Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationSun, 06 Jun 2010 16:48:19 +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/Jun/06/t12758429713lakcwzm7531rgn.htm/, Retrieved Sun, 28 Apr 2024 07:18:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77750, Retrieved Sun, 28 Apr 2024 07:18:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W62
Estimated Impact200
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [Nieuwe personenwa...] [2009-01-13 17:37:29] [74be16979710d4c4e7c6647856088456]
-       [Classical Decomposition] [roger dirkx oefen...] [2009-01-14 16:39:03] [74be16979710d4c4e7c6647856088456]
- RMP     [Exponential Smoothing] [roger dirkx oef 10] [2009-01-24 20:53:30] [74be16979710d4c4e7c6647856088456]
-           [Exponential Smoothing] [Dennis Collin oef 10] [2009-01-25 12:25:31] [2097edf1f094fab6879a8cb46df74ec2]
-             [Exponential Smoothing] [Dennis Collin oef 2] [2009-01-25 12:34:26] [2097edf1f094fab6879a8cb46df74ec2]
-               [Exponential Smoothing] [Dennis Collin oef 10] [2009-01-25 12:39:06] [2097edf1f094fab6879a8cb46df74ec2]
- RM D            [Exponential Smoothing] [exponential smoot...] [2010-01-19 11:49:31] [74be16979710d4c4e7c6647856088456]
-   PD                [Exponential Smoothing] [OPGAVE 10 oef 2 s...] [2010-06-06 16:48:19] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message
Dataseries X:
1954
2302
3054
2414
2226
2725
2589
3470
2400
3180
4009
3924
2072
2434
2956
2828
2687
2629
3150
4119
3030
3055
3821
4001
2529
2472
3134
2789
2758
2993
3282
3437
2804
3076
3782
3889
2271
2452
3084
2522
2769
3438
2839
3746
2632
2851
3871
3618
2389
2344
2678
2492
2858
2246
2800
3869
3007
3023
3907
4209
2353
2570
2903
2910
3782
2759
2931
3641
2794
3070
3576
4106
2452
2206
2488
2416
2534
2521
3093
3903
2907
3025
3812
4209
2138
2419
2622
2912
2708
2798
3254
2895
3263
3736
4077
4097
2175
3138
2823
2498
2822
2738
4137
3515
3785
3632
4504
4451
2550
2867
3458
2961
3163
2880
3331
3062
3534
3622
4464
5411
2564
2820
3508
3088
3299
2939
3320
3418
3604
3495
4163
4882
2211
3260
2992
2425
2707
3244
3965
3315
3333
3583
4021
4904
2252
2952
3573
3048
3059
2731
3563
3092
3478
3478
4308
5029
2075
3264
3308
3688
3136
2824
3644
4694
2914
3686
4358
5587
2265
3685
3754
3708
3210
3517
3905
3670
4221
4404
5086
5725
2367
3819
4067
4022
3937
4365
4290




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=77750&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=77750&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77750&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.122923936061106
beta0.0628781616526975
gamma0.35503071893546

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.122923936061106 \tabularnewline
beta & 0.0628781616526975 \tabularnewline
gamma & 0.35503071893546 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77750&T=1

[TABLE]
[ROW][C]Estimated Parameters of Exponential Smoothing[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]alpha[/C][C]0.122923936061106[/C][/ROW]
[ROW][C]beta[/C][C]0.0628781616526975[/C][/ROW]
[ROW][C]gamma[/C][C]0.35503071893546[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77750&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77750&T=1

As an alternative you can also use a QR Code:  

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

Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.122923936061106
beta0.0628781616526975
gamma0.35503071893546







Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
1320721985.8426816239386.1573183760677
1424342331.83381956774102.166180432265
1529562837.70749586882118.292504131177
1628282728.7277934576899.2722065423186
1726872639.2606723636247.7393276363823
1826292618.4112485881510.5887514118508
1931502809.57697266319340.423027336813
2041193751.37676577387367.623234226128
2130302757.36156032045272.638439679548
2230553592.02773556861-537.027735568609
2338214348.72407950558-527.72407950558
2440014209.7351640861-208.735164086099
2525292364.00602923632164.993970763677
2624722726.60730668541-254.607306685407
2731343192.82320107236-58.8232010723636
2827893053.95672088088-264.956720880879
2927582898.6628602674-140.6628602674
3029932836.62229787113156.377702128866
3132823143.07883611707138.921163882932
3234374061.68473144673-624.684731446733
3328042901.54979309679-97.5497930967904
3430763421.16448977267-345.164489772670
3537824188.40004272526-406.400042725262
3638894148.64968698426-259.649686984263
