556 & 0.00163315972222233 \tabularnewline
35 & 1.1786 & 1.20641579861111 & 1.21225833333333 & -0.00584253472222217 & -0.0278157986111107 \tabularnewline
36 & 1.1856 & 1.23998975694444 & 1.21459583333333 & 0.025393923611111 & -0.0543897569444443 \tabularnewline
37 & 1.2103 & 1.24221059027778 & 1.2193125 & 0.0228980902777777 & -0.0319105902777779 \tabularnewline
38 & 1.1938 & 1.23799079861111 & 1.22417083333333 & 0.0138199652777777 & -0.044190798611111 \tabularnewline
39 & 1.202 & 1.23806892361111 & 1.22829583333333 & 0.00977309027777779 & -0.0360689236111109 \tabularnewline
40 & 1.2271 & 1.23671371527778 & 1.23274166666667 & 0.00397204861111112 & -0.00961371527777755 \tabularnewline
41 & 1.277 & 1.24481267361111 & 1.2397875 & 0.00502517361111128 & 0.0321873263888888 \tabularnewline
42 & 1.265 & 1.23429392361111 & 1.25000416666667 & -0.0157102430555555 & 0.0307060763888891 \tabularnewline
43 & 1.2684 & 1.24843454861111 & 1.25939166666667 & -0.0109571180555557 & 0.0199654513888889 \tabularnewline
44 & 1.2811 & 1.25350329861111 & 1.26785833333333 & -0.0143550347222223 & 0.0275967013888889 \tabularnewline
45 & 1.2727 & 1.25851996527778 & 1.27768333333333 & -0.0191633680555556 & 0.0141800347222225 \tabularnewline
46 & 1.2611 & 1.27310850694444 & 1.2879625 & -0.0148539930555556 & -0.0120085069444442 \tabularnewline
47 & 1.2881 & 1.29039496527778 & 1.2962375 & -0.00584253472222217 & -0.00229496527777773 \tabularnewline
48 & 1.3213 & 1.32792309027778 & 1.30252916666667 & 0.025393923611111 & -0.00662309027777774 \tabularnewline
49 & 1.2999 & 1.33293142361111 & 1.31003333333333 & 0.0228980902777777 & -0.0330314236111111 \tabularnewline
50 & 1.3074 & 1.33153246527778 & 1.3177125 & 0.0138199652777777 & -0.0241324652777777 \tabularnewline
51 & 1.3242 & 1.33573559027778 & 1.3259625 & 0.00977309027777779 & -0.0115355902777776 \tabularnewline
52 & 1.3516 & 1.34153871527778 & 1.33756666666667 & 0.00397204861111112 & 0.0100612847222223 \tabularnewline
53 & 1.3511 & 1.35683767361111 & 1.3518125 & 0.00502517361111128 & -0.00573767361111099 \tabularnewline
54 & 1.3419 & 1.34926892361111 & 1.36497916666667 & -0.0157102430555555 & -0.00736892361111074 \tabularnewline
55 & 1.3716 & NA & NA & -0.0109571180555557 & NA \tabularnewline
56 & 1.3622 & NA & NA & -0.0143550347222223 & NA \tabularnewline
57 & 1.3896 & NA & NA & -0.0191633680555556 & NA \tabularnewline
58 & 1.4227 & NA & NA & -0.0148539930555556 & NA \tabularnewline
59 & 1.4684 & NA & NA & -0.00584253472222217 & NA \tabularnewline
60 & 1.457 & NA & NA & 0.025393923611111 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147332&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]1.0622[/C][C]NA[/C][C]NA[/C][C]0.0228980902777777[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.0773[/C][C]NA[/C][C]NA[/C][C]0.0138199652777777[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.0807[/C][C]NA[/C][C]NA[/C][C]0.00977309027777779[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.0848[/C][C]NA[/C][C]NA[/C][C]0.00397204861111112[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.1582[/C][C]NA[/C][C]NA[/C][C]0.00502517361111128[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.1663[/C][C]NA[/C][C]NA[/C][C]-0.0157102430555555[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.1372[/C][C]1.12823871527778[/C][C]1.13919583333333[/C][C]-0.0109571180555557[/C][C]0.00896128472222246[/C][/ROW]
[ROW][C]8[/C][C]1.1139[/C][C]1.14094079861111[/C][C]1.15529583333333[/C][C]-0.0143550347222223[/C][C]-0.027040798611111[/C][/ROW]
[ROW][C]9[/C][C]1.1222[/C][C]1.14999913194444[/C][C]1.1691625[/C][C]-0.0191633680555556[/C][C]-0.0277991319444442[/C][/ROW]
