FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decomposeloess.wasp
Title produced by softwareDecomposition by Loess
Date of computationThu, 03 Dec 2009 10:54:46 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/03/t12598629279gv7ix2is1qr9fq.htm/, Retrieved Thu, 25 Apr 2024 02:32:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62994, Retrieved Thu, 25 Apr 2024 02:32:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Decomposition by Loess] [] [2009-11-27 15:00:29] [b98453cac15ba1066b407e146608df68]
-   PD      [Decomposition by Loess] [workshop 9 bereke...] [2009-12-03 17:54:46] [78d370e6d5f4594e9982a5085e7604c6] [Current]
-   PD        [Decomposition by Loess] [review workshop 9] [2009-12-04 10:31:35] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D          [Decomposition by Loess] [review workshop 9] [2009-12-06 10:43:18] [eaf42bcf5162b5692bb3c7f9d4636222]
-   PD        [Decomposition by Loess] [] [2009-12-09 16:12:31] [3425351e86519d261a643e224a0c8ee1]
-   P         [Decomposition by Loess] [] [2009-12-12 17:01:18] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4716.99
4926.65
4920.10
5170.09
5246.24
5283.61
4979.05
4825.20
4695.12
4711.54
4727.22
4384.96
4378.75
4472.93
4564.07
4310.54
4171.38
4049.38
3591.37
3720.46
4107.23
4101.71
4162.34
4136.22
4125.88
4031.48
3761.36
3408.56
3228.47
3090.45
2741.14
2980.44
3104.33
3181.57
2863.86
2898.01
3112.33
3254.33
3513.47
3587.61
3727.45
3793.34
3817.58
3845.13
3931.86
4197.52
4307.13
4229.43
4362.28
4217.34
4361.28
4327.74
4417.65
4557.68
4650.35
4967.18
5123.42
5290.85
5535.66
5514.06
5493.88
5694.83
5850.41
6116.64
6175.00
6513.58
6383.78
6673.66
6936.61
7300.68
7392.93
7497.31
7584.71
7160.79
7196.19
7245.63
7347.51
7425.75
7778.51
7822.33
8181.22
8371.47
8347.71
8672.11
8802.79
9138.46
9123.29
9023.21
8850.41
8864.58
9163.74
8516.66
8553.44
7555.20
7851.22
7442.00
7992.53
8264.04
7517.39
7200.40
7193.69
6193.58
5104.21
4800.46
4461.61
4398.59
4243.63
4293.82

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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62994&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62994&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62994&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' @ 72.249.127.135






Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal10810109
Trend1912
Low-pass1312

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Parameters \tabularnewline
Component & Window & Degree & Jump \tabularnewline
Seasonal & 1081 & 0 & 109 \tabularnewline
Trend & 19 & 1 & 2 \tabularnewline
Low-pass & 13 & 1 & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62994&T=1

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Parameters[/C][/ROW]
[ROW][C]Component[/C][C]Window[/C][C]Degree[/C][C]Jump[/C][/ROW]
[ROW][C]Seasonal[/C][C]1081[/C][C]0[/C][C]109[/C][/ROW]
[ROW][C]Trend[/C][C]19[/C][C]1[/C][C]2[/C][/ROW]
[ROW][C]Low-pass[/C][C]13[/C][C]1[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62994&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62994&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:

Seasonal Decomposition by Loess - Parameters
ComponentWindowDegreeJump
Seasonal10810109
Trend1912
Low-pass1312






Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
14716.994338.4205784131455.42886517781085040.13055640905-378.569421586862
24926.654713.49299084938125.2042545657425014.60275458488-213.157009150625
34920.14761.0339086627290.0911385765654989.07495276072-159.066091337280
45170.095329.2865313482753.82609390054224957.06737475119159.196531348271
55246.245507.1347282950460.2854749633024925.05979674166260.894728295041
65283.615675.575623594941.376052289899924890.26832411516391.965623594941
74979.055268.64204696551-166.018898454174855.47685148866289.59204696551
84825.24995.98984245107-165.5662756841914819.97643323312170.789842451069
94695.124659.59658761483-53.83260259241614784.47601497758-35.5234123851687
104711.544738.37007576279-33.84517193619914718.5550961734126.8300757627912
114727.224781.4103757274820.39544690328964652.6341773692354.1903757274804
124384.964198.3625938693112.65544681294244558.90195931774-186.597406130687
134378.754236.9013935559355.42886517781084465.16974126626-141.848606444069
144472.934439.18323198675125.2042545657424381.47251344751-33.7467680132495
154564.074740.2735757946890.0911385765654297.77528562876176.203575794676
164310.544324.7479450795553.82609390054224242.5059610199114.2079450795454
174171.384095.2378886256360.2854749633024187.23663641107-76.1421113743672
184049.383944.744450429161.376052289899924152.63949728094-104.635549570839
193591.373230.71654030336-166.018898454174118.04235815081-360.653459696643
203720.463525.28946838467-165.5662756841914081.19680729952-195.170531615332
214107.234223.94134614418-53.83260259241614044.35125644823116.711346144183
224101.714248.67005716257-33.84517193619913988.59511477363146.960057162572
234162.344371.4455799976920.39544690328963932.83897309902209.105579997688
244136.224400.5222567763812.65544681294243859.26229641067264.302256776384
254125.884410.6455150998655.42886517781083785.68561972233284.765515099863
264031.484238.97659647825125.2042545657423698.77914895601207.496596478247
273761.363820.7561832337490.0911385765653611.872678189759.3961832337382
283408.563249.4505365799853.82609390054223513.84336951948-159.109463420021
293228.472980.8404641874460.2854749633023415.81406084926-247.629535812563
303090.452855.091835395691.376052289899923324.43211231441-235.358164604309
312741.142415.24873467461-166.018898454173233.05016377956-325.891265325388
322980.442945.535761135-165.5662756841913180.91051454919-34.9042388650009
333104.333133.72173727359-53.83260259241613128.7708653188329.3917372735891
343181.573260.21780175005-33.84517193619913136.7673701861578.6478017500535
352863.862562.5606780432520.39544690328963144.76387505346-301.299321956754