3722712397.63883920792-126.638839207915
3824522576.07994645867-124.079946458666
3930843102.66234208457-18.6623420845667
4025222888.21186409838-366.211864098378
4127692742.0594032403926.9405967596081
4234382777.29625715575660.703742844251
4328393128.38860904603-289.388609046026
4437463741.333886149644.6661138503614
4526322812.33696108994-180.336961089944
4628513233.66251037908-382.662510379085
4738713965.92261036955-94.9226103695464
4836184001.26623179294-383.26623179294
4923892266.63210520868122.367894791320
5023442468.55758762906-124.557587629064
5126783019.9821309966-341.982130996601
5224922647.14080399939-155.140803999393
5328582640.56474709947217.43525290053
5422462889.24455719202-643.244557192023
5528002766.8034436802333.196556319765
5638693496.06213210009372.937867899915
5730072542.66774864412464.332251355881
5830232973.1604733593449.8395266406642
5939073844.4511961780162.5488038219873
6042093806.84868640701402.151313592991
6123532329.7646061805423.2353938194615
6225702445.40280050067124.597199499333
6329032964.46494134045-61.4649413404509
6429102691.16850706248218.831492937523
6537822856.35147252505925.648527474953
6627592939.32822162209-180.328221622091
6729313103.25163278733-172.251632787325
6836413930.28429496249-289.284294962492
6927942936.06447428926-142.064474289257
7030703170.3794106414-100.379410641397
7135764033.43241840469-457.432418404686
7241064039.9114420606366.0885579393744
7324522403.1806742485548.8193257514458
7422062553.37813390341-347.378133903406
7524882952.68895069317-464.688950693167
7624162710.19466911439-294.194669114394
7725343021.53097666638-487.530976666377
7825212564.60394020959-43.6039402095853
7930932727.10450740374365.895492596256
8039033567.26062737423335.739372625771
8129072683.95972539023223.040274609765
8230252967.2029461697157.7970538302902
8338123730.8077540043281.1922459956754
8442093962.96892683598246.031073164016
8521382340.82441112322-202.824411123217
8624192332.6167682298386.3832317701654
8726222747.97003496763-125.970034967634
8829122602.07257418404309.927425815963
8927082934.00668175509-226.006681755093
9027982656.02211769573141.977882304272
9132542978.844039266275.155960734003
9228953807.74977932082-912.74977932082
9332632735.53052504221527.469474957786
9437363006.73757444092729.262425559083
9540773867.35356930211209.646430697892
9640974174.81369316516-77.8136931651561
9721752378.76906557102-203.769065571024
9831382466.17086096644671.829139033559
9928232897.55952585991-74.55952585991
10024982904.30720429103-406.307204291029
10128222986.37093875851-164.370938758506
10227382836.08156851991-98.08156851991
10341373174.54150425071962.458495749285
10435153727.02166685362-212.021666853620
10537853203.81232021901581.187679780989
10636323559.2792123314572.7207876685475
10745044187.13378152134316.866218478655
10844514428.8365387602722.1634612397338
10925502617.20779232954-67.2077923295383
11028673006.45075866478-139.450758664777
11134583111.82887619607346.171123803929
11229613076.37613699992-115.376136999919
11331633281.17149012045-118.171490120448
11428803169.19294939455-289.192949394546
11533313824.91406458938-493.914064589375
11630623831.90729050255-769.907290502546
11735343482.0612924445851.9387075554214
11836223604.9933839948617.0066160051406
11944644292.44644409626171.553555903743
12054114413.81936884119997.180631158812
12125642691.05023608226-127.050236082257
12228203046.81482232811-226.814822328106
12335083288.36918390758219.630816092424
12430883088.36093058357-0.360930583570735
12532993302.03297606169-3.03297606168780
12629393147.45246753272-208.452467532723
12733203746.47363493709-426.473634937086
12834183673.45993355708-255.459933557082
12936043644.38614000392-40.3861400039191
13034953745.99878241764-250.998782417642
13141634447.4672487195-284.467248719498
13248824765.1862314213116.813768578697
13322112572.63210130036-361.632101300363
13432602855.18846143743404.81153856257
13529923304.97813353914-312.978133539136
13624252958.45491158245-533.454911582449
13727073089.10291247523-382.102912475235
13832442804.36836860031439.631631399694
13939653400.58248683110564.417513168898
14033153495.70091234209-180.700912342089
14133333536.44233408617-203.442334086170
14235833544.8226600405838.1773399594249
14340214266.04483352958-245.044833529581
14449044708.4977029165195.502297083496
14522522372.17517874422-120.175178744218
14629522920.4823846076731.5176153923312
14735733095.39618782337477.603812176634
