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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 28 Dec 2010 12:20:45 +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/2010/Dec/28/t1293538754vsb3v8dji4p111f.htm/, Retrieved Thu, 02 May 2024 01:05:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116316, Retrieved Thu, 02 May 2024 01:05:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-25 16:13:35] [1253bc7c4737195066123d9caa6dfc18]
- RMPD    [Classical Decomposition] [] [2010-12-28 12:20:45] [e180d4cd19004beeddc12e67012247dc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4,031636
3,702076
3,056167
3,280707
2,984728
3,693712
3,226317
2,190349
2,599515
3,080288
2,929672
2,922548
3,234943
2,983081
3,284389
3,806511
3,784579
2,645654
3,092081
3,204859
3,107225
3,466909
2,984404
3,218072
2,827310
3,182049
2,236319
2,033218
1,644804
1,627971
1,677559
2,330828
2,493615
2,257172
2,655517
2,298655
2,600402
3,045230
2,790583
3,227052
2,967479
2,938817
3,277961
3,423985
3,072646
2,754253
2,910431
3,174369
3,068387
3,089543
2,906654
2,931161
3,025660
2,939551
2,691019
3,198120
3,076390
2,863873
3,013802
3,053364
2,864753
3,057062
2,959365
3,252258
3,602988
3,497704
3,296867
3,602417
3,300100
3,401930
3,502591
3,402348
3,498551
3,199823
2,700064
2,801034
2,898628
2,800854
2,399942
2,402724
2,202331
2,102594
1,798293
1,202484
1,400201
1,200832
1,298083
1,099742
1,001377
0,836174

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116316&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]3 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=116316&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116316&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 time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
14.031636NANA0.046548175347222NA
23.702076NANA0.127885730902778NA
33.056167NANA-0.150733206597223NA
43.280707NANA0.054457890625NA
52.984728NANA0.047921564236111NA
63.693712NANA-0.177874581597222NA
73.2263172.952571946180563.10828070833333-0.1557087621527780.273745053819444
82.1903493.202453605902783.045127041666670.157326564236111-1.01210460590278
92.5995153.056404251736113.024678166666670.0317260850694447-0.456889251736111
103.0802883.052816800347223.05609591666667-0.003279116319444550.0274711996527781
112.9296723.1492283906253.111331541666670.0378968489583335-0.219556390624999
122.9225483.0848223906253.10098958333333-0.0161671927083335-0.162274390624999
133.2349433.098275508680563.051727333333330.0465481753472220.136667491319444
142.9830813.216291147569443.088405416666670.127885730902778-0.233210147569444
153.2843893.001098043402783.15183125-0.1507332065972230.283290956597223
163.8065113.243552932291673.189095041666670.0544578906250.562958067708333
173.7845793.255406314236113.207484750.0479215642361110.529172685763889
182.6456543.044204168402783.22207875-0.177874581597222-0.398550168402778
193.0920813.061698779513893.21740754166667-0.1557087621527780.0303822204861115
203.2048593.366039730902783.208713166666670.157326564236111-0.161180730902777
213.1072253.205060001736113.173333916666670.0317260850694447-0.0978350017361107
223.4669093.052498008680563.055777125-0.003279116319444550.414410991319444
232.9844042.930629473958332.8927326250.03789684895833350.0537745260416673
243.2180722.745004682291672.761171875-0.01616719270833350.473067317708333
252.827312.706378175347222.659830.0465481753472220.120931824652778
263.1820492.692359355902782.5644736250.1278857309027780.489689644097223
272.2363192.351755376736112.50248858333333-0.150733206597223-0.115436376736111
282.0332182.480973682291672.426515791666670.054457890625-0.447755682291666
291.6448042.410328022569442.362406458333330.047921564236111-0.765524022569445