362898.012583.1582042697612.65544681294243200.20634891729-314.851795730237
373112.332913.5823120410755.42886517781083255.64882278112-198.747687958934
383254.333046.86195523638125.2042545657423336.59379019788-207.46804476362
393513.473519.310103808890.0911385765653417.538757614635.84010380880181
403587.613603.5421190150953.82609390054223517.8517870843715.9321190150881
413727.453776.4497084825960.2854749633023618.1648165541148.9997084825918
423793.343860.111973335551.376052289899923725.1919743745566.7719733355507
433817.583968.95976625918-166.018898454173832.21913219499151.379766259177
443845.133937.16721505402-165.5662756841913918.6590606301792.0372150540247
453931.863912.45361352708-53.83260259241614005.09898906534-19.4063864729246
464197.524360.70853490986-33.84517193619914068.17663702634163.188534909864
474307.134462.6102681093820.39544690328964131.25428498733155.480268109380
484229.434254.4762412544212.65544681294244191.7283119326425.0462412544202
494362.284416.9287959442455.42886517781084252.2023388779454.6487959442447
504217.343980.54554489313125.2042545657424328.93020054113-236.794455106868
514361.284226.8107992191390.0911385765654405.65806220431-134.469200780874
524327.744098.4796758700853.82609390054224503.17423022938-229.260324129918
534417.654174.3241267822660.2854749633024600.69039825444-243.325873217742
544557.684400.747948503881.376052289899924713.23599920622-156.932051496117
554650.354640.93729829617-166.018898454174825.781600158-9.4127017038254
564967.185148.32611854529-165.5662756841914951.6001571389181.146118545291
575123.425223.25388847261-53.83260259241615077.4187141198099.8338884726118
585290.855401.43454954525-33.84517193619915214.11062239095110.584549545245
595535.665700.122022434620.39544690328965350.80253066210164.462022434605
605514.065522.5747863290912.65544681294245492.889766857978.5147863290913
615493.885297.3541317683655.42886517781085634.97700305383-196.52586823164
625694.835482.9956371608125.2042545657425781.46010827346-211.834362839200
635850.415682.7856479303590.0911385765655927.94321349309-167.624352069654
646116.646090.5816755752553.82609390054226088.87223052421-26.0583244247518
6561756039.9132774813760.2854749633026249.80124755533-135.086722518632
666513.586607.768033081351.376052289899926418.0159146287594.1880330813465
676383.786347.348316752-166.018898454176586.23058170218-36.4316832480063
686673.666782.66155087675-165.5662756841916730.22472480744109.001550876751
696936.617052.83373467971-53.83260259241616874.2188679127116.223734679712
707300.687656.92867258841-33.84517193619916978.27649934779356.248672588407
717392.937683.1304223138320.39544690328967082.33413078288290.200422313831
727497.317816.1271779252312.65544681294247165.83737526183318.81717792523
737584.717864.6505150814155.42886517781087249.34061974078279.940515081414
747160.796864.25997175526125.2042545657427332.115773679-296.530028244738
757196.196887.3979338062290.0911385765657414.89092761722-308.792066193782
767245.636933.3153636139153.82609390054227504.11854248554-312.314636386085
777347.517041.3883676828360.2854749633027593.34615735387-306.12163231717
787425.757143.957294271981.376052289899927706.16665343812-281.792705728024
797778.517904.0517489318-166.018898454177818.98714952238125.541748931792
807822.337844.79889990724-165.5662756841917965.4273757769522.4688999072423
818181.228304.4050005609-53.83260259241618111.86760203152123.185000560897
828371.478517.06250446234-33.84517193619918259.72266747386145.592504462338
838347.718267.4468201805120.39544690328968407.5777329162-80.2631798194907
848672.118807.2563678033412.65544681294248524.30818538372135.146367803338
858802.798909.1124969709555.42886517781088641.03863785124106.322496970946
869138.469449.24260553694125.2042545657428702.47313989732310.782605536941
879123.299392.5812194800590.0911385765658763.9076419434269.291219480045
889023.219244.8207279457553.82609390054228747.77317815371221.610727945746
898850.418908.8958106726760.2854749633028731.6387143640358.4858106726679
908864.589074.992606748411.376052289899928652.79134096169210.412606748410
919163.749919.55493089482-166.018898454178573.94396755935755.814930894818
928516.668737.89146462115-165.5662756841918460.99481106305221.231464621145
938553.448812.66694802568-53.83260259241618348.04565456674259.226948025675
947555.26946.3414598409-33.84517193619918197.9037120953-608.858540159095
957851.227634.2827834728720.39544690328968047.76176962385-216.937216527135
9674427042.2775420281412.65544681294247829.06701115892-399.722457971861
977992.538319.258882128255.42886517781087610.372252694326.728882128196
988264.049075.98855241598125.2042545657427326.88719301828811.948552415976
997517.397901.2867280808690.0911385765657043.40213334257383.896728080863
1007200.47646.9735839107753.82609390054226700.00032218869446.573583910772
1017193.697970.496014001960.2854749633026356.5985110348776.8060140019
1026193.586365.037083732161.376052289899926020.74686397794171.457083732164
1035104.214689.5436815331-166.018898454175684.89521692107-414.666318466902
1044800.464428.98922579075-165.5662756841915337.49704989344-371.470774209246
1054461.613986.95371972661-53.83260259241614990.0988828658-474.656280273386
1064398.594199.34538734006-33.84517193619914631.67978459614-199.24461265994
1074243.634193.6038667702320.39544690328964273.26068632648-50.0261332297659
1084293.824664.7750517634912.65544681294243910.20950142356370.955051763493

\begin{tabular}{lllllllll}
\hline
Seasonal Decomposition by Loess - Time Series Components \tabularnewline
t & Observed & Fitted & Seasonal & Trend & Remainder \tabularnewline
1 & 4716.99 & 4338.42057841314 & 55.4288651778108 & 5040.13055640905 & -378.569421586862 \tabularnewline
2 & 4926.65 & 4713.49299084938 & 125.204254565742 & 5014.60275458488 & -213.157009150625 \tabularnewline
3 & 4920.1 & 4761.03390866272 & 90.091138576565 & 4989.07495276072 & -159.066091337280 \tabularnewline