14830482778.03362813544269.966371864562
14930593061.41375285475-2.41375285474896
15027313089.00893130404-358.008931304042
15135633629.64351109778-66.6435110977814
15230923413.90280922877-321.902809228772
15334783427.8493470361450.1506529638605
15434783542.2437317922-64.2437317922008
15543084161.49572906673146.504270933275
15650294791.09931454002237.900685459981
15720752363.85625030521-288.856250305212
15832642939.52635862239324.473641377605
15933083292.4844894124515.5155105875529
16036882853.21933533991834.780664660094
16131363125.1331985090210.8668014909777
16228243047.65581804721-223.655818047206
16336443700.59537930672-56.5953793067156
16446943411.744370992811282.25562900719
16529143756.2720860273-842.272086027302
16636863735.98583927871-49.985839278705
16743584433.36590475871-75.3659047587116
16855875073.19211581412513.807884185875
16922652527.00686188418-262.006861884177
17036853308.33757430996376.662425690035
17137543583.28421186176170.715788138243
17237083431.18598058334276.814019416664
17332103386.62104665384-176.62104665384
17435173220.28636201448296.713637985523
17539054000.45180595504-95.451805955035
17636704134.66673322833-464.666733228330
17742213600.33798063106620.662019368937
17844044015.3344371608388.665562839199
17950864770.86653169258315.133468307419
18057255657.3092714746967.690728525311
18123672826.40986638851-459.409866388513
18238193792.5282683476826.4717316523179
18340673967.7705641301399.2294358698682
18440223846.84221389780175.157786102205
18539373654.72035250663282.279647493373
18643653701.86740927603663.132590723971
18742904417.47133932666-127.471339326661

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
13 & 2072 & 1985.84268162393 & 86.1573183760677 \tabularnewline
14 & 2434 & 2331.83381956774 & 102.166180432265 \tabularnewline
15 & 2956 & 2837.70749586882 & 118.292504131177 \tabularnewline
16 & 2828 & 2728.72779345768 & 99.2722065423186 \tabularnewline
17 & 2687 & 2639.26067236362 & 47.7393276363823 \tabularnewline
18 & 2629 & 2618.41124858815 & 10.5887514118508 \tabularnewline
19 & 3150 & 2809.57697266319 & 340.423027336813 \tabularnewline
20 & 4119 & 3751.37676577387 & 367.623234226128 \tabularnewline
21 & 3030 & 2757.36156032045 & 272.638439679548 \tabularnewline
22 & 3055 & 3592.02773556861 & -537.027735568609 \tabularnewline
23 & 3821 & 4348.72407950558 & -527.72407950558 \tabularnewline
24 & 4001 & 4209.7351640861 & -208.735164086099 \tabularnewline
25 & 2529 & 2364.00602923632 & 164.993970763677 \tabularnewline
26 & 2472 & 2726.60730668541 & -254.607306685407 \tabularnewline
27 & 3134 & 3192.82320107236 & -58.8232010723636 \tabularnewline
28 & 2789 & 3053.95672088088 & -264.956720880879 \tabularnewline
29 & 2758 & 2898.6628602674 & -140.6628602674 \tabularnewline
30 & 2993 & 2836.62229787113 & 156.377702128866 \tabularnewline
31 & 3282 & 3143.07883611707 & 138.921163882932 \tabularnewline
32 & 3437 & 4061.68473144673 & -624.684731446733 \tabularnewline
33 & 2804 & 2901.54979309679 & -97.5497930967904 \tabularnewline
34 & 3076 & 3421.16448977267 & -345.164489772670 \tabularnewline
35 & 3782 & 4188.40004272526 & -406.400042725262 \tabularnewline
36 & 3889 & 4148.64968698426 & -259.649686984263 \tabularnewline
37 & 2271 & 2397.63883920792 & -126.638839207915 \tabularnewline
38 & 2452 & 2576.07994645867 & -124.079946458666 \tabularnewline
39 & 3084 & 3102.66234208457 & -18.6623420845667 \tabularnewline
40 & 2522 & 2888.21186409838 & -366.211864098378 \tabularnewline
41 & 2769 & 2742.05940324039 & 26.9405967596081 \tabularnewline
42 & 3438 & 2777.29625715575 & 660.703742844251 \tabularnewline
43 & 2839 & 3128.38860904603 & -289.388609046026 \tabularnewline
44 & 3746 & 3741.33388614964 & 4.6661138503614 \tabularnewline
45 & 2632 & 2812.33696108994 & -180.336961089944 \tabularnewline
46 & 2851 & 3233.66251037908 & -382.662510379085 \tabularnewline
47 & 3871 & 3965.92261036955 & -94.9226103695464 \tabularnewline
48 & 3618 & 4001.26623179294 & -383.26623179294 \tabularnewline
49 & 2389 & 2266.63210520868 & 122.367894791320 \tabularnewline
50 & 2344 & 2468.55758762906 & -124.557587629064 \tabularnewline
51 & 2678 & 3019.9821309966 & -341.982130996601 \tabularnewline
52 & 2492 & 2647.14080399939 & -155.140803999393 \tabularnewline
53 & 2858 & 2640.56474709947 & 217.43525290053 \tabularnewline
54 & 2246 & 2889.24455719202 & -643.244557192023 \tabularnewline
55 & 2800 & 2766.80344368023 & 33.196556319765 \tabularnewline