301.6279712.132519210069442.31039379166667-0.177874581597222-0.504548210069445
311.6775592.106921487847222.26263025-0.155708762152778-0.429362487847222
322.3308282.404801522569442.247474958333330.157326564236111-0.0739735225694447
332.4936152.296594585069442.26486850.03172608506944470.197020414930555
342.2571722.334426800347222.33770591666667-0.00327911631944455-0.0772548003472222
352.6555172.480457307291672.442560458333330.03789684895833350.175059692708334
362.2986552.536123307291672.5522905-0.0161671927083335-0.237468307291666
372.6004022.720140675347222.67359250.046548175347222-0.119738675347222
383.045232.913709855902782.7858241250.1278857309027780.131520144097223
392.7905832.704765418402782.855498625-0.1507332065972230.0858175815972224
403.2270522.9547945156252.9003366250.0544578906250.272257484375
412.9674792.979591314236112.931669750.047921564236111-0.0121123142361101
422.9388172.800904668402782.97877925-0.1778745815972220.137912331597222
433.2779612.879057946180563.03476670833333-0.1557087621527780.398903053819445
443.4239853.213439022569443.056112458333330.1573265642361110.210545977430556
453.0726463.094521210069443.0627951250.0317260850694447-0.0218752100694437
462.7542533.052023508680563.055302625-0.00327911631944455-0.297770508680556
472.9104313.0832948906253.045398041666670.0378968489583335-0.172863890625
483.1743693.0316856406253.04785283333333-0.01616719270833350.142683359374999
493.0683873.069975675347223.02342750.046548175347222-0.00158867534722207
503.0895433.117446272569442.989560541666670.127885730902778-0.0279032725694446
512.9066542.829572293402782.9803055-0.1507332065972230.0770817065972227
522.9311613.0394868906252.9850290.054457890625-0.108325890625
533.025663.041825189236112.9939036250.047921564236111-0.0161651892361108
542.9395512.815294293402782.993168875-0.1778745815972220.124256706597222
552.6910192.823933487847222.97964225-0.155708762152778-0.132914487847223
563.198123.127130689236112.9698041250.1573265642361110.0709893107638893
573.076393.002373126736112.970647041666670.03172608506944470.0740168732638886
582.8638732.982943258680562.986222375-0.00327911631944455-0.119070258680555
593.0138023.061553598958333.023656750.0378968489583335-0.0477515989583326
603.0533643.0548012656253.07096845833333-0.0161671927083335-0.00143726562499902
612.8647533.166016675347223.11946850.046548175347222-0.301263675347222
623.0570623.289443605902783.1615578750.127885730902778-0.232381605902777
632.9593653.036991626736113.18772483333333-0.150733206597223-0.0776266267361105
643.2522583.2739230156253.2194651250.054457890625-0.0216650156249996
653.6029883.310171939236113.2622503750.0479215642361110.292816060763889
663.4977043.119283001736113.29715758333333-0.1778745815972220.37842099826389
673.2968673.182398071180563.33810683333333-0.1557087621527780.114468928819445
683.6024173.527790022569443.370463458333330.1573265642361110.0746269774305559
693.30013.397333710069443.3656076250.0317260850694447-0.0972337100694438
703.401933.332723300347223.33600241666667-0.003279116319444550.0692066996527783
713.5025913.325749932291673.287853083333330.03789684895833350.176841067708334
723.4023483.2133021406253.22946933333333-0.01616719270833350.189045859375
733.4985513.209610217013893.163062041666670.0465481753472220.288940782986111
743.1998233.203588689236113.075702958333330.127885730902778-0.00376568923611087
752.7000642.829242168402782.979975375-0.150733206597223-0.129178168402778
762.8010342.9345538906252.8800960.054457890625-0.133519890625
772.8986282.802866147569442.754944583333330.0479215642361110.095761852430556
782.8008542.414396585069442.59227116666667-0.1778745815972220.386457414930556
792.3999422.257470154513892.41317891666667-0.1557087621527780.142471845486111
802.4027242.399782939236112.2424563750.1573265642361110.00294106076388889