4 & 5170.09 & 5329.28653134827 & 53.8260939005422 & 4957.06737475119 & 159.196531348271 \tabularnewline
5 & 5246.24 & 5507.13472829504 & 60.285474963302 & 4925.05979674166 & 260.894728295041 \tabularnewline
6 & 5283.61 & 5675.57562359494 & 1.37605228989992 & 4890.26832411516 & 391.965623594941 \tabularnewline
7 & 4979.05 & 5268.64204696551 & -166.01889845417 & 4855.47685148866 & 289.59204696551 \tabularnewline
8 & 4825.2 & 4995.98984245107 & -165.566275684191 & 4819.97643323312 & 170.789842451069 \tabularnewline
9 & 4695.12 & 4659.59658761483 & -53.8326025924161 & 4784.47601497758 & -35.5234123851687 \tabularnewline
10 & 4711.54 & 4738.37007576279 & -33.8451719361991 & 4718.55509617341 & 26.8300757627912 \tabularnewline
11 & 4727.22 & 4781.41037572748 & 20.3954469032896 & 4652.63417736923 & 54.1903757274804 \tabularnewline
12 & 4384.96 & 4198.36259386931 & 12.6554468129424 & 4558.90195931774 & -186.597406130687 \tabularnewline
13 & 4378.75 & 4236.90139355593 & 55.4288651778108 & 4465.16974126626 & -141.848606444069 \tabularnewline
14 & 4472.93 & 4439.18323198675 & 125.204254565742 & 4381.47251344751 & -33.7467680132495 \tabularnewline
15 & 4564.07 & 4740.27357579468 & 90.091138576565 & 4297.77528562876 & 176.203575794676 \tabularnewline
16 & 4310.54 & 4324.74794507955 & 53.8260939005422 & 4242.50596101991 & 14.2079450795454 \tabularnewline
17 & 4171.38 & 4095.23788862563 & 60.285474963302 & 4187.23663641107 & -76.1421113743672 \tabularnewline
18 & 4049.38 & 3944.74445042916 & 1.37605228989992 & 4152.63949728094 & -104.635549570839 \tabularnewline
19 & 3591.37 & 3230.71654030336 & -166.01889845417 & 4118.04235815081 & -360.653459696643 \tabularnewline
20 & 3720.46 & 3525.28946838467 & -165.566275684191 & 4081.19680729952 & -195.170531615332 \tabularnewline
21 & 4107.23 & 4223.94134614418 & -53.8326025924161 & 4044.35125644823 & 116.711346144183 \tabularnewline
22 & 4101.71 & 4248.67005716257 & -33.8451719361991 & 3988.59511477363 & 146.960057162572 \tabularnewline
23 & 4162.34 & 4371.44557999769 & 20.3954469032896 & 3932.83897309902 & 209.105579997688 \tabularnewline
24 & 4136.22 & 4400.52225677638 & 12.6554468129424 & 3859.26229641067 & 264.302256776384 \tabularnewline
25 & 4125.88 & 4410.64551509986 & 55.4288651778108 & 3785.68561972233 & 284.765515099863 \tabularnewline
26 & 4031.48 & 4238.97659647825 & 125.204254565742 & 3698.77914895601 & 207.496596478247 \tabularnewline
27 & 3761.36 & 3820.75618323374 & 90.091138576565 & 3611.8726781897 & 59.3961832337382 \tabularnewline
28 & 3408.56 & 3249.45053657998 & 53.8260939005422 & 3513.84336951948 & -159.109463420021 \tabularnewline
29 & 3228.47 & 2980.84046418744 & 60.285474963302 & 3415.81406084926 & -247.629535812563 \tabularnewline
30 & 3090.45 & 2855.09183539569 & 1.37605228989992 & 3324.43211231441 & -235.358164604309 \tabularnewline
31 & 2741.14 & 2415.24873467461 & -166.01889845417 & 3233.05016377956 & -325.891265325388 \tabularnewline
32 & 2980.44 & 2945.535761135 & -165.566275684191 & 3180.91051454919 & -34.9042388650009 \tabularnewline
33 & 3104.33 & 3133.72173727359 & -53.8326025924161 & 3128.77086531883 & 29.3917372735891 \tabularnewline
34 & 3181.57 & 3260.21780175005 & -33.8451719361991 & 3136.76737018615 & 78.6478017500535 \tabularnewline
35 & 2863.86 & 2562.56067804325 & 20.3954469032896 & 3144.76387505346 & -301.299321956754 \tabularnewline
36 & 2898.01 & 2583.15820426976 & 12.6554468129424 & 3200.20634891729 & -314.851795730237 \tabularnewline
37 & 3112.33 & 2913.58231204107 & 55.4288651778108 & 3255.64882278112 & -198.747687958934 \tabularnewline
38 & 3254.33 & 3046.86195523638 & 125.204254565742 & 3336.59379019788 & -207.46804476362 \tabularnewline
39 & 3513.47 & 3519.3101038088 & 90.091138576565 & 3417.53875761463 & 5.84010380880181 \tabularnewline
40 & 3587.61 & 3603.54211901509 & 53.8260939005422 & 3517.85178708437 & 15.9321190150881 \tabularnewline
41 & 3727.45 & 3776.44970848259 & 60.285474963302 & 3618.16481655411 & 48.9997084825918 \tabularnewline
42 & 3793.34 & 3860.11197333555 & 1.37605228989992 & 3725.19197437455 & 66.7719733355507 \tabularnewline
43 & 3817.58 & 3968.95976625918 & -166.01889845417 & 3832.21913219499 & 151.379766259177 \tabularnewline
44 & 3845.13 & 3937.16721505402 & -165.566275684191 & 3918.65906063017 & 92.0372150540247 \tabularnewline
45 & 3931.86 & 3912.45361352708 & -53.8326025924161 & 4005.09898906534 & -19.4063864729246 \tabularnewline
46 & 4197.52 & 4360.70853490986 & -33.8451719361991 & 4068.17663702634 & 163.188534909864 \tabularnewline
47 & 4307.13 & 4462.61026810938 & 20.3954469032896 & 4131.25428498733 & 155.480268109380 \tabularnewline
48 & 4229.43 & 4254.47624125442 & 12.6554468129424 & 4191.72831193264 & 25.0462412544202 \tabularnewline
49 & 4362.28 & 4416.92879594424 & 55.4288651778108 & 4252.20233887794 & 54.6487959442447 \tabularnewline
50 & 4217.34 & 3980.54554489313 & 125.204254565742 & 4328.93020054113 & -236.794455106868 \tabularnewline
51 & 4361.28 & 4226.81079921913 & 90.091138576565 & 4405.65806220431 & -134.469200780874 \tabularnewline
52 & 4327.74 & 4098.47967587008 & 53.8260939005422 & 4503.17423022938 & -229.260324129918 \tabularnewline
53 & 4417.65 & 4174.32412678226 & 60.285474963302 & 4600.69039825444 & -243.325873217742 \tabularnewline
54 & 4557.68 & 4400.74794850388 & 1.37605228989992 & 4713.23599920622 & -156.932051496117 \tabularnewline
55 & 4650.35 & 4640.93729829617 & -166.01889845417 & 4825.781600158 & -9.4127017038254 \tabularnewline
56 & 4967.18 & 5148.32611854529 & -165.566275684191 & 4951.6001571389 & 181.146118545291 \tabularnewline
57 & 5123.42 & 5223.25388847261 & -53.8326025924161 & 5077.41871411980 & 99.8338884726118 \tabularnewline
58 & 5290.85 & 5401.43454954525 & -33.8451719361991 & 5214.11062239095 & 110.584549545245 \tabularnewline
59 & 5535.66 & 5700.1220224346 & 20.3954469032896 & 5350.80253066210 & 164.462022434605 \tabularnewline