56 & 3869 & 3496.06213210009 & 372.937867899915 \tabularnewline
57 & 3007 & 2542.66774864412 & 464.332251355881 \tabularnewline
58 & 3023 & 2973.16047335934 & 49.8395266406642 \tabularnewline
59 & 3907 & 3844.45119617801 & 62.5488038219873 \tabularnewline
60 & 4209 & 3806.84868640701 & 402.151313592991 \tabularnewline
61 & 2353 & 2329.76460618054 & 23.2353938194615 \tabularnewline
62 & 2570 & 2445.40280050067 & 124.597199499333 \tabularnewline
63 & 2903 & 2964.46494134045 & -61.4649413404509 \tabularnewline
64 & 2910 & 2691.16850706248 & 218.831492937523 \tabularnewline
65 & 3782 & 2856.35147252505 & 925.648527474953 \tabularnewline
66 & 2759 & 2939.32822162209 & -180.328221622091 \tabularnewline
67 & 2931 & 3103.25163278733 & -172.251632787325 \tabularnewline
68 & 3641 & 3930.28429496249 & -289.284294962492 \tabularnewline
69 & 2794 & 2936.06447428926 & -142.064474289257 \tabularnewline
70 & 3070 & 3170.3794106414 & -100.379410641397 \tabularnewline
71 & 3576 & 4033.43241840469 & -457.432418404686 \tabularnewline
72 & 4106 & 4039.91144206063 & 66.0885579393744 \tabularnewline
73 & 2452 & 2403.18067424855 & 48.8193257514458 \tabularnewline
74 & 2206 & 2553.37813390341 & -347.378133903406 \tabularnewline
75 & 2488 & 2952.68895069317 & -464.688950693167 \tabularnewline
76 & 2416 & 2710.19466911439 & -294.194669114394 \tabularnewline
77 & 2534 & 3021.53097666638 & -487.530976666377 \tabularnewline
78 & 2521 & 2564.60394020959 & -43.6039402095853 \tabularnewline
79 & 3093 & 2727.10450740374 & 365.895492596256 \tabularnewline
80 & 3903 & 3567.26062737423 & 335.739372625771 \tabularnewline
81 & 2907 & 2683.95972539023 & 223.040274609765 \tabularnewline
82 & 3025 & 2967.20294616971 & 57.7970538302902 \tabularnewline
83 & 3812 & 3730.80775400432 & 81.1922459956754 \tabularnewline
84 & 4209 & 3962.96892683598 & 246.031073164016 \tabularnewline
85 & 2138 & 2340.82441112322 & -202.824411123217 \tabularnewline
86 & 2419 & 2332.61676822983 & 86.3832317701654 \tabularnewline
87 & 2622 & 2747.97003496763 & -125.970034967634 \tabularnewline
88 & 2912 & 2602.07257418404 & 309.927425815963 \tabularnewline
89 & 2708 & 2934.00668175509 & -226.006681755093 \tabularnewline
90 & 2798 & 2656.02211769573 & 141.977882304272 \tabularnewline
91 & 3254 & 2978.844039266 & 275.155960734003 \tabularnewline
92 & 2895 & 3807.74977932082 & -912.74977932082 \tabularnewline
93 & 3263 & 2735.53052504221 & 527.469474957786 \tabularnewline
94 & 3736 & 3006.73757444092 & 729.262425559083 \tabularnewline
95 & 4077 & 3867.35356930211 & 209.646430697892 \tabularnewline
96 & 4097 & 4174.81369316516 & -77.8136931651561 \tabularnewline
97 & 2175 & 2378.76906557102 & -203.769065571024 \tabularnewline
98 & 3138 & 2466.17086096644 & 671.829139033559 \tabularnewline
99 & 2823 & 2897.55952585991 & -74.55952585991 \tabularnewline
100 & 2498 & 2904.30720429103 & -406.307204291029 \tabularnewline
101 & 2822 & 2986.37093875851 & -164.370938758506 \tabularnewline
102 & 2738 & 2836.08156851991 & -98.08156851991 \tabularnewline
103 & 4137 & 3174.54150425071 & 962.458495749285 \tabularnewline
104 & 3515 & 3727.02166685362 & -212.021666853620 \tabularnewline
105 & 3785 & 3203.81232021901 & 581.187679780989 \tabularnewline
106 & 3632 & 3559.27921233145 & 72.7207876685475 \tabularnewline
107 & 4504 & 4187.13378152134 & 316.866218478655 \tabularnewline
108 & 4451 & 4428.83653876027 & 22.1634612397338 \tabularnewline
109 & 2550 & 2617.20779232954 & -67.2077923295383 \tabularnewline
110 & 2867 & 3006.45075866478 & -139.450758664777 \tabularnewline
111 & 3458 & 3111.82887619607 & 346.171123803929 \tabularnewline
112 & 2961 & 3076.37613699992 & -115.376136999919 \tabularnewline
113 & 3163 & 3281.17149012045 & -118.171490120448 \tabularnewline
114 & 2880 & 3169.19294939455 & -289.192949394546 \tabularnewline
115 & 3331 & 3824.91406458938 & -493.914064589375 \tabularnewline
116 & 3062 & 3831.90729050255 & -769.907290502546 \tabularnewline
117 & 3534 & 3482.06129244458 & 51.9387075554214 \tabularnewline
118 & 3622 & 3604.99338399486 & 17.0066160051406 \tabularnewline
119 & 4464 & 4292.44644409626 & 171.553555903743 \tabularnewline
120 & 5411 & 4413.81936884119 & 997.180631158812 \tabularnewline
121 & 2564 & 2691.05023608226 & -127.050236082257 \tabularnewline
122 & 2820 & 3046.81482232811 & -226.814822328106 \tabularnewline
123 & 3508 & 3288.36918390758 & 219.630816092424 \tabularnewline