812.2023312.132475293402782.100749208333330.03172608506944470.0698557065972221
822.1025941.968167050347221.97144616666667-0.003279116319444550.134426949652778
831.7982931.859403723958331.8215068750.0378968489583335-0.0611107239583335
841.2024841.6444258906251.66059308333333-0.0161671927083335-0.441941890624999
851.400201NANANANA
861.200832NANANANA
871.298083NANANANA
881.099742NANANANA
891.001377NANANANA
900.836174NANANANA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 4.031636 & NA & NA & 0.046548175347222 & NA \tabularnewline
2 & 3.702076 & NA & NA & 0.127885730902778 & NA \tabularnewline
3 & 3.056167 & NA & NA & -0.150733206597223 & NA \tabularnewline
4 & 3.280707 & NA & NA & 0.054457890625 & NA \tabularnewline
5 & 2.984728 & NA & NA & 0.047921564236111 & NA \tabularnewline
6 & 3.693712 & NA & NA & -0.177874581597222 & NA \tabularnewline
7 & 3.226317 & 2.95257194618056 & 3.10828070833333 & -0.155708762152778 & 0.273745053819444 \tabularnewline
8 & 2.190349 & 3.20245360590278 & 3.04512704166667 & 0.157326564236111 & -1.01210460590278 \tabularnewline
9 & 2.599515 & 3.05640425173611 & 3.02467816666667 & 0.0317260850694447 & -0.456889251736111 \tabularnewline
10 & 3.080288 & 3.05281680034722 & 3.05609591666667 & -0.00327911631944455 & 0.0274711996527781 \tabularnewline
11 & 2.929672 & 3.149228390625 & 3.11133154166667 & 0.0378968489583335 & -0.219556390624999 \tabularnewline
12 & 2.922548 & 3.084822390625 & 3.10098958333333 & -0.0161671927083335 & -0.162274390624999 \tabularnewline
13 & 3.234943 & 3.09827550868056 & 3.05172733333333 & 0.046548175347222 & 0.136667491319444 \tabularnewline
14 & 2.983081 & 3.21629114756944 & 3.08840541666667 & 0.127885730902778 & -0.233210147569444 \tabularnewline
15 & 3.284389 & 3.00109804340278 & 3.15183125 & -0.150733206597223 & 0.283290956597223 \tabularnewline
16 & 3.806511 & 3.24355293229167 & 3.18909504166667 & 0.054457890625 & 0.562958067708333 \tabularnewline
17 & 3.784579 & 3.25540631423611 & 3.20748475 & 0.047921564236111 & 0.529172685763889 \tabularnewline
18 & 2.645654 & 3.04420416840278 & 3.22207875 & -0.177874581597222 & -0.398550168402778 \tabularnewline
19 & 3.092081 & 3.06169877951389 & 3.21740754166667 & -0.155708762152778 & 0.0303822204861115 \tabularnewline
20 & 3.204859 & 3.36603973090278 & 3.20871316666667 & 0.157326564236111 & -0.161180730902777 \tabularnewline
21 & 3.107225 & 3.20506000173611 & 3.17333391666667 & 0.0317260850694447 & -0.0978350017361107 \tabularnewline
22 & 3.466909 & 3.05249800868056 & 3.055777125 & -0.00327911631944455 & 0.414410991319444 \tabularnewline
23 & 2.984404 & 2.93062947395833 & 2.892732625 & 0.0378968489583335 & 0.0537745260416673 \tabularnewline
24 & 3.218072 & 2.74500468229167 & 2.761171875 & -0.0161671927083335 & 0.473067317708333 \tabularnewline
25 & 2.82731 & 2.70637817534722 & 2.65983 & 0.046548175347222 & 0.120931824652778 \tabularnewline
26 & 3.182049 & 2.69235935590278 & 2.564473625 & 0.127885730902778 & 0.489689644097223 \tabularnewline
27 & 2.236319 & 2.35175537673611 & 2.50248858333333 & -0.150733206597223 & -0.115436376736111 \tabularnewline
28 & 2.033218 & 2.48097368229167 & 2.42651579166667 & 0.054457890625 & -0.447755682291666 \tabularnewline
29 & 1.644804 & 2.41032802256944 & 2.36240645833333 & 0.047921564236111 & -0.765524022569445 \tabularnewline
30 & 1.627971 & 2.13251921006944 & 2.31039379166667 & -0.177874581597222 & -0.504548210069445 \tabularnewline
31 & 1.677559 & 2.10692148784722 & 2.26263025 & -0.155708762152778 & -0.429362487847222 \tabularnewline
32 & 2.330828 & 2.40480152256944 & 2.24747495833333 & 0.157326564236111 & -0.0739735225694447 \tabularnewline
33 & 2.493615 & 2.29659458506944 & 2.2648685 & 0.0317260850694447 & 0.197020414930555 \tabularnewline