60 & 5514.06 & 5522.57478632909 & 12.6554468129424 & 5492.88976685797 & 8.5147863290913 \tabularnewline
61 & 5493.88 & 5297.35413176836 & 55.4288651778108 & 5634.97700305383 & -196.52586823164 \tabularnewline
62 & 5694.83 & 5482.9956371608 & 125.204254565742 & 5781.46010827346 & -211.834362839200 \tabularnewline
63 & 5850.41 & 5682.78564793035 & 90.091138576565 & 5927.94321349309 & -167.624352069654 \tabularnewline
64 & 6116.64 & 6090.58167557525 & 53.8260939005422 & 6088.87223052421 & -26.0583244247518 \tabularnewline
65 & 6175 & 6039.91327748137 & 60.285474963302 & 6249.80124755533 & -135.086722518632 \tabularnewline
66 & 6513.58 & 6607.76803308135 & 1.37605228989992 & 6418.01591462875 & 94.1880330813465 \tabularnewline
67 & 6383.78 & 6347.348316752 & -166.01889845417 & 6586.23058170218 & -36.4316832480063 \tabularnewline
68 & 6673.66 & 6782.66155087675 & -165.566275684191 & 6730.22472480744 & 109.001550876751 \tabularnewline
69 & 6936.61 & 7052.83373467971 & -53.8326025924161 & 6874.2188679127 & 116.223734679712 \tabularnewline
70 & 7300.68 & 7656.92867258841 & -33.8451719361991 & 6978.27649934779 & 356.248672588407 \tabularnewline
71 & 7392.93 & 7683.13042231383 & 20.3954469032896 & 7082.33413078288 & 290.200422313831 \tabularnewline
72 & 7497.31 & 7816.12717792523 & 12.6554468129424 & 7165.83737526183 & 318.81717792523 \tabularnewline
73 & 7584.71 & 7864.65051508141 & 55.4288651778108 & 7249.34061974078 & 279.940515081414 \tabularnewline
74 & 7160.79 & 6864.25997175526 & 125.204254565742 & 7332.115773679 & -296.530028244738 \tabularnewline
75 & 7196.19 & 6887.39793380622 & 90.091138576565 & 7414.89092761722 & -308.792066193782 \tabularnewline
76 & 7245.63 & 6933.31536361391 & 53.8260939005422 & 7504.11854248554 & -312.314636386085 \tabularnewline
77 & 7347.51 & 7041.38836768283 & 60.285474963302 & 7593.34615735387 & -306.12163231717 \tabularnewline
78 & 7425.75 & 7143.95729427198 & 1.37605228989992 & 7706.16665343812 & -281.792705728024 \tabularnewline
79 & 7778.51 & 7904.0517489318 & -166.01889845417 & 7818.98714952238 & 125.541748931792 \tabularnewline
80 & 7822.33 & 7844.79889990724 & -165.566275684191 & 7965.42737577695 & 22.4688999072423 \tabularnewline
81 & 8181.22 & 8304.4050005609 & -53.8326025924161 & 8111.86760203152 & 123.185000560897 \tabularnewline
82 & 8371.47 & 8517.06250446234 & -33.8451719361991 & 8259.72266747386 & 145.592504462338 \tabularnewline
83 & 8347.71 & 8267.44682018051 & 20.3954469032896 & 8407.5777329162 & -80.2631798194907 \tabularnewline
84 & 8672.11 & 8807.25636780334 & 12.6554468129424 & 8524.30818538372 & 135.146367803338 \tabularnewline
85 & 8802.79 & 8909.11249697095 & 55.4288651778108 & 8641.03863785124 & 106.322496970946 \tabularnewline
86 & 9138.46 & 9449.24260553694 & 125.204254565742 & 8702.47313989732 & 310.782605536941 \tabularnewline
87 & 9123.29 & 9392.58121948005 & 90.091138576565 & 8763.9076419434 & 269.291219480045 \tabularnewline
88 & 9023.21 & 9244.82072794575 & 53.8260939005422 & 8747.77317815371 & 221.610727945746 \tabularnewline
89 & 8850.41 & 8908.89581067267 & 60.285474963302 & 8731.63871436403 & 58.4858106726679 \tabularnewline
90 & 8864.58 & 9074.99260674841 & 1.37605228989992 & 8652.79134096169 & 210.412606748410 \tabularnewline
91 & 9163.74 & 9919.55493089482 & -166.01889845417 & 8573.94396755935 & 755.814930894818 \tabularnewline
92 & 8516.66 & 8737.89146462115 & -165.566275684191 & 8460.99481106305 & 221.231464621145 \tabularnewline
93 & 8553.44 & 8812.66694802568 & -53.8326025924161 & 8348.04565456674 & 259.226948025675 \tabularnewline
94 & 7555.2 & 6946.3414598409 & -33.8451719361991 & 8197.9037120953 & -608.858540159095 \tabularnewline
95 & 7851.22 & 7634.28278347287 & 20.3954469032896 & 8047.76176962385 & -216.937216527135 \tabularnewline
96 & 7442 & 7042.27754202814 & 12.6554468129424 & 7829.06701115892 & -399.722457971861 \tabularnewline
97 & 7992.53 & 8319.2588821282 & 55.4288651778108 & 7610.372252694 & 326.728882128196 \tabularnewline
98 & 8264.04 & 9075.98855241598 & 125.204254565742 & 7326.88719301828 & 811.948552415976 \tabularnewline
99 & 7517.39 & 7901.28672808086 & 90.091138576565 & 7043.40213334257 & 383.896728080863 \tabularnewline
100 & 7200.4 & 7646.97358391077 & 53.8260939005422 & 6700.00032218869 & 446.573583910772 \tabularnewline
101 & 7193.69 & 7970.4960140019 & 60.285474963302 & 6356.5985110348 & 776.8060140019 \tabularnewline
102 & 6193.58 & 6365.03708373216 & 1.37605228989992 & 6020.74686397794 & 171.457083732164 \tabularnewline
103 & 5104.21 & 4689.5436815331 & -166.01889845417 & 5684.89521692107 & -414.666318466902 \tabularnewline
104 & 4800.46 & 4428.98922579075 & -165.566275684191 & 5337.49704989344 & -371.470774209246 \tabularnewline
105 & 4461.61 & 3986.95371972661 & -53.8326025924161 & 4990.0988828658 & -474.656280273386 \tabularnewline
106 & 4398.59 & 4199.34538734006 & -33.8451719361991 & 4631.67978459614 & -199.24461265994 \tabularnewline
107 & 4243.63 & 4193.60386677023 & 20.3954469032896 & 4273.26068632648 & -50.0261332297659 \tabularnewline
108 & 4293.82 & 4664.77505176349 & 12.6554468129424 & 3910.20950142356 & 370.955051763493 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62994&T=2

[TABLE]
[ROW][C]Seasonal Decomposition by Loess - Time Series Components[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Fitted[/C][C]Seasonal[/C][C]Trend[/C][C]Remainder[/C][/ROW]
[ROW][C]1[/C][C]4716.99[/C][C]4338.42057841314[/C][C]55.4288651778108[/C][C]5040.13055640905[/C][C]-378.569421586862[/C][/ROW]
[ROW][C]2[/C][C]4926.65[/C][C]4713.49299084938[/C][C]125.204254565742[/C][C]5014.60275458488[/C][C]-213.157009150625[/C][/ROW]
[ROW][C]3[/C][C]4920.1[/C][C]4761.03390866272[/C][C]90.091138576565[/C][C]4989.07495276072[/C][C]-159.066091337280[/C][/ROW]
[ROW][C]4[/C][C]5170.09[/C][C]5329.28653134827[/C][C]53.8260939005422[/C][C]4957.06737475119[/C][C]159.196531348271[/C][/ROW]