124 & 3088 & 3088.36093058357 & -0.360930583570735 \tabularnewline
125 & 3299 & 3302.03297606169 & -3.03297606168780 \tabularnewline
126 & 2939 & 3147.45246753272 & -208.452467532723 \tabularnewline
127 & 3320 & 3746.47363493709 & -426.473634937086 \tabularnewline
128 & 3418 & 3673.45993355708 & -255.459933557082 \tabularnewline
129 & 3604 & 3644.38614000392 & -40.3861400039191 \tabularnewline
130 & 3495 & 3745.99878241764 & -250.998782417642 \tabularnewline
131 & 4163 & 4447.4672487195 & -284.467248719498 \tabularnewline
132 & 4882 & 4765.1862314213 & 116.813768578697 \tabularnewline
133 & 2211 & 2572.63210130036 & -361.632101300363 \tabularnewline
134 & 3260 & 2855.18846143743 & 404.81153856257 \tabularnewline
135 & 2992 & 3304.97813353914 & -312.978133539136 \tabularnewline
136 & 2425 & 2958.45491158245 & -533.454911582449 \tabularnewline
137 & 2707 & 3089.10291247523 & -382.102912475235 \tabularnewline
138 & 3244 & 2804.36836860031 & 439.631631399694 \tabularnewline
139 & 3965 & 3400.58248683110 & 564.417513168898 \tabularnewline
140 & 3315 & 3495.70091234209 & -180.700912342089 \tabularnewline
141 & 3333 & 3536.44233408617 & -203.442334086170 \tabularnewline
142 & 3583 & 3544.82266004058 & 38.1773399594249 \tabularnewline
143 & 4021 & 4266.04483352958 & -245.044833529581 \tabularnewline
144 & 4904 & 4708.4977029165 & 195.502297083496 \tabularnewline
145 & 2252 & 2372.17517874422 & -120.175178744218 \tabularnewline
146 & 2952 & 2920.48238460767 & 31.5176153923312 \tabularnewline
147 & 3573 & 3095.39618782337 & 477.603812176634 \tabularnewline
148 & 3048 & 2778.03362813544 & 269.966371864562 \tabularnewline
149 & 3059 & 3061.41375285475 & -2.41375285474896 \tabularnewline
150 & 2731 & 3089.00893130404 & -358.008931304042 \tabularnewline
151 & 3563 & 3629.64351109778 & -66.6435110977814 \tabularnewline
152 & 3092 & 3413.90280922877 & -321.902809228772 \tabularnewline
153 & 3478 & 3427.84934703614 & 50.1506529638605 \tabularnewline
154 & 3478 & 3542.2437317922 & -64.2437317922008 \tabularnewline
155 & 4308 & 4161.49572906673 & 146.504270933275 \tabularnewline
156 & 5029 & 4791.09931454002 & 237.900685459981 \tabularnewline
157 & 2075 & 2363.85625030521 & -288.856250305212 \tabularnewline
158 & 3264 & 2939.52635862239 & 324.473641377605 \tabularnewline
159 & 3308 & 3292.48448941245 & 15.5155105875529 \tabularnewline
160 & 3688 & 2853.21933533991 & 834.780664660094 \tabularnewline
161 & 3136 & 3125.13319850902 & 10.8668014909777 \tabularnewline
162 & 2824 & 3047.65581804721 & -223.655818047206 \tabularnewline
163 & 3644 & 3700.59537930672 & -56.5953793067156 \tabularnewline
164 & 4694 & 3411.74437099281 & 1282.25562900719 \tabularnewline
165 & 2914 & 3756.2720860273 & -842.272086027302 \tabularnewline
166 & 3686 & 3735.98583927871 & -49.985839278705 \tabularnewline
167 & 4358 & 4433.36590475871 & -75.3659047587116 \tabularnewline
168 & 5587 & 5073.19211581412 & 513.807884185875 \tabularnewline
169 & 2265 & 2527.00686188418 & -262.006861884177 \tabularnewline
170 & 3685 & 3308.33757430996 & 376.662425690035 \tabularnewline
171 & 3754 & 3583.28421186176 & 170.715788138243 \tabularnewline
172 & 3708 & 3431.18598058334 & 276.814019416664 \tabularnewline
173 & 3210 & 3386.62104665384 & -176.62104665384 \tabularnewline
174 & 3517 & 3220.28636201448 & 296.713637985523 \tabularnewline
175 & 3905 & 4000.45180595504 & -95.451805955035 \tabularnewline
176 & 3670 & 4134.66673322833 & -464.666733228330 \tabularnewline
177 & 4221 & 3600.33798063106 & 620.662019368937 \tabularnewline
178 & 4404 & 4015.3344371608 & 388.665562839199 \tabularnewline
179 & 5086 & 4770.86653169258 & 315.133468307419 \tabularnewline
180 & 5725 & 5657.30927147469 & 67.690728525311 \tabularnewline
181 & 2367 & 2826.40986638851 & -459.409866388513 \tabularnewline
182 & 3819 & 3792.52826834768 & 26.4717316523179 \tabularnewline
183 & 4067 & 3967.77056413013 & 99.2294358698682 \tabularnewline
184 & 4022 & 3846.84221389780 & 175.157786102205 \tabularnewline
185 & 3937 & 3654.72035250663 & 282.279647493373 \tabularnewline
186 & 4365 & 3701.86740927603 & 663.132590723971 \tabularnewline
187 & 4290 & 4417.47133932666 & -127.471339326661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77750&T=2

[TABLE]
[ROW][C]Interpolation Forecasts of Exponential Smoothing[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Fitted[/C][C]Residuals[/C][/ROW]