34 & 2.257172 & 2.33442680034722 & 2.33770591666667 & -0.00327911631944455 & -0.0772548003472222 \tabularnewline
35 & 2.655517 & 2.48045730729167 & 2.44256045833333 & 0.0378968489583335 & 0.175059692708334 \tabularnewline
36 & 2.298655 & 2.53612330729167 & 2.5522905 & -0.0161671927083335 & -0.237468307291666 \tabularnewline
37 & 2.600402 & 2.72014067534722 & 2.6735925 & 0.046548175347222 & -0.119738675347222 \tabularnewline
38 & 3.04523 & 2.91370985590278 & 2.785824125 & 0.127885730902778 & 0.131520144097223 \tabularnewline
39 & 2.790583 & 2.70476541840278 & 2.855498625 & -0.150733206597223 & 0.0858175815972224 \tabularnewline
40 & 3.227052 & 2.954794515625 & 2.900336625 & 0.054457890625 & 0.272257484375 \tabularnewline
41 & 2.967479 & 2.97959131423611 & 2.93166975 & 0.047921564236111 & -0.0121123142361101 \tabularnewline
42 & 2.938817 & 2.80090466840278 & 2.97877925 & -0.177874581597222 & 0.137912331597222 \tabularnewline
43 & 3.277961 & 2.87905794618056 & 3.03476670833333 & -0.155708762152778 & 0.398903053819445 \tabularnewline
44 & 3.423985 & 3.21343902256944 & 3.05611245833333 & 0.157326564236111 & 0.210545977430556 \tabularnewline
45 & 3.072646 & 3.09452121006944 & 3.062795125 & 0.0317260850694447 & -0.0218752100694437 \tabularnewline
46 & 2.754253 & 3.05202350868056 & 3.055302625 & -0.00327911631944455 & -0.297770508680556 \tabularnewline
47 & 2.910431 & 3.083294890625 & 3.04539804166667 & 0.0378968489583335 & -0.172863890625 \tabularnewline
48 & 3.174369 & 3.031685640625 & 3.04785283333333 & -0.0161671927083335 & 0.142683359374999 \tabularnewline
49 & 3.068387 & 3.06997567534722 & 3.0234275 & 0.046548175347222 & -0.00158867534722207 \tabularnewline
50 & 3.089543 & 3.11744627256944 & 2.98956054166667 & 0.127885730902778 & -0.0279032725694446 \tabularnewline
51 & 2.906654 & 2.82957229340278 & 2.9803055 & -0.150733206597223 & 0.0770817065972227 \tabularnewline
52 & 2.931161 & 3.039486890625 & 2.985029 & 0.054457890625 & -0.108325890625 \tabularnewline
53 & 3.02566 & 3.04182518923611 & 2.993903625 & 0.047921564236111 & -0.0161651892361108 \tabularnewline
54 & 2.939551 & 2.81529429340278 & 2.993168875 & -0.177874581597222 & 0.124256706597222 \tabularnewline
55 & 2.691019 & 2.82393348784722 & 2.97964225 & -0.155708762152778 & -0.132914487847223 \tabularnewline
56 & 3.19812 & 3.12713068923611 & 2.969804125 & 0.157326564236111 & 0.0709893107638893 \tabularnewline
57 & 3.07639 & 3.00237312673611 & 2.97064704166667 & 0.0317260850694447 & 0.0740168732638886 \tabularnewline
58 & 2.863873 & 2.98294325868056 & 2.986222375 & -0.00327911631944455 & -0.119070258680555 \tabularnewline
59 & 3.013802 & 3.06155359895833 & 3.02365675 & 0.0378968489583335 & -0.0477515989583326 \tabularnewline
60 & 3.053364 & 3.054801265625 & 3.07096845833333 & -0.0161671927083335 & -0.00143726562499902 \tabularnewline
61 & 2.864753 & 3.16601667534722 & 3.1194685 & 0.046548175347222 & -0.301263675347222 \tabularnewline
62 & 3.057062 & 3.28944360590278 & 3.161557875 & 0.127885730902778 & -0.232381605902777 \tabularnewline
63 & 2.959365 & 3.03699162673611 & 3.18772483333333 & -0.150733206597223 & -0.0776266267361105 \tabularnewline
64 & 3.252258 & 3.273923015625 & 3.219465125 & 0.054457890625 & -0.0216650156249996 \tabularnewline
65 & 3.602988 & 3.31017193923611 & 3.262250375 & 0.047921564236111 & 0.292816060763889 \tabularnewline
66 & 3.497704 & 3.11928300173611 & 3.29715758333333 & -0.177874581597222 & 0.37842099826389 \tabularnewline
67 & 3.296867 & 3.18239807118056 & 3.33810683333333 & -0.155708762152778 & 0.114468928819445 \tabularnewline
68 & 3.602417 & 3.52779002256944 & 3.37046345833333 & 0.157326564236111 & 0.0746269774305559 \tabularnewline