[ROW][C]5[/C][C]5246.24[/C][C]5507.13472829504[/C][C]60.285474963302[/C][C]4925.05979674166[/C][C]260.894728295041[/C][/ROW]
[ROW][C]6[/C][C]5283.61[/C][C]5675.57562359494[/C][C]1.37605228989992[/C][C]4890.26832411516[/C][C]391.965623594941[/C][/ROW]
[ROW][C]7[/C][C]4979.05[/C][C]5268.64204696551[/C][C]-166.01889845417[/C][C]4855.47685148866[/C][C]289.59204696551[/C][/ROW]
[ROW][C]8[/C][C]4825.2[/C][C]4995.98984245107[/C][C]-165.566275684191[/C][C]4819.97643323312[/C][C]170.789842451069[/C][/ROW]
[ROW][C]9[/C][C]4695.12[/C][C]4659.59658761483[/C][C]-53.8326025924161[/C][C]4784.47601497758[/C][C]-35.5234123851687[/C][/ROW]
[ROW][C]10[/C][C]4711.54[/C][C]4738.37007576279[/C][C]-33.8451719361991[/C][C]4718.55509617341[/C][C]26.8300757627912[/C][/ROW]
[ROW][C]11[/C][C]4727.22[/C][C]4781.41037572748[/C][C]20.3954469032896[/C][C]4652.63417736923[/C][C]54.1903757274804[/C][/ROW]
[ROW][C]12[/C][C]4384.96[/C][C]4198.36259386931[/C][C]12.6554468129424[/C][C]4558.90195931774[/C][C]-186.597406130687[/C][/ROW]
[ROW][C]13[/C][C]4378.75[/C][C]4236.90139355593[/C][C]55.4288651778108[/C][C]4465.16974126626[/C][C]-141.848606444069[/C][/ROW]
[ROW][C]14[/C][C]4472.93[/C][C]4439.18323198675[/C][C]125.204254565742[/C][C]4381.47251344751[/C][C]-33.7467680132495[/C][/ROW]
[ROW][C]15[/C][C]4564.07[/C][C]4740.27357579468[/C][C]90.091138576565[/C][C]4297.77528562876[/C][C]176.203575794676[/C][/ROW]
[ROW][C]16[/C][C]4310.54[/C][C]4324.74794507955[/C][C]53.8260939005422[/C][C]4242.50596101991[/C][C]14.2079450795454[/C][/ROW]
[ROW][C]17[/C][C]4171.38[/C][C]4095.23788862563[/C][C]60.285474963302[/C][C]4187.23663641107[/C][C]-76.1421113743672[/C][/ROW]
[ROW][C]18[/C][C]4049.38[/C][C]3944.74445042916[/C][C]1.37605228989992[/C][C]4152.63949728094[/C][C]-104.635549570839[/C][/ROW]
[ROW][C]19[/C][C]3591.37[/C][C]3230.71654030336[/C][C]-166.01889845417[/C][C]4118.04235815081[/C][C]-360.653459696643[/C][/ROW]
[ROW][C]20[/C][C]3720.46[/C][C]3525.28946838467[/C][C]-165.566275684191[/C][C]4081.19680729952[/C][C]-195.170531615332[/C][/ROW]
[ROW][C]21[/C][C]4107.23[/C][C]4223.94134614418[/C][C]-53.8326025924161[/C][C]4044.35125644823[/C][C]116.711346144183[/C][/ROW]
[ROW][C]22[/C][C]4101.71[/C][C]4248.67005716257[/C][C]-33.8451719361991[/C][C]3988.59511477363[/C][C]146.960057162572[/C][/ROW]
[ROW][C]23[/C][C]4162.34[/C][C]4371.44557999769[/C][C]20.3954469032896[/C][C]3932.83897309902[/C][C]209.105579997688[/C][/ROW]
[ROW][C]24[/C][C]4136.22[/C][C]4400.52225677638[/C][C]12.6554468129424[/C][C]3859.26229641067[/C][C]264.302256776384[/C][/ROW]
[ROW][C]25[/C][C]4125.88[/C][C]4410.64551509986[/C][C]55.4288651778108[/C][C]3785.68561972233[/C][C]284.765515099863[/C][/ROW]
[ROW][C]26[/C][C]4031.48[/C][C]4238.97659647825[/C][C]125.204254565742[/C][C]3698.77914895601[/C][C]207.496596478247[/C][/ROW]
[ROW][C]27[/C][C]3761.36[/C][C]3820.75618323374[/C][C]90.091138576565[/C][C]3611.8726781897[/C][C]59.3961832337382[/C][/ROW]
[ROW][C]28[/C][C]3408.56[/C][C]3249.45053657998[/C][C]53.8260939005422[/C][C]3513.84336951948[/C][C]-159.109463420021[/C][/ROW]
[ROW][C]29[/C][C]3228.47[/C][C]2980.84046418744[/C][C]60.285474963302[/C][C]3415.81406084926[/C][C]-247.629535812563[/C][/ROW]
[ROW][C]30[/C][C]3090.45[/C][C]2855.09183539569[/C][C]1.37605228989992[/C][C]3324.43211231441[/C][C]-235.358164604309[/C][/ROW]
[ROW][C]31[/C][C]2741.14[/C][C]2415.24873467461[/C][C]-166.01889845417[/C][C]3233.05016377956[/C][C]-325.891265325388[/C][/ROW]
[ROW][C]32[/C][C]2980.44[/C][C]2945.535761135[/C][C]-165.566275684191[/C][C]3180.91051454919[/C][C]-34.9042388650009[/C][/ROW]
[ROW][C]33[/C][C]3104.33[/C][C]3133.72173727359[/C][C]-53.8326025924161[/C][C]3128.77086531883[/C][C]29.3917372735891[/C][/ROW]
[ROW][C]34[/C][C]3181.57[/C][C]3260.21780175005[/C][C]-33.8451719361991[/C][C]3136.76737018615[/C][C]78.6478017500535[/C][/ROW]
[ROW][C]35[/C][C]2863.86[/C][C]2562.56067804325[/C][C]20.3954469032896[/C][C]3144.76387505346[/C][C]-301.299321956754[/C][/ROW]
[ROW][C]36[/C][C]2898.01[/C][C]2583.15820426976[/C][C]12.6554468129424[/C][C]3200.20634891729[/C][C]-314.851795730237[/C][/ROW]
[ROW][C]37[/C][C]3112.33[/C][C]2913.58231204107[/C][C]55.4288651778108[/C][C]3255.64882278112[/C][C]-198.747687958934[/C][/ROW]
[ROW][C]38[/C][C]3254.33[/C][C]3046.86195523638[/C][C]125.204254565742[/C][C]3336.59379019788[/C][C]-207.46804476362[/C][/ROW]
[ROW][C]39[/C][C]3513.47[/C][C]3519.3101038088[/C][C]90.091138576565[/C][C]3417.53875761463[/C][C]5.84010380880181[/C][/ROW]
[ROW][C]40[/C][C]3587.61[/C][C]3603.54211901509[/C][C]53.8260939005422[/C][C]3517.85178708437[/C][C]15.9321190150881[/C][/ROW]
[ROW][C]41[/C][C]3727.45[/C][C]3776.44970848259[/C][C]60.285474963302[/C][C]3618.16481655411[/C][C]48.9997084825918[/C][/ROW]
[ROW][C]42[/C][C]3793.34[/C][C]3860.11197333555[/C][C]1.37605228989992[/C][C]3725.19197437455[/C][C]66.7719733355507[/C][/ROW]
[ROW][C]43[/C][C]3817.58[/C][C]3968.95976625918[/C][C]-166.01889845417[/C][C]3832.21913219499[/C][C]151.379766259177[/C][/ROW]
[ROW][C]44[/C][C]3845.13[/C][C]3937.16721505402[/C][C]-165.566275684191[/C][C]3918.65906063017[/C][C]92.0372150540247[/C][/ROW]
[ROW][C]45[/C][C]3931.86[/C][C]3912.45361352708[/C][C]-53.8326025924161[/C][C]4005.09898906534[/C][C]-19.4063864729246[/C][/ROW]
[ROW][C]46[/C][C]4197.52[/C][C]4360.70853490986[/C][C]-33.8451719361991[/C][C]4068.17663702634[/C][C]163.188534909864[/C][/ROW]
[ROW][C]47[/C][C]4307.13[/C][C]4462.61026810938[/C][C]20.3954469032896[/C][C]4131.25428498733[/C][C]155.480268109380[/C][/ROW]
[ROW][C]48[/C][C]4229.43[/C][C]4254.47624125442[/C][C]12.6554468129424[/C][C]4191.72831193264[/C][C]25.0462412544202[/C][/ROW]
[ROW][C]49[/C][C]4362.28[/C][C]4416.92879594424[/C][C]55.4288651778108[/C][C]4252.20233887794[/C][C]54.6487959442447[/C][/ROW]
[ROW][C]50[/C][C]4217.34[/C][C]3980.54554489313[/C][C]125.204254565742[/C][C]4328.93020054113[/C][C]-236.794455106868[/C][/ROW]