[ROW][C]13[/C][C]2072[/C][C]1985.84268162393[/C][C]86.1573183760677[/C][/ROW]
[ROW][C]14[/C][C]2434[/C][C]2331.83381956774[/C][C]102.166180432265[/C][/ROW]
[ROW][C]15[/C][C]2956[/C][C]2837.70749586882[/C][C]118.292504131177[/C][/ROW]
[ROW][C]16[/C][C]2828[/C][C]2728.72779345768[/C][C]99.2722065423186[/C][/ROW]
[ROW][C]17[/C][C]2687[/C][C]2639.26067236362[/C][C]47.7393276363823[/C][/ROW]
[ROW][C]18[/C][C]2629[/C][C]2618.41124858815[/C][C]10.5887514118508[/C][/ROW]
[ROW][C]19[/C][C]3150[/C][C]2809.57697266319[/C][C]340.423027336813[/C][/ROW]
[ROW][C]20[/C][C]4119[/C][C]3751.37676577387[/C][C]367.623234226128[/C][/ROW]
[ROW][C]21[/C][C]3030[/C][C]2757.36156032045[/C][C]272.638439679548[/C][/ROW]
[ROW][C]22[/C][C]3055[/C][C]3592.02773556861[/C][C]-537.027735568609[/C][/ROW]
[ROW][C]23[/C][C]3821[/C][C]4348.72407950558[/C][C]-527.72407950558[/C][/ROW]
[ROW][C]24[/C][C]4001[/C][C]4209.7351640861[/C][C]-208.735164086099[/C][/ROW]
[ROW][C]25[/C][C]2529[/C][C]2364.00602923632[/C][C]164.993970763677[/C][/ROW]
[ROW][C]26[/C][C]2472[/C][C]2726.60730668541[/C][C]-254.607306685407[/C][/ROW]
[ROW][C]27[/C][C]3134[/C][C]3192.82320107236[/C][C]-58.8232010723636[/C][/ROW]
[ROW][C]28[/C][C]2789[/C][C]3053.95672088088[/C][C]-264.956720880879[/C][/ROW]
[ROW][C]29[/C][C]2758[/C][C]2898.6628602674[/C][C]-140.6628602674[/C][/ROW]
[ROW][C]30[/C][C]2993[/C][C]2836.62229787113[/C][C]156.377702128866[/C][/ROW]
[ROW][C]31[/C][C]3282[/C][C]3143.07883611707[/C][C]138.921163882932[/C][/ROW]
[ROW][C]32[/C][C]3437[/C][C]4061.68473144673[/C][C]-624.684731446733[/C][/ROW]
[ROW][C]33[/C][C]2804[/C][C]2901.54979309679[/C][C]-97.5497930967904[/C][/ROW]
[ROW][C]34[/C][C]3076[/C][C]3421.16448977267[/C][C]-345.164489772670[/C][/ROW]
[ROW][C]35[/C][C]3782[/C][C]4188.40004272526[/C][C]-406.400042725262[/C][/ROW]
[ROW][C]36[/C][C]3889[/C][C]4148.64968698426[/C][C]-259.649686984263[/C][/ROW]
[ROW][C]37[/C][C]2271[/C][C]2397.63883920792[/C][C]-126.638839207915[/C][/ROW]
[ROW][C]38[/C][C]2452[/C][C]2576.07994645867[/C][C]-124.079946458666[/C][/ROW]
[ROW][C]39[/C][C]3084[/C][C]3102.66234208457[/C][C]-18.6623420845667[/C][/ROW]
[ROW][C]40[/C][C]2522[/C][C]2888.21186409838[/C][C]-366.211864098378[/C][/ROW]
[ROW][C]41[/C][C]2769[/C][C]2742.05940324039[/C][C]26.9405967596081[/C][/ROW]
[ROW][C]42[/C][C]3438[/C][C]2777.29625715575[/C][C]660.703742844251[/C][/ROW]
[ROW][C]43[/C][C]2839[/C][C]3128.38860904603[/C][C]-289.388609046026[/C][/ROW]
[ROW][C]44[/C][C]3746[/C][C]3741.33388614964[/C][C]4.6661138503614[/C][/ROW]
[ROW][C]45[/C][C]2632[/C][C]2812.33696108994[/C][C]-180.336961089944[/C][/ROW]
[ROW][C]46[/C][C]2851[/C][C]3233.66251037908[/C][C]-382.662510379085[/C][/ROW]
[ROW][C]47[/C][C]3871[/C][C]3965.92261036955[/C][C]-94.9226103695464[/C][/ROW]
[ROW][C]48[/C][C]3618[/C][C]4001.26623179294[/C][C]-383.26623179294[/C][/ROW]
[ROW][C]49[/C][C]2389[/C][C]2266.63210520868[/C][C]122.367894791320[/C][/ROW]
[ROW][C]50[/C][C]2344[/C][C]2468.55758762906[/C][C]-124.557587629064[/C][/ROW]
[ROW][C]51[/C][C]2678[/C][C]3019.9821309966[/C][C]-341.982130996601[/C][/ROW]
[ROW][C]52[/C][C]2492[/C][C]2647.14080399939[/C][C]-155.140803999393[/C][/ROW]
[ROW][C]53[/C][C]2858[/C][C]2640.56474709947[/C][C]217.43525290053[/C][/ROW]
[ROW][C]54[/C][C]2246[/C][C]2889.24455719202[/C][C]-643.244557192023[/C][/ROW]
[ROW][C]55[/C][C]2800[/C][C]2766.80344368023[/C][C]33.196556319765[/C][/ROW]
[ROW][C]56[/C][C]3869[/C][C]3496.06213210009[/C][C]372.937867899915[/C][/ROW]
[ROW][C]57[/C][C]3007[/C][C]2542.66774864412[/C][C]464.332251355881[/C][/ROW]
[ROW][C]58[/C][C]3023[/C][C]2973.16047335934[/C][C]49.8395266406642[/C][/ROW]
[ROW][C]59[/C][C]3907[/C][C]3844.45119617801[/C][C]62.5488038219873[/C][/ROW]
[ROW][C]60[/C][C]4209[/C][C]3806.84868640701[/C][C]402.151313592991[/C][/ROW]
[ROW][C]61[/C][C]2353[/C][C]2329.76460618054[/C][C]23.2353938194615[/C][/ROW]
[ROW][C]62[/C][C]2570[/C][C]2445.40280050067[/C][C]124.597199499333[/C][/ROW]
[ROW][C]63[/C][C]2903[/C][C]2964.46494134045[/C][C]-61.4649413404509[/C][/ROW]
[ROW][C]64[/C][C]2910[/C][C]2691.16850706248[/C][C]218.831492937523[/C][/ROW]
[ROW][C]65[/C][C]3782[/C][C]2856.35147252505[/C][C]925.648527474953[/C][/ROW]
[ROW][C]66[/C][C]2759[/C][C]2939.32822162209[/C][C]-180.328221622091[/C][/ROW]
[ROW][C]67[/C][C]2931[/C][C]3103.25163278733[/C][C]-172.251632787325[/C][/ROW]
[ROW][C]68[/C][C]3641[/C][C]3930.28429496249[/C][C]-289.284294962492[/C][/ROW]
[ROW][C]69[/C][C]2794[/C][C]2936.06447428926[/C][C]-142.064474289257[/C][/ROW]