69 & 3.3001 & 3.39733371006944 & 3.365607625 & 0.0317260850694447 & -0.0972337100694438 \tabularnewline
70 & 3.40193 & 3.33272330034722 & 3.33600241666667 & -0.00327911631944455 & 0.0692066996527783 \tabularnewline
71 & 3.502591 & 3.32574993229167 & 3.28785308333333 & 0.0378968489583335 & 0.176841067708334 \tabularnewline
72 & 3.402348 & 3.213302140625 & 3.22946933333333 & -0.0161671927083335 & 0.189045859375 \tabularnewline
73 & 3.498551 & 3.20961021701389 & 3.16306204166667 & 0.046548175347222 & 0.288940782986111 \tabularnewline
74 & 3.199823 & 3.20358868923611 & 3.07570295833333 & 0.127885730902778 & -0.00376568923611087 \tabularnewline
75 & 2.700064 & 2.82924216840278 & 2.979975375 & -0.150733206597223 & -0.129178168402778 \tabularnewline
76 & 2.801034 & 2.934553890625 & 2.880096 & 0.054457890625 & -0.133519890625 \tabularnewline
77 & 2.898628 & 2.80286614756944 & 2.75494458333333 & 0.047921564236111 & 0.095761852430556 \tabularnewline
78 & 2.800854 & 2.41439658506944 & 2.59227116666667 & -0.177874581597222 & 0.386457414930556 \tabularnewline
79 & 2.399942 & 2.25747015451389 & 2.41317891666667 & -0.155708762152778 & 0.142471845486111 \tabularnewline
80 & 2.402724 & 2.39978293923611 & 2.242456375 & 0.157326564236111 & 0.00294106076388889 \tabularnewline
81 & 2.202331 & 2.13247529340278 & 2.10074920833333 & 0.0317260850694447 & 0.0698557065972221 \tabularnewline
82 & 2.102594 & 1.96816705034722 & 1.97144616666667 & -0.00327911631944455 & 0.134426949652778 \tabularnewline
83 & 1.798293 & 1.85940372395833 & 1.821506875 & 0.0378968489583335 & -0.0611107239583335 \tabularnewline
84 & 1.202484 & 1.644425890625 & 1.66059308333333 & -0.0161671927083335 & -0.441941890624999 \tabularnewline
85 & 1.400201 & NA & NA & NA & NA \tabularnewline
86 & 1.200832 & NA & NA & NA & NA \tabularnewline
87 & 1.298083 & NA & NA & NA & NA \tabularnewline
88 & 1.099742 & NA & NA & NA & NA \tabularnewline
89 & 1.001377 & NA & NA & NA & NA \tabularnewline
90 & 0.836174 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116316&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]4.031636[/C][C]NA[/C][C]NA[/C][C]0.046548175347222[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3.702076[/C][C]NA[/C][C]NA[/C][C]0.127885730902778[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.056167[/C][C]NA[/C][C]NA[/C][C]-0.150733206597223[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3.280707[/C][C]NA[/C][C]NA[/C][C]0.054457890625[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.984728[/C][C]NA[/C][C]NA[/C][C]0.047921564236111[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3.693712[/C][C]NA[/C][C]NA[/C][C]-0.177874581597222[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3.226317[/C][C]2.95257194618056[/C][C]3.10828070833333[/C][C]-0.155708762152778[/C][C]0.273745053819444[/C][/ROW]
[ROW][C]8[/C][C]2.190349[/C][C]3.20245360590278[/C][C]3.04512704166667[/C][C]0.157326564236111[/C][C]-1.01210460590278[/C][/ROW]
[ROW][C]9[/C][C]2.599515[/C][C]3.05640425173611[/C][C]3.02467816666667[/C][C]0.0317260850694447[/C][C]-0.456889251736111[/C][/ROW]
[ROW][C]10[/C][C]3.080288[/C][C]3.05281680034722[/C][C]3.05609591666667[/C][C]-0.00327911631944455[/C][C]0.0274711996527781[/C][/ROW]
[ROW][C]11[/C][C]2.929672[/C][C]3.149228390625[/C][C]3.11133154166667[/C][C]0.0378968489583335[/C][C]-0.219556390624999[/C][/ROW]
[ROW][C]12[/C][C]2.922548[/C][C]3.084822390625[/C][C]3.10098958333333[/C][C]-0.0161671927083335[/C][C]-0.162274390624999[/C][/ROW]
[ROW][C]13[/C][C]3.234943[/C][C]3.09827550868056[/C][C]3.05172733333333[/C][C]0.046548175347222[/C][C]0.136667491319444[/C][/ROW]
[ROW][C]14[/C][C]2.983081[/C][C]3.21629114756944[/C][C]3.08840541666667[/C][C]0.127885730902778[/C][C]-0.233210147569444[/C][/ROW]