[ROW][C]51[/C][C]4361.28[/C][C]4226.81079921913[/C][C]90.091138576565[/C][C]4405.65806220431[/C][C]-134.469200780874[/C][/ROW]
[ROW][C]52[/C][C]4327.74[/C][C]4098.47967587008[/C][C]53.8260939005422[/C][C]4503.17423022938[/C][C]-229.260324129918[/C][/ROW]
[ROW][C]53[/C][C]4417.65[/C][C]4174.32412678226[/C][C]60.285474963302[/C][C]4600.69039825444[/C][C]-243.325873217742[/C][/ROW]
[ROW][C]54[/C][C]4557.68[/C][C]4400.74794850388[/C][C]1.37605228989992[/C][C]4713.23599920622[/C][C]-156.932051496117[/C][/ROW]
[ROW][C]55[/C][C]4650.35[/C][C]4640.93729829617[/C][C]-166.01889845417[/C][C]4825.781600158[/C][C]-9.4127017038254[/C][/ROW]
[ROW][C]56[/C][C]4967.18[/C][C]5148.32611854529[/C][C]-165.566275684191[/C][C]4951.6001571389[/C][C]181.146118545291[/C][/ROW]
[ROW][C]57[/C][C]5123.42[/C][C]5223.25388847261[/C][C]-53.8326025924161[/C][C]5077.41871411980[/C][C]99.8338884726118[/C][/ROW]
[ROW][C]58[/C][C]5290.85[/C][C]5401.43454954525[/C][C]-33.8451719361991[/C][C]5214.11062239095[/C][C]110.584549545245[/C][/ROW]
[ROW][C]59[/C][C]5535.66[/C][C]5700.1220224346[/C][C]20.3954469032896[/C][C]5350.80253066210[/C][C]164.462022434605[/C][/ROW]
[ROW][C]60[/C][C]5514.06[/C][C]5522.57478632909[/C][C]12.6554468129424[/C][C]5492.88976685797[/C][C]8.5147863290913[/C][/ROW]
[ROW][C]61[/C][C]5493.88[/C][C]5297.35413176836[/C][C]55.4288651778108[/C][C]5634.97700305383[/C][C]-196.52586823164[/C][/ROW]
[ROW][C]62[/C][C]5694.83[/C][C]5482.9956371608[/C][C]125.204254565742[/C][C]5781.46010827346[/C][C]-211.834362839200[/C][/ROW]
[ROW][C]63[/C][C]5850.41[/C][C]5682.78564793035[/C][C]90.091138576565[/C][C]5927.94321349309[/C][C]-167.624352069654[/C][/ROW]
[ROW][C]64[/C][C]6116.64[/C][C]6090.58167557525[/C][C]53.8260939005422[/C][C]6088.87223052421[/C][C]-26.0583244247518[/C][/ROW]
[ROW][C]65[/C][C]6175[/C][C]6039.91327748137[/C][C]60.285474963302[/C][C]6249.80124755533[/C][C]-135.086722518632[/C][/ROW]
[ROW][C]66[/C][C]6513.58[/C][C]6607.76803308135[/C][C]1.37605228989992[/C][C]6418.01591462875[/C][C]94.1880330813465[/C][/ROW]
[ROW][C]67[/C][C]6383.78[/C][C]6347.348316752[/C][C]-166.01889845417[/C][C]6586.23058170218[/C][C]-36.4316832480063[/C][/ROW]
[ROW][C]68[/C][C]6673.66[/C][C]6782.66155087675[/C][C]-165.566275684191[/C][C]6730.22472480744[/C][C]109.001550876751[/C][/ROW]
[ROW][C]69[/C][C]6936.61[/C][C]7052.83373467971[/C][C]-53.8326025924161[/C][C]6874.2188679127[/C][C]116.223734679712[/C][/ROW]
[ROW][C]70[/C][C]7300.68[/C][C]7656.92867258841[/C][C]-33.8451719361991[/C][C]6978.27649934779[/C][C]356.248672588407[/C][/ROW]
[ROW][C]71[/C][C]7392.93[/C][C]7683.13042231383[/C][C]20.3954469032896[/C][C]7082.33413078288[/C][C]290.200422313831[/C][/ROW]
[ROW][C]72[/C][C]7497.31[/C][C]7816.12717792523[/C][C]12.6554468129424[/C][C]7165.83737526183[/C][C]318.81717792523[/C][/ROW]
[ROW][C]73[/C][C]7584.71[/C][C]7864.65051508141[/C][C]55.4288651778108[/C][C]7249.34061974078[/C][C]279.940515081414[/C][/ROW]
[ROW][C]74[/C][C]7160.79[/C][C]6864.25997175526[/C][C]125.204254565742[/C][C]7332.115773679[/C][C]-296.530028244738[/C][/ROW]
[ROW][C]75[/C][C]7196.19[/C][C]6887.39793380622[/C][C]90.091138576565[/C][C]7414.89092761722[/C][C]-308.792066193782[/C][/ROW]
[ROW][C]76[/C][C]7245.63[/C][C]6933.31536361391[/C][C]53.8260939005422[/C][C]7504.11854248554[/C][C]-312.314636386085[/C][/ROW]
[ROW][C]77[/C][C]7347.51[/C][C]7041.38836768283[/C][C]60.285474963302[/C][C]7593.34615735387[/C][C]-306.12163231717[/C][/ROW]
[ROW][C]78[/C][C]7425.75[/C][C]7143.95729427198[/C][C]1.37605228989992[/C][C]7706.16665343812[/C][C]-281.792705728024[/C][/ROW]
[ROW][C]79[/C][C]7778.51[/C][C]7904.0517489318[/C][C]-166.01889845417[/C][C]7818.98714952238[/C][C]125.541748931792[/C][/ROW]
[ROW][C]80[/C][C]7822.33[/C][C]7844.79889990724[/C][C]-165.566275684191[/C][C]7965.42737577695[/C][C]22.4688999072423[/C][/ROW]
[ROW][C]81[/C][C]8181.22[/C][C]8304.4050005609[/C][C]-53.8326025924161[/C][C]8111.86760203152[/C][C]123.185000560897[/C][/ROW]
[ROW][C]82[/C][C]8371.47[/C][C]8517.06250446234[/C][C]-33.8451719361991[/C][C]8259.72266747386[/C][C]145.592504462338[/C][/ROW]
[ROW][C]83[/C][C]8347.71[/C][C]8267.44682018051[/C][C]20.3954469032896[/C][C]8407.5777329162[/C][C]-80.2631798194907[/C][/ROW]
[ROW][C]84[/C][C]8672.11[/C][C]8807.25636780334[/C][C]12.6554468129424[/C][C]8524.30818538372[/C][C]135.146367803338[/C][/ROW]
[ROW][C]85[/C][C]8802.79[/C][C]8909.11249697095[/C][C]55.4288651778108[/C][C]8641.03863785124[/C][C]106.322496970946[/C][/ROW]
[ROW][C]86[/C][C]9138.46[/C][C]9449.24260553694[/C][C]125.204254565742[/C][C]8702.47313989732[/C][C]310.782605536941[/C][/ROW]
[ROW][C]87[/C][C]9123.29[/C][C]9392.58121948005[/C][C]90.091138576565[/C][C]8763.9076419434[/C][C]269.291219480045[/C][/ROW]
[ROW][C]88[/C][C]9023.21[/C][C]9244.82072794575[/C][C]53.8260939005422[/C][C]8747.77317815371[/C][C]221.610727945746[/C][/ROW]
[ROW][C]89[/C][C]8850.41[/C][C]8908.89581067267[/C][C]60.285474963302[/C][C]8731.63871436403[/C][C]58.4858106726679[/C][/ROW]
[ROW][C]90[/C][C]8864.58[/C][C]9074.99260674841[/C][C]1.37605228989992[/C][C]8652.79134096169[/C][C]210.412606748410[/C][/ROW]
[ROW][C]91[/C][C]9163.74[/C][C]9919.55493089482[/C][C]-166.01889845417[/C][C]8573.94396755935[/C][C]755.814930894818[/C][/ROW]
[ROW][C]92[/C][C]8516.66[/C][C]8737.89146462115[/C][C]-165.566275684191[/C][C]8460.99481106305[/C][C]221.231464621145[/C][/ROW]
[ROW][C]93[/C][C]8553.44[/C][C]8812.66694802568[/C][C]-53.8326025924161[/C][C]8348.04565456674[/C][C]259.226948025675[/C][/ROW]
[ROW][C]94[/C][C]7555.2[/C][C]6946.3414598409[/C][C]-33.8451719361991[/C][C]8197.9037120953[/C][C]-608.858540159095[/C][/ROW]
[ROW][C]95[/C][C]7851.22[/C][C]7634.28278347287[/C][C]20.3954469032896[/C][C]8047.76176962385[/C][C]-216.937216527135[/C][/ROW]
[ROW][C]96[/C][C]7442[/C][C]7042.27754202814[/C][C]12.6554468129424[/C][C]7829.06701115892[/C][C]-399.722457971861[/C][/ROW]
[ROW][C]97[/C][C]7992.53[/C][C]8319.2588821282[/C][C]55.4288651778108[/C][C]7610.372252694[/C][C]326.728882128196[/C][/ROW]