[ROW][C]70[/C][C]3070[/C][C]3170.3794106414[/C][C]-100.379410641397[/C][/ROW]
[ROW][C]71[/C][C]3576[/C][C]4033.43241840469[/C][C]-457.432418404686[/C][/ROW]
[ROW][C]72[/C][C]4106[/C][C]4039.91144206063[/C][C]66.0885579393744[/C][/ROW]
[ROW][C]73[/C][C]2452[/C][C]2403.18067424855[/C][C]48.8193257514458[/C][/ROW]
[ROW][C]74[/C][C]2206[/C][C]2553.37813390341[/C][C]-347.378133903406[/C][/ROW]
[ROW][C]75[/C][C]2488[/C][C]2952.68895069317[/C][C]-464.688950693167[/C][/ROW]
[ROW][C]76[/C][C]2416[/C][C]2710.19466911439[/C][C]-294.194669114394[/C][/ROW]
[ROW][C]77[/C][C]2534[/C][C]3021.53097666638[/C][C]-487.530976666377[/C][/ROW]
[ROW][C]78[/C][C]2521[/C][C]2564.60394020959[/C][C]-43.6039402095853[/C][/ROW]
[ROW][C]79[/C][C]3093[/C][C]2727.10450740374[/C][C]365.895492596256[/C][/ROW]
[ROW][C]80[/C][C]3903[/C][C]3567.26062737423[/C][C]335.739372625771[/C][/ROW]
[ROW][C]81[/C][C]2907[/C][C]2683.95972539023[/C][C]223.040274609765[/C][/ROW]
[ROW][C]82[/C][C]3025[/C][C]2967.20294616971[/C][C]57.7970538302902[/C][/ROW]
[ROW][C]83[/C][C]3812[/C][C]3730.80775400432[/C][C]81.1922459956754[/C][/ROW]
[ROW][C]84[/C][C]4209[/C][C]3962.96892683598[/C][C]246.031073164016[/C][/ROW]
[ROW][C]85[/C][C]2138[/C][C]2340.82441112322[/C][C]-202.824411123217[/C][/ROW]
[ROW][C]86[/C][C]2419[/C][C]2332.61676822983[/C][C]86.3832317701654[/C][/ROW]
[ROW][C]87[/C][C]2622[/C][C]2747.97003496763[/C][C]-125.970034967634[/C][/ROW]
[ROW][C]88[/C][C]2912[/C][C]2602.07257418404[/C][C]309.927425815963[/C][/ROW]
[ROW][C]89[/C][C]2708[/C][C]2934.00668175509[/C][C]-226.006681755093[/C][/ROW]
[ROW][C]90[/C][C]2798[/C][C]2656.02211769573[/C][C]141.977882304272[/C][/ROW]
[ROW][C]91[/C][C]3254[/C][C]2978.844039266[/C][C]275.155960734003[/C][/ROW]
[ROW][C]92[/C][C]2895[/C][C]3807.74977932082[/C][C]-912.74977932082[/C][/ROW]
[ROW][C]93[/C][C]3263[/C][C]2735.53052504221[/C][C]527.469474957786[/C][/ROW]
[ROW][C]94[/C][C]3736[/C][C]3006.73757444092[/C][C]729.262425559083[/C][/ROW]
[ROW][C]95[/C][C]4077[/C][C]3867.35356930211[/C][C]209.646430697892[/C][/ROW]
[ROW][C]96[/C][C]4097[/C][C]4174.81369316516[/C][C]-77.8136931651561[/C][/ROW]
[ROW][C]97[/C][C]2175[/C][C]2378.76906557102[/C][C]-203.769065571024[/C][/ROW]
[ROW][C]98[/C][C]3138[/C][C]2466.17086096644[/C][C]671.829139033559[/C][/ROW]
[ROW][C]99[/C][C]2823[/C][C]2897.55952585991[/C][C]-74.55952585991[/C][/ROW]
[ROW][C]100[/C][C]2498[/C][C]2904.30720429103[/C][C]-406.307204291029[/C][/ROW]
[ROW][C]101[/C][C]2822[/C][C]2986.37093875851[/C][C]-164.370938758506[/C][/ROW]
[ROW][C]102[/C][C]2738[/C][C]2836.08156851991[/C][C]-98.08156851991[/C][/ROW]
[ROW][C]103[/C][C]4137[/C][C]3174.54150425071[/C][C]962.458495749285[/C][/ROW]
[ROW][C]104[/C][C]3515[/C][C]3727.02166685362[/C][C]-212.021666853620[/C][/ROW]
[ROW][C]105[/C][C]3785[/C][C]3203.81232021901[/C][C]581.187679780989[/C][/ROW]
[ROW][C]106[/C][C]3632[/C][C]3559.27921233145[/C][C]72.7207876685475[/C][/ROW]
[ROW][C]107[/C][C]4504[/C][C]4187.13378152134[/C][C]316.866218478655[/C][/ROW]
[ROW][C]108[/C][C]4451[/C][C]4428.83653876027[/C][C]22.1634612397338[/C][/ROW]
[ROW][C]109[/C][C]2550[/C][C]2617.20779232954[/C][C]-67.2077923295383[/C][/ROW]
[ROW][C]110[/C][C]2867[/C][C]3006.45075866478[/C][C]-139.450758664777[/C][/ROW]
[ROW][C]111[/C][C]3458[/C][C]3111.82887619607[/C][C]346.171123803929[/C][/ROW]
[ROW][C]112[/C][C]2961[/C][C]3076.37613699992[/C][C]-115.376136999919[/C][/ROW]
[ROW][C]113[/C][C]3163[/C][C]3281.17149012045[/C][C]-118.171490120448[/C][/ROW]
[ROW][C]114[/C][C]2880[/C][C]3169.19294939455[/C][C]-289.192949394546[/C][/ROW]
[ROW][C]115[/C][C]3331[/C][C]3824.91406458938[/C][C]-493.914064589375[/C][/ROW]
[ROW][C]116[/C][C]3062[/C][C]3831.90729050255[/C][C]-769.907290502546[/C][/ROW]
[ROW][C]117[/C][C]3534[/C][C]3482.06129244458[/C][C]51.9387075554214[/C][/ROW]
[ROW][C]118[/C][C]3622[/C][C]3604.99338399486[/C][C]17.0066160051406[/C][/ROW]
[ROW][C]119[/C][C]4464[/C][C]4292.44644409626[/C][C]171.553555903743[/C][/ROW]
[ROW][C]120[/C][C]5411[/C][C]4413.81936884119[/C][C]997.180631158812[/C][/ROW]
[ROW][C]121[/C][C]2564[/C][C]2691.05023608226[/C][C]-127.050236082257[/C][/ROW]
[ROW][C]122[/C][C]2820[/C][C]3046.81482232811[/C][C]-226.814822328106[/C][/ROW]
[ROW][C]123[/C][C]3508[/C][C]3288.36918390758[/C][C]219.630816092424[/C][/ROW]
[ROW][C]124[/C][C]3088[/C][C]3088.36093058357[/C][C]-0.360930583570735[/C][/ROW]
[ROW][C]125[/C][C]3299[/C][C]3302.03297606169[/C][C]-3.03297606168780[/C][/ROW]