[ROW][C]10[/C][C]1.1692[/C][C]1.16510850694444[/C][C]1.1799625[/C][C]-0.0148539930555556[/C][C]0.00409149305555578[/C][/ROW]
[ROW][C]11[/C][C]1.1702[/C][C]1.18062829861111[/C][C]1.18647083333333[/C][C]-0.00584253472222217[/C][C]-0.0104282986111111[/C][/ROW]
[ROW][C]12[/C][C]1.2286[/C][C]1.21561475694444[/C][C]1.19022083333333[/C][C]0.025393923611111[/C][C]0.0129852430555553[/C][/ROW]
[ROW][C]13[/C][C]1.2613[/C][C]1.21882309027778[/C][C]1.195925[/C][C]0.0228980902777777[/C][C]0.0424769097222224[/C][/ROW]
[ROW][C]14[/C][C]1.2646[/C][C]1.21779079861111[/C][C]1.20397083333333[/C][C]0.0138199652777777[/C][C]0.046809201388889[/C][/ROW]
[ROW][C]15[/C][C]1.2262[/C][C]1.22221475694444[/C][C]1.21244166666667[/C][C]0.00977309027777779[/C][C]0.00398524305555581[/C][/ROW]
[ROW][C]16[/C][C]1.1985[/C][C]1.22388871527778[/C][C]1.21991666666667[/C][C]0.00397204861111112[/C][C]-0.0253887152777779[/C][/ROW]
[ROW][C]17[/C][C]1.2007[/C][C]1.23363767361111[/C][C]1.2286125[/C][C]0.00502517361111128[/C][C]-0.0329376736111109[/C][/ROW]
[ROW][C]18[/C][C]1.2138[/C][C]1.22294809027778[/C][C]1.23865833333333[/C][C]-0.0157102430555555[/C][C]-0.00914809027777763[/C][/ROW]
[ROW][C]19[/C][C]1.2266[/C][C]1.23448454861111[/C][C]1.24544166666667[/C][C]-0.0109571180555557[/C][C]-0.00788454861111099[/C][/ROW]
[ROW][C]20[/C][C]1.2176[/C][C]1.23472829861111[/C][C]1.24908333333333[/C][C]-0.0143550347222223[/C][C]-0.0171282986111108[/C][/ROW]
[ROW][C]21[/C][C]1.2218[/C][C]1.23536579861111[/C][C]1.25452916666667[/C][C]-0.0191633680555556[/C][C]-0.0135657986111111[/C][/ROW]
[ROW][C]22[/C][C]1.249[/C][C]1.24755850694444[/C][C]1.2624125[/C][C]-0.0148539930555556[/C][C]0.00144149305555552[/C][/ROW]
[ROW][C]23[/C][C]1.2991[/C][C]1.26340329861111[/C][C]1.26924583333333[/C][C]-0.00584253472222217[/C][C]0.0356967013888889[/C][/ROW]
[ROW][C]24[/C][C]1.3408[/C][C]1.29761475694444[/C][C]1.27222083333333[/C][C]0.025393923611111[/C][C]0.0431852430555557[/C][/ROW]
[ROW][C]25[/C][C]1.3119[/C][C]1.29427725694444[/C][C]1.27137916666667[/C][C]0.0228980902777777[/C][C]0.0176227430555558[/C][/ROW]
[ROW][C]26[/C][C]1.3014[/C][C]1.28472829861111[/C][C]1.27090833333333[/C][C]0.0138199652777777[/C][C]0.0166717013888891[/C][/ROW]
[ROW][C]27[/C][C]1.3201[/C][C]1.28132309027778[/C][C]1.27155[/C][C]0.00977309027777779[/C][C]0.0387769097222224[/C][/ROW]
[ROW][C]28[/C][C]1.2938[/C][C]1.27370121527778[/C][C]1.26972916666667[/C][C]0.00397204861111112[/C][C]0.020098784722222[/C][/ROW]
[ROW][C]29[/C][C]1.2694[/C][C]1.26775434027778[/C][C]1.26272916666667[/C][C]0.00502517361111128[/C][C]0.0016456597222223[/C][/ROW]
[ROW][C]30[/C][C]1.2165[/C][C]1.23553142361111[/C][C]1.25124166666667[/C][C]-0.0157102430555555[/C][C]-0.0190314236111111[/C][/ROW]
[ROW][C]31[/C][C]1.2037[/C][C]1.22958454861111[/C][C]1.24054166666667[/C][C]-0.0109571180555557[/C][C]-0.025884548611111[/C][/ROW]
[ROW][C]32[/C][C]1.2292[/C][C]1.21746996527778[/C][C]1.231825[/C][C]-0.0143550347222223[/C][C]0.0117300347222224[/C][/ROW]
[ROW][C]33[/C][C]1.2256[/C][C]1.20325746527778[/C][C]1.22242083333333[/C][C]-0.0191633680555556[/C][C]0.0223425347222224[/C][/ROW]
[ROW][C]34[/C][C]1.2015[/C][C]1.19986684027778[/C][C]1.21472083333333[/C][C]-0.0148539930555556[/C][C]0.00163315972222233[/C][/ROW]
[ROW][C]35[/C][C]1.1786[/C][C]1.20641579861111[/C][C]1.21225833333333[/C][C]-0.00584253472222217[/C][C]-0.0278157986111107[/C][/ROW]
[ROW][C]36[/C][C]1.1856[/C][C]1.23998975694444[/C][C]1.21459583333333[/C][C]0.025393923611111[/C][C]-0.0543897569444443[/C][/ROW]