[ROW][C]98[/C][C]8264.04[/C][C]9075.98855241598[/C][C]125.204254565742[/C][C]7326.88719301828[/C][C]811.948552415976[/C][/ROW]
[ROW][C]99[/C][C]7517.39[/C][C]7901.28672808086[/C][C]90.091138576565[/C][C]7043.40213334257[/C][C]383.896728080863[/C][/ROW]
[ROW][C]100[/C][C]7200.4[/C][C]7646.97358391077[/C][C]53.8260939005422[/C][C]6700.00032218869[/C][C]446.573583910772[/C][/ROW]
[ROW][C]101[/C][C]7193.69[/C][C]7970.4960140019[/C][C]60.285474963302[/C][C]6356.5985110348[/C][C]776.8060140019[/C][/ROW]
[ROW][C]102[/C][C]6193.58[/C][C]6365.03708373216[/C][C]1.37605228989992[/C][C]6020.74686397794[/C][C]171.457083732164[/C][/ROW]
[ROW][C]103[/C][C]5104.21[/C][C]4689.5436815331[/C][C]-166.01889845417[/C][C]5684.89521692107[/C][C]-414.666318466902[/C][/ROW]
[ROW][C]104[/C][C]4800.46[/C][C]4428.98922579075[/C][C]-165.566275684191[/C][C]5337.49704989344[/C][C]-371.470774209246[/C][/ROW]
[ROW][C]105[/C][C]4461.61[/C][C]3986.95371972661[/C][C]-53.8326025924161[/C][C]4990.0988828658[/C][C]-474.656280273386[/C][/ROW]
[ROW][C]106[/C][C]4398.59[/C][C]4199.34538734006[/C][C]-33.8451719361991[/C][C]4631.67978459614[/C][C]-199.24461265994[/C][/ROW]
[ROW][C]107[/C][C]4243.63[/C][C]4193.60386677023[/C][C]20.3954469032896[/C][C]4273.26068632648[/C][C]-50.0261332297659[/C][/ROW]
[ROW][C]108[/C][C]4293.82[/C][C]4664.77505176349[/C][C]12.6554468129424[/C][C]3910.20950142356[/C][C]370.955051763493[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62994&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62994&T=2

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


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

Seasonal Decomposition by Loess - Time Series Components
tObservedFittedSeasonalTrendRemainder
14716.994338.4205784131455.42886517781085040.13055640905-378.569421586862
24926.654713.49299084938125.2042545657425014.60275458488-213.157009150625
34920.14761.0339086627290.0911385765654989.07495276072-159.066091337280
45170.095329.2865313482753.82609390054224957.06737475119159.196531348271
55246.245507.1347282950460.2854749633024925.05979674166260.894728295041
65283.615675.575623594941.376052289899924890.26832411516391.965623594941
74979.055268.64204696551-166.018898454174855.47685148866289.59204696551
84825.24995.98984245107-165.5662756841914819.97643323312170.789842451069
94695.124659.59658761483-53.83260259241614784.47601497758-35.5234123851687
104711.544738.37007576279-33.84517193619914718.5550961734126.8300757627912
114727.224781.4103757274820.39544690328964652.6341773692354.1903757274804
124384.964198.3625938693112.65544681294244558.90195931774-186.597406130687
134378.754236.9013935559355.42886517781084465.16974126626-141.848606444069
144472.934439.18323198675125.2042545657424381.47251344751-33.7467680132495
154564.074740.2735757946890.0911385765654297.77528562876176.203575794676
164310.544324.7479450795553.82609390054224242.5059610199114.2079450795454
174171.384095.2378886256360.2854749633024187.23663641107-76.1421113743672
184049.383944.744450429161.376052289899924152.63949728094-104.635549570839
193591.373230.71654030336-166.018898454174118.04235815081-360.653459696643
203720.463525.28946838467-165.5662756841914081.19680729952-195.170531615332
214107.234223.94134614418-53.83260259241614044.35125644823116.711346144183
224101.714248.67005716257-33.84517193619913988.59511477363146.960057162572
234162.344371.4455799976920.39544690328963932.83897309902209.105579997688
244136.224400.5222567763812.65544681294243859.26229641067264.302256776384
254125.884410.6455150998655.42886517781083785.68561972233284.765515099863
264031.484238.97659647825125.2042545657423698.77914895601207.496596478247
273761.363820.7561832337490.0911385765653611.872678189759.3961832337382
283408.563249.4505365799853.82609390054223513.84336951948-159.109463420021
293228.472980.8404641874460.2854749633023415.81406084926-247.629535812563
303090.452855.091835395691.376052289899923324.43211231441-235.358164604309
312741.142415.24873467461-166.018898454173233.05016377956-325.891265325388
322980.442945.535761135-165.5662756841913180.91051454919-34.9042388650009
333104.333133.72173727359-53.83260259241613128.7708653188329.3917372735891
343181.573260.21780175005-33.84517193619913136.7673701861578.6478017500535
352863.862562.5606780432520.39544690328963144.76387505346-301.299321956754
362898.012583.1582042697612.65544681294243200.20634891729-314.851795730237
373112.332913.5823120410755.42886517781083255.64882278112-198.747687958934
383254.333046.86195523638125.2042545657423336.59379019788-207.46804476362
393513.473519.310103808890.0911385765653417.538757614635.84010380880181
403587.613603.5421190150953.82609390054223517.8517870843715.9321190150881
413727.453776.4497084825960.2854749633023618.1648165541148.9997084825918
423793.343860.111973335551.376052289899923725.1919743745566.7719733355507
433817.583968.95976625918-166.018898454173832.21913219499151.379766259177
443845.133937.16721505402-165.5662756841913918.6590606301792.0372150540247
453931.863912.45361352708-53.83260259241614005.09898906534-19.4063864729246
464197.524360.70853490986-33.84517193619914068.17663702634163.188534909864
474307.134462.6102681093820.39544690328964131.25428498733155.480268109380
484229.434254.4762412544212.65544681294244191.7283119326425.0462412544202
494362.284416.9287959442455.42886517781084252.2023388779454.6487959442447
504217.343980.54554489313125.2042545657424328.93020054113-236.794455106868
514361.284226.8107992191390.0911385765654405.65806220431-134.469200780874
524327.744098.4796758700853.82609390054224503.17423022938-229.260324129918
534417.654174.3241267822660.2854749633024600.69039825444-243.325873217742
544557.684400.747948503881.376052289899924713.23599920622-156.932051496117
554650.354640.93729829617-166.018898454174825.781600158-9.4127017038254