[ROW][C]15[/C][C]3.284389[/C][C]3.00109804340278[/C][C]3.15183125[/C][C]-0.150733206597223[/C][C]0.283290956597223[/C][/ROW]
[ROW][C]16[/C][C]3.806511[/C][C]3.24355293229167[/C][C]3.18909504166667[/C][C]0.054457890625[/C][C]0.562958067708333[/C][/ROW]
[ROW][C]17[/C][C]3.784579[/C][C]3.25540631423611[/C][C]3.20748475[/C][C]0.047921564236111[/C][C]0.529172685763889[/C][/ROW]
[ROW][C]18[/C][C]2.645654[/C][C]3.04420416840278[/C][C]3.22207875[/C][C]-0.177874581597222[/C][C]-0.398550168402778[/C][/ROW]
[ROW][C]19[/C][C]3.092081[/C][C]3.06169877951389[/C][C]3.21740754166667[/C][C]-0.155708762152778[/C][C]0.0303822204861115[/C][/ROW]
[ROW][C]20[/C][C]3.204859[/C][C]3.36603973090278[/C][C]3.20871316666667[/C][C]0.157326564236111[/C][C]-0.161180730902777[/C][/ROW]
[ROW][C]21[/C][C]3.107225[/C][C]3.20506000173611[/C][C]3.17333391666667[/C][C]0.0317260850694447[/C][C]-0.0978350017361107[/C][/ROW]
[ROW][C]22[/C][C]3.466909[/C][C]3.05249800868056[/C][C]3.055777125[/C][C]-0.00327911631944455[/C][C]0.414410991319444[/C][/ROW]
[ROW][C]23[/C][C]2.984404[/C][C]2.93062947395833[/C][C]2.892732625[/C][C]0.0378968489583335[/C][C]0.0537745260416673[/C][/ROW]
[ROW][C]24[/C][C]3.218072[/C][C]2.74500468229167[/C][C]2.761171875[/C][C]-0.0161671927083335[/C][C]0.473067317708333[/C][/ROW]
[ROW][C]25[/C][C]2.82731[/C][C]2.70637817534722[/C][C]2.65983[/C][C]0.046548175347222[/C][C]0.120931824652778[/C][/ROW]
[ROW][C]26[/C][C]3.182049[/C][C]2.69235935590278[/C][C]2.564473625[/C][C]0.127885730902778[/C][C]0.489689644097223[/C][/ROW]
[ROW][C]27[/C][C]2.236319[/C][C]2.35175537673611[/C][C]2.50248858333333[/C][C]-0.150733206597223[/C][C]-0.115436376736111[/C][/ROW]
[ROW][C]28[/C][C]2.033218[/C][C]2.48097368229167[/C][C]2.42651579166667[/C][C]0.054457890625[/C][C]-0.447755682291666[/C][/ROW]
[ROW][C]29[/C][C]1.644804[/C][C]2.41032802256944[/C][C]2.36240645833333[/C][C]0.047921564236111[/C][C]-0.765524022569445[/C][/ROW]
[ROW][C]30[/C][C]1.627971[/C][C]2.13251921006944[/C][C]2.31039379166667[/C][C]-0.177874581597222[/C][C]-0.504548210069445[/C][/ROW]
[ROW][C]31[/C][C]1.677559[/C][C]2.10692148784722[/C][C]2.26263025[/C][C]-0.155708762152778[/C][C]-0.429362487847222[/C][/ROW]
[ROW][C]32[/C][C]2.330828[/C][C]2.40480152256944[/C][C]2.24747495833333[/C][C]0.157326564236111[/C][C]-0.0739735225694447[/C][/ROW]
[ROW][C]33[/C][C]2.493615[/C][C]2.29659458506944[/C][C]2.2648685[/C][C]0.0317260850694447[/C][C]0.197020414930555[/C][/ROW]
[ROW][C]34[/C][C]2.257172[/C][C]2.33442680034722[/C][C]2.33770591666667[/C][C]-0.00327911631944455[/C][C]-0.0772548003472222[/C][/ROW]
[ROW][C]35[/C][C]2.655517[/C][C]2.48045730729167[/C][C]2.44256045833333[/C][C]0.0378968489583335[/C][C]0.175059692708334[/C][/ROW]
[ROW][C]36[/C][C]2.298655[/C][C]2.53612330729167[/C][C]2.5522905[/C][C]-0.0161671927083335[/C][C]-0.237468307291666[/C][/ROW]
[ROW][C]37[/C][C]2.600402[/C][C]2.72014067534722[/C][C]2.6735925[/C][C]0.046548175347222[/C][C]-0.119738675347222[/C][/ROW]
[ROW][C]38[/C][C]3.04523[/C][C]2.91370985590278[/C][C]2.785824125[/C][C]0.127885730902778[/C][C]0.131520144097223[/C][/ROW]
[ROW][C]39[/C][C]2.790583[/C][C]2.70476541840278[/C][C]2.855498625[/C][C]-0.150733206597223[/C][C]0.0858175815972224[/C][/ROW]
[ROW][C]40[/C][C]3.227052[/C][C]2.954794515625[/C][C]2.900336625[/C][C]0.054457890625[/C][C]0.272257484375[/C][/ROW]
[ROW][C]41[/C][C]2.967479[/C][C]2.97959131423611[/C][C]2.93166975[/C][C]0.047921564236111[/C][C]-0.0121123142361101[/C][/ROW]
[ROW][C]42[/C][C]2.938817[/C][C]2.80090466840278[/C][C]2.97877925[/C][C]-0.177874581597222[/C][C]0.137912331597222[/C][/ROW]
[ROW][C]43[/C][C]3.277961[/C][C]2.87905794618056[/C][C]3.03476670833333[/C][C]-0.155708762152778[/C][C]0.398903053819445[/C][/ROW]