[ROW][C]37[/C][C]1.2103[/C][C]1.24221059027778[/C][C]1.2193125[/C][C]0.0228980902777777[/C][C]-0.0319105902777779[/C][/ROW]
[ROW][C]38[/C][C]1.1938[/C][C]1.23799079861111[/C][C]1.22417083333333[/C][C]0.0138199652777777[/C][C]-0.044190798611111[/C][/ROW]
[ROW][C]39[/C][C]1.202[/C][C]1.23806892361111[/C][C]1.22829583333333[/C][C]0.00977309027777779[/C][C]-0.0360689236111109[/C][/ROW]
[ROW][C]40[/C][C]1.2271[/C][C]1.23671371527778[/C][C]1.23274166666667[/C][C]0.00397204861111112[/C][C]-0.00961371527777755[/C][/ROW]
[ROW][C]41[/C][C]1.277[/C][C]1.24481267361111[/C][C]1.2397875[/C][C]0.00502517361111128[/C][C]0.0321873263888888[/C][/ROW]
[ROW][C]42[/C][C]1.265[/C][C]1.23429392361111[/C][C]1.25000416666667[/C][C]-0.0157102430555555[/C][C]0.0307060763888891[/C][/ROW]
[ROW][C]43[/C][C]1.2684[/C][C]1.24843454861111[/C][C]1.25939166666667[/C][C]-0.0109571180555557[/C][C]0.0199654513888889[/C][/ROW]
[ROW][C]44[/C][C]1.2811[/C][C]1.25350329861111[/C][C]1.26785833333333[/C][C]-0.0143550347222223[/C][C]0.0275967013888889[/C][/ROW]
[ROW][C]45[/C][C]1.2727[/C][C]1.25851996527778[/C][C]1.27768333333333[/C][C]-0.0191633680555556[/C][C]0.0141800347222225[/C][/ROW]
[ROW][C]46[/C][C]1.2611[/C][C]1.27310850694444[/C][C]1.2879625[/C][C]-0.0148539930555556[/C][C]-0.0120085069444442[/C][/ROW]
[ROW][C]47[/C][C]1.2881[/C][C]1.29039496527778[/C][C]1.2962375[/C][C]-0.00584253472222217[/C][C]-0.00229496527777773[/C][/ROW]
[ROW][C]48[/C][C]1.3213[/C][C]1.32792309027778[/C][C]1.30252916666667[/C][C]0.025393923611111[/C][C]-0.00662309027777774[/C][/ROW]
[ROW][C]49[/C][C]1.2999[/C][C]1.33293142361111[/C][C]1.31003333333333[/C][C]0.0228980902777777[/C][C]-0.0330314236111111[/C][/ROW]
[ROW][C]50[/C][C]1.3074[/C][C]1.33153246527778[/C][C]1.3177125[/C][C]0.0138199652777777[/C][C]-0.0241324652777777[/C][/ROW]
[ROW][C]51[/C][C]1.3242[/C][C]1.33573559027778[/C][C]1.3259625[/C][C]0.00977309027777779[/C][C]-0.0115355902777776[/C][/ROW]
[ROW][C]52[/C][C]1.3516[/C][C]1.34153871527778[/C][C]1.33756666666667[/C][C]0.00397204861111112[/C][C]0.0100612847222223[/C][/ROW]
[ROW][C]53[/C][C]1.3511[/C][C]1.35683767361111[/C][C]1.3518125[/C][C]0.00502517361111128[/C][C]-0.00573767361111099[/C][/ROW]
[ROW][C]54[/C][C]1.3419[/C][C]1.34926892361111[/C][C]1.36497916666667[/C][C]-0.0157102430555555[/C][C]-0.00736892361111074[/C][/ROW]
[ROW][C]55[/C][C]1.3716[/C][C]NA[/C][C]NA[/C][C]-0.0109571180555557[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]1.3622[/C][C]NA[/C][C]NA[/C][C]-0.0143550347222223[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]1.3896[/C][C]NA[/C][C]NA[/C][C]-0.0191633680555556[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]1.4227[/C][C]NA[/C][C]NA[/C][C]-0.0148539930555556[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]1.4684[/C][C]NA[/C][C]NA[/C][C]-0.00584253472222217[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]1.457[/C][C]NA[/C][C]NA[/C][C]0.025393923611111[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147332&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147332&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
tObservationsFitTrendSeasonalRandom
11.0622NANA0.0228980902777777NA
21.0773NANA0.0138199652777777NA
31.0807NANA0.00977309027777779NA
41.0848NANA0.00397204861111112NA
51.1582NANA0.00502517361111128NA
61.1663NANA-0.0157102430555555NA
71.13721.128238715277781.13919583333333-0.01095711805555570.00896128472222246
81.11391.140940798611111.15529583333333-0.0143550347222223-0.027040798611111
91.12221.149999131944441.1691625-0.0191633680555556-0.0277991319444442
101.16921.165108506944441.1799625-0.01485399305555560.00409149305555578