564967.185148.32611854529-165.5662756841914951.6001571389181.146118545291
575123.425223.25388847261-53.83260259241615077.4187141198099.8338884726118
585290.855401.43454954525-33.84517193619915214.11062239095110.584549545245
595535.665700.122022434620.39544690328965350.80253066210164.462022434605
605514.065522.5747863290912.65544681294245492.889766857978.5147863290913
615493.885297.3541317683655.42886517781085634.97700305383-196.52586823164
625694.835482.9956371608125.2042545657425781.46010827346-211.834362839200
635850.415682.7856479303590.0911385765655927.94321349309-167.624352069654
646116.646090.5816755752553.82609390054226088.87223052421-26.0583244247518
6561756039.9132774813760.2854749633026249.80124755533-135.086722518632
666513.586607.768033081351.376052289899926418.0159146287594.1880330813465
676383.786347.348316752-166.018898454176586.23058170218-36.4316832480063
686673.666782.66155087675-165.5662756841916730.22472480744109.001550876751
696936.617052.83373467971-53.83260259241616874.2188679127116.223734679712
707300.687656.92867258841-33.84517193619916978.27649934779356.248672588407
717392.937683.1304223138320.39544690328967082.33413078288290.200422313831
727497.317816.1271779252312.65544681294247165.83737526183318.81717792523
737584.717864.6505150814155.42886517781087249.34061974078279.940515081414
747160.796864.25997175526125.2042545657427332.115773679-296.530028244738
757196.196887.3979338062290.0911385765657414.89092761722-308.792066193782
767245.636933.3153636139153.82609390054227504.11854248554-312.314636386085
777347.517041.3883676828360.2854749633027593.34615735387-306.12163231717
787425.757143.957294271981.376052289899927706.16665343812-281.792705728024
797778.517904.0517489318-166.018898454177818.98714952238125.541748931792
807822.337844.79889990724-165.5662756841917965.4273757769522.4688999072423
818181.228304.4050005609-53.83260259241618111.86760203152123.185000560897
828371.478517.06250446234-33.84517193619918259.72266747386145.592504462338
838347.718267.4468201805120.39544690328968407.5777329162-80.2631798194907
848672.118807.2563678033412.65544681294248524.30818538372135.146367803338
858802.798909.1124969709555.42886517781088641.03863785124106.322496970946
869138.469449.24260553694125.2042545657428702.47313989732310.782605536941
879123.299392.5812194800590.0911385765658763.9076419434269.291219480045
889023.219244.8207279457553.82609390054228747.77317815371221.610727945746
898850.418908.8958106726760.2854749633028731.6387143640358.4858106726679
908864.589074.992606748411.376052289899928652.79134096169210.412606748410
919163.749919.55493089482-166.018898454178573.94396755935755.814930894818
928516.668737.89146462115-165.5662756841918460.99481106305221.231464621145
938553.448812.66694802568-53.83260259241618348.04565456674259.226948025675
947555.26946.3414598409-33.84517193619918197.9037120953-608.858540159095
957851.227634.2827834728720.39544690328968047.76176962385-216.937216527135
9674427042.2775420281412.65544681294247829.06701115892-399.722457971861
977992.538319.258882128255.42886517781087610.372252694326.728882128196
988264.049075.98855241598125.2042545657427326.88719301828811.948552415976
997517.397901.2867280808690.0911385765657043.40213334257383.896728080863
1007200.47646.9735839107753.82609390054226700.00032218869446.573583910772
1017193.697970.496014001960.2854749633026356.5985110348776.8060140019
1026193.586365.037083732161.376052289899926020.74686397794171.457083732164
1035104.214689.5436815331-166.018898454175684.89521692107-414.666318466902
1044800.464428.98922579075-165.5662756841915337.49704989344-371.470774209246
1054461.613986.95371972661-53.83260259241614990.0988828658-474.656280273386
1064398.594199.34538734006-33.84517193619914631.67978459614-199.24461265994
1074243.634193.6038667702320.39544690328964273.26068632648-50.0261332297659
1084293.824664.7750517634912.65544681294243910.20950142356370.955051763493


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 0.2 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = 2 ; par7 = 0 ; par8 = 0 ; par9 = 0 ;
Parameters (R input):
par1 = 12 ; par2 = periodic ; par3 = 0 ; par4 = ; par5 = 1 ; par6 = ; par7 = 1 ; par8 = FALSE ;
R code (references can be found in the software module):
par1 <- as.numeric(par1) #seasonal period
if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
par3 <- as.numeric(par3) #s.degree
if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
par5 <- as.numeric(par5)#t.degree
if (par6 != '') par6 <- as.numeric(par6)#l.window
par7 <- as.numeric(par7)#l.degree
if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
nx <- length(x)
x <- ts(x,frequency=par1)
if (par6 != '') {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
} else {
m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
}
m$time.series
m$win
m$deg
m$jump
m$inner
m$outer
bitmap(file='test1.png')
plot(m,main=main)
dev.off()
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Component',header=TRUE)
a<-table.element(a,'Window',header=TRUE)
a<-table.element(a,'Degree',header=TRUE)
a<-table.element(a,'Jump',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,m$win['s'])
a<-table.element(a,m$deg['s'])
a<-table.element(a,m$jump['s'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,m$win['t'])
a<-table.element(a,m$deg['t'])
a<-table.element(a,m$jump['t'])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Low-pass',header=TRUE)
a<-table.element(a,m$win['l'])
a<-table.element(a,m$deg['l'])
a<-table.element(a,m$jump['l'])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Fitted',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Remainder',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,x[i]+m$time.series[i,'remainder'])
a<-table.element(a,m$time.series[i,'seasonal'])
a<-table.element(a,m$time.series[i,'trend'])
a<-table.element(a,m$time.series[i,'remainder'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')