[ROW][C]44[/C][C]3.423985[/C][C]3.21343902256944[/C][C]3.05611245833333[/C][C]0.157326564236111[/C][C]0.210545977430556[/C][/ROW]
[ROW][C]45[/C][C]3.072646[/C][C]3.09452121006944[/C][C]3.062795125[/C][C]0.0317260850694447[/C][C]-0.0218752100694437[/C][/ROW]
[ROW][C]46[/C][C]2.754253[/C][C]3.05202350868056[/C][C]3.055302625[/C][C]-0.00327911631944455[/C][C]-0.297770508680556[/C][/ROW]
[ROW][C]47[/C][C]2.910431[/C][C]3.083294890625[/C][C]3.04539804166667[/C][C]0.0378968489583335[/C][C]-0.172863890625[/C][/ROW]
[ROW][C]48[/C][C]3.174369[/C][C]3.031685640625[/C][C]3.04785283333333[/C][C]-0.0161671927083335[/C][C]0.142683359374999[/C][/ROW]
[ROW][C]49[/C][C]3.068387[/C][C]3.06997567534722[/C][C]3.0234275[/C][C]0.046548175347222[/C][C]-0.00158867534722207[/C][/ROW]
[ROW][C]50[/C][C]3.089543[/C][C]3.11744627256944[/C][C]2.98956054166667[/C][C]0.127885730902778[/C][C]-0.0279032725694446[/C][/ROW]
[ROW][C]51[/C][C]2.906654[/C][C]2.82957229340278[/C][C]2.9803055[/C][C]-0.150733206597223[/C][C]0.0770817065972227[/C][/ROW]
[ROW][C]52[/C][C]2.931161[/C][C]3.039486890625[/C][C]2.985029[/C][C]0.054457890625[/C][C]-0.108325890625[/C][/ROW]
[ROW][C]53[/C][C]3.02566[/C][C]3.04182518923611[/C][C]2.993903625[/C][C]0.047921564236111[/C][C]-0.0161651892361108[/C][/ROW]
[ROW][C]54[/C][C]2.939551[/C][C]2.81529429340278[/C][C]2.993168875[/C][C]-0.177874581597222[/C][C]0.124256706597222[/C][/ROW]
[ROW][C]55[/C][C]2.691019[/C][C]2.82393348784722[/C][C]2.97964225[/C][C]-0.155708762152778[/C][C]-0.132914487847223[/C][/ROW]
[ROW][C]56[/C][C]3.19812[/C][C]3.12713068923611[/C][C]2.969804125[/C][C]0.157326564236111[/C][C]0.0709893107638893[/C][/ROW]
[ROW][C]57[/C][C]3.07639[/C][C]3.00237312673611[/C][C]2.97064704166667[/C][C]0.0317260850694447[/C][C]0.0740168732638886[/C][/ROW]
[ROW][C]58[/C][C]2.863873[/C][C]2.98294325868056[/C][C]2.986222375[/C][C]-0.00327911631944455[/C][C]-0.119070258680555[/C][/ROW]
[ROW][C]59[/C][C]3.013802[/C][C]3.06155359895833[/C][C]3.02365675[/C][C]0.0378968489583335[/C][C]-0.0477515989583326[/C][/ROW]
[ROW][C]60[/C][C]3.053364[/C][C]3.054801265625[/C][C]3.07096845833333[/C][C]-0.0161671927083335[/C][C]-0.00143726562499902[/C][/ROW]
[ROW][C]61[/C][C]2.864753[/C][C]3.16601667534722[/C][C]3.1194685[/C][C]0.046548175347222[/C][C]-0.301263675347222[/C][/ROW]
[ROW][C]62[/C][C]3.057062[/C][C]3.28944360590278[/C][C]3.161557875[/C][C]0.127885730902778[/C][C]-0.232381605902777[/C][/ROW]
[ROW][C]63[/C][C]2.959365[/C][C]3.03699162673611[/C][C]3.18772483333333[/C][C]-0.150733206597223[/C][C]-0.0776266267361105[/C][/ROW]
[ROW][C]64[/C][C]3.252258[/C][C]3.273923015625[/C][C]3.219465125[/C][C]0.054457890625[/C][C]-0.0216650156249996[/C][/ROW]
[ROW][C]65[/C][C]3.602988[/C][C]3.31017193923611[/C][C]3.262250375[/C][C]0.047921564236111[/C][C]0.292816060763889[/C][/ROW]
[ROW][C]66[/C][C]3.497704[/C][C]3.11928300173611[/C][C]3.29715758333333[/C][C]-0.177874581597222[/C][C]0.37842099826389[/C][/ROW]
[ROW][C]67[/C][C]3.296867[/C][C]3.18239807118056[/C][C]3.33810683333333[/C][C]-0.155708762152778[/C][C]0.114468928819445[/C][/ROW]
[ROW][C]68[/C][C]3.602417[/C][C]3.52779002256944[/C][C]3.37046345833333[/C][C]0.157326564236111[/C][C]0.0746269774305559[/C][/ROW]
[ROW][C]69[/C][C]3.3001[/C][C]3.39733371006944[/C][C]3.365607625[/C][C]0.0317260850694447[/C][C]-0.0972337100694438[/C][/ROW]
[ROW][C]70[/C][C]3.40193[/C][C]3.33272330034722[/C][C]3.33600241666667[/C][C]-0.00327911631944455[/C][C]0.0692066996527783[/C][/ROW]
[ROW][C]71[/C][C]3.502591[/C][C]3.32574993229167[/C][C]3.28785308333333[/C][C]0.0378968489583335[/C][C]0.176841067708334[/C][/ROW]
[ROW][C]72[/C][C]3.402348[/C][C]3.213302140625[/C][C]3.22946933333333[/C][C]-0.0161671927083335[/C][C]0.189045859375[/C][/ROW]
[ROW][C]73[/C][C]3.498551[/C][C]3.20961021701389[/C][C]3.16306204166667[/C][C]0.046548175347222[/C][C]0.288940782986111[/C][/ROW]