111.17021.180628298611111.18647083333333-0.00584253472222217-0.0104282986111111
121.22861.215614756944441.190220833333330.0253939236111110.0129852430555553
131.26131.218823090277781.1959250.02289809027777770.0424769097222224
141.26461.217790798611111.203970833333330.01381996527777770.046809201388889
151.22621.222214756944441.212441666666670.009773090277777790.00398524305555581
161.19851.223888715277781.219916666666670.00397204861111112-0.0253887152777779
171.20071.233637673611111.22861250.00502517361111128-0.0329376736111109
181.21381.222948090277781.23865833333333-0.0157102430555555-0.00914809027777763
191.22661.234484548611111.24544166666667-0.0109571180555557-0.00788454861111099
201.21761.234728298611111.24908333333333-0.0143550347222223-0.0171282986111108
211.22181.235365798611111.25452916666667-0.0191633680555556-0.0135657986111111
221.2491.247558506944441.2624125-0.01485399305555560.00144149305555552
231.29911.263403298611111.26924583333333-0.005842534722222170.0356967013888889
241.34081.297614756944441.272220833333330.0253939236111110.0431852430555557
251.31191.294277256944441.271379166666670.02289809027777770.0176227430555558
261.30141.284728298611111.270908333333330.01381996527777770.0166717013888891
271.32011.281323090277781.271550.009773090277777790.0387769097222224
281.29381.273701215277781.269729166666670.003972048611111120.020098784722222
291.26941.267754340277781.262729166666670.005025173611111280.0016456597222223
301.21651.235531423611111.25124166666667-0.0157102430555555-0.0190314236111111
311.20371.229584548611111.24054166666667-0.0109571180555557-0.025884548611111
321.22921.217469965277781.231825-0.01435503472222230.0117300347222224
331.22561.203257465277781.22242083333333-0.01916336805555560.0223425347222224
341.20151.199866840277781.21472083333333-0.01485399305555560.00163315972222233
351.17861.206415798611111.21225833333333-0.00584253472222217-0.0278157986111107
361.18561.239989756944441.214595833333330.025393923611111-0.0543897569444443
371.21031.242210590277781.21931250.0228980902777777-0.0319105902777779
381.19381.237990798611111.224170833333330.0138199652777777-0.044190798611111
391.2021.238068923611111.228295833333330.00977309027777779-0.0360689236111109
401.22711.236713715277781.232741666666670.00397204861111112-0.00961371527777755
411.2771.244812673611111.23978750.005025173611111280.0321873263888888
421.2651.234293923611111.25000416666667-0.01571024305555550.0307060763888891
431.26841.248434548611111.25939166666667-0.01095711805555570.0199654513888889
441.28111.253503298611111.26785833333333-0.01435503472222230.0275967013888889
451.27271.258519965277781.27768333333333-0.01916336805555560.0141800347222225
461.26111.273108506944441.2879625-0.0148539930555556-0.0120085069444442
471.28811.290394965277781.2962375-0.00584253472222217-0.00229496527777773
481.32131.327923090277781.302529166666670.025393923611111-0.00662309027777774
491.29991.332931423611111.310033333333330.0228980902777777-0.0330314236111111
501.30741.331532465277781.31771250.0138199652777777-0.0241324652777777
511.32421.335735590277781.32596250.00977309027777779-0.0115355902777776
521.35161.341538715277781.337566666666670.003972048611111120.0100612847222223
531.35111.356837673611111.35181250.00502517361111128-0.00573767361111099
541.34191.349268923611111.36497916666667-0.0157102430555555-0.00736892361111074
551.3716NANA-0.0109571180555557NA
561.3622NANA-0.0143550347222223NA
571.3896NANA-0.0191633680555556NA
581.4227NANA-0.0148539930555556NA
591.4684NANA-0.00584253472222217NA
601.457NANA0.025393923611111NA



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')