[ROW][C]74[/C][C]3.199823[/C][C]3.20358868923611[/C][C]3.07570295833333[/C][C]0.127885730902778[/C][C]-0.00376568923611087[/C][/ROW]
[ROW][C]75[/C][C]2.700064[/C][C]2.82924216840278[/C][C]2.979975375[/C][C]-0.150733206597223[/C][C]-0.129178168402778[/C][/ROW]
[ROW][C]76[/C][C]2.801034[/C][C]2.934553890625[/C][C]2.880096[/C][C]0.054457890625[/C][C]-0.133519890625[/C][/ROW]
[ROW][C]77[/C][C]2.898628[/C][C]2.80286614756944[/C][C]2.75494458333333[/C][C]0.047921564236111[/C][C]0.095761852430556[/C][/ROW]
[ROW][C]78[/C][C]2.800854[/C][C]2.41439658506944[/C][C]2.59227116666667[/C][C]-0.177874581597222[/C][C]0.386457414930556[/C][/ROW]
[ROW][C]79[/C][C]2.399942[/C][C]2.25747015451389[/C][C]2.41317891666667[/C][C]-0.155708762152778[/C][C]0.142471845486111[/C][/ROW]
[ROW][C]80[/C][C]2.402724[/C][C]2.39978293923611[/C][C]2.242456375[/C][C]0.157326564236111[/C][C]0.00294106076388889[/C][/ROW]
[ROW][C]81[/C][C]2.202331[/C][C]2.13247529340278[/C][C]2.10074920833333[/C][C]0.0317260850694447[/C][C]0.0698557065972221[/C][/ROW]
[ROW][C]82[/C][C]2.102594[/C][C]1.96816705034722[/C][C]1.97144616666667[/C][C]-0.00327911631944455[/C][C]0.134426949652778[/C][/ROW]
[ROW][C]83[/C][C]1.798293[/C][C]1.85940372395833[/C][C]1.821506875[/C][C]0.0378968489583335[/C][C]-0.0611107239583335[/C][/ROW]
[ROW][C]84[/C][C]1.202484[/C][C]1.644425890625[/C][C]1.66059308333333[/C][C]-0.0161671927083335[/C][C]-0.441941890624999[/C][/ROW]
[ROW][C]85[/C][C]1.400201[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]86[/C][C]1.200832[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]87[/C][C]1.298083[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]88[/C][C]1.099742[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]89[/C][C]1.001377[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]90[/C][C]0.836174[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116316&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116316&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
14.031636NANA0.046548175347222NA
23.702076NANA0.127885730902778NA
33.056167NANA-0.150733206597223NA
43.280707NANA0.054457890625NA
52.984728NANA0.047921564236111NA
63.693712NANA-0.177874581597222NA
73.2263172.952571946180563.10828070833333-0.1557087621527780.273745053819444
82.1903493.202453605902783.045127041666670.157326564236111-1.01210460590278
92.5995153.056404251736113.024678166666670.0317260850694447-0.456889251736111
103.0802883.052816800347223.05609591666667-0.003279116319444550.0274711996527781
112.9296723.1492283906253.111331541666670.0378968489583335-0.219556390624999
122.9225483.0848223906253.10098958333333-0.0161671927083335-0.162274390624999
133.2349433.098275508680563.051727333333330.0465481753472220.136667491319444
142.9830813.216291147569443.088405416666670.127885730902778-0.233210147569444
153.2843893.001098043402783.15183125-0.1507332065972230.283290956597223
163.8065113.243552932291673.189095041666670.0544578906250.562958067708333
173.7845793.255406314236113.207484750.0479215642361110.529172685763889
182.6456543.044204168402783.22207875-0.177874581597222-0.398550168402778
193.0920813.061698779513893.21740754166667-0.1557087621527780.0303822204861115
203.2048593.366039730902783.208713166666670.157326564236111-0.161180730902777
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812.2023312.132475293402782.100749208333330.03172608506944470.0698557065972221
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851.400201NANANANA
861.200832NANANANA
871.298083NANANANA
881.099742NANANANA
891.001377NANANANA
900.836174NANANANA


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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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')