[ROW][C]126[/C][C]2939[/C][C]3147.45246753272[/C][C]-208.452467532723[/C][/ROW]
[ROW][C]127[/C][C]3320[/C][C]3746.47363493709[/C][C]-426.473634937086[/C][/ROW]
[ROW][C]128[/C][C]3418[/C][C]3673.45993355708[/C][C]-255.459933557082[/C][/ROW]
[ROW][C]129[/C][C]3604[/C][C]3644.38614000392[/C][C]-40.3861400039191[/C][/ROW]
[ROW][C]130[/C][C]3495[/C][C]3745.99878241764[/C][C]-250.998782417642[/C][/ROW]
[ROW][C]131[/C][C]4163[/C][C]4447.4672487195[/C][C]-284.467248719498[/C][/ROW]
[ROW][C]132[/C][C]4882[/C][C]4765.1862314213[/C][C]116.813768578697[/C][/ROW]
[ROW][C]133[/C][C]2211[/C][C]2572.63210130036[/C][C]-361.632101300363[/C][/ROW]
[ROW][C]134[/C][C]3260[/C][C]2855.18846143743[/C][C]404.81153856257[/C][/ROW]
[ROW][C]135[/C][C]2992[/C][C]3304.97813353914[/C][C]-312.978133539136[/C][/ROW]
[ROW][C]136[/C][C]2425[/C][C]2958.45491158245[/C][C]-533.454911582449[/C][/ROW]
[ROW][C]137[/C][C]2707[/C][C]3089.10291247523[/C][C]-382.102912475235[/C][/ROW]
[ROW][C]138[/C][C]3244[/C][C]2804.36836860031[/C][C]439.631631399694[/C][/ROW]
[ROW][C]139[/C][C]3965[/C][C]3400.58248683110[/C][C]564.417513168898[/C][/ROW]
[ROW][C]140[/C][C]3315[/C][C]3495.70091234209[/C][C]-180.700912342089[/C][/ROW]
[ROW][C]141[/C][C]3333[/C][C]3536.44233408617[/C][C]-203.442334086170[/C][/ROW]
[ROW][C]142[/C][C]3583[/C][C]3544.82266004058[/C][C]38.1773399594249[/C][/ROW]
[ROW][C]143[/C][C]4021[/C][C]4266.04483352958[/C][C]-245.044833529581[/C][/ROW]
[ROW][C]144[/C][C]4904[/C][C]4708.4977029165[/C][C]195.502297083496[/C][/ROW]
[ROW][C]145[/C][C]2252[/C][C]2372.17517874422[/C][C]-120.175178744218[/C][/ROW]
[ROW][C]146[/C][C]2952[/C][C]2920.48238460767[/C][C]31.5176153923312[/C][/ROW]
[ROW][C]147[/C][C]3573[/C][C]3095.39618782337[/C][C]477.603812176634[/C][/ROW]
[ROW][C]148[/C][C]3048[/C][C]2778.03362813544[/C][C]269.966371864562[/C][/ROW]
[ROW][C]149[/C][C]3059[/C][C]3061.41375285475[/C][C]-2.41375285474896[/C][/ROW]
[ROW][C]150[/C][C]2731[/C][C]3089.00893130404[/C][C]-358.008931304042[/C][/ROW]
[ROW][C]151[/C][C]3563[/C][C]3629.64351109778[/C][C]-66.6435110977814[/C][/ROW]
[ROW][C]152[/C][C]3092[/C][C]3413.90280922877[/C][C]-321.902809228772[/C][/ROW]
[ROW][C]153[/C][C]3478[/C][C]3427.84934703614[/C][C]50.1506529638605[/C][/ROW]
[ROW][C]154[/C][C]3478[/C][C]3542.2437317922[/C][C]-64.2437317922008[/C][/ROW]
[ROW][C]155[/C][C]4308[/C][C]4161.49572906673[/C][C]146.504270933275[/C][/ROW]
[ROW][C]156[/C][C]5029[/C][C]4791.09931454002[/C][C]237.900685459981[/C][/ROW]
[ROW][C]157[/C][C]2075[/C][C]2363.85625030521[/C][C]-288.856250305212[/C][/ROW]
[ROW][C]158[/C][C]3264[/C][C]2939.52635862239[/C][C]324.473641377605[/C][/ROW]
[ROW][C]159[/C][C]3308[/C][C]3292.48448941245[/C][C]15.5155105875529[/C][/ROW]
[ROW][C]160[/C][C]3688[/C][C]2853.21933533991[/C][C]834.780664660094[/C][/ROW]
[ROW][C]161[/C][C]3136[/C][C]3125.13319850902[/C][C]10.8668014909777[/C][/ROW]
[ROW][C]162[/C][C]2824[/C][C]3047.65581804721[/C][C]-223.655818047206[/C][/ROW]
[ROW][C]163[/C][C]3644[/C][C]3700.59537930672[/C][C]-56.5953793067156[/C][/ROW]
[ROW][C]164[/C][C]4694[/C][C]3411.74437099281[/C][C]1282.25562900719[/C][/ROW]
[ROW][C]165[/C][C]2914[/C][C]3756.2720860273[/C][C]-842.272086027302[/C][/ROW]
[ROW][C]166[/C][C]3686[/C][C]3735.98583927871[/C][C]-49.985839278705[/C][/ROW]
[ROW][C]167[/C][C]4358[/C][C]4433.36590475871[/C][C]-75.3659047587116[/C][/ROW]
[ROW][C]168[/C][C]5587[/C][C]5073.19211581412[/C][C]513.807884185875[/C][/ROW]
[ROW][C]169[/C][C]2265[/C][C]2527.00686188418[/C][C]-262.006861884177[/C][/ROW]
[ROW][C]170[/C][C]3685[/C][C]3308.33757430996[/C][C]376.662425690035[/C][/ROW]
[ROW][C]171[/C][C]3754[/C][C]3583.28421186176[/C][C]170.715788138243[/C][/ROW]
[ROW][C]172[/C][C]3708[/C][C]3431.18598058334[/C][C]276.814019416664[/C][/ROW]
[ROW][C]173[/C][C]3210[/C][C]3386.62104665384[/C][C]-176.62104665384[/C][/ROW]
[ROW][C]174[/C][C]3517[/C][C]3220.28636201448[/C][C]296.713637985523[/C][/ROW]
[ROW][C]175[/C][C]3905[/C][C]4000.45180595504[/C][C]-95.451805955035[/C][/ROW]
[ROW][C]176[/C][C]3670[/C][C]4134.66673322833[/C][C]-464.666733228330[/C][/ROW]
[ROW][C]177[/C][C]4221[/C][C]3600.33798063106[/C][C]620.662019368937[/C][/ROW]
[ROW][C]178[/C][C]4404[/C][C]4015.3344371608[/C][C]388.665562839199[/C][/ROW]
[ROW][C]179[/C][C]5086[/C][C]4770.86653169258[/C][C]315.133468307419[/C][/ROW]
[ROW][C]180[/C][C]5725[/C][C]5657.30927147469[/C][C]67.690728525311[/C][/ROW]
[ROW][C]181[/C][C]2367[/C][C]2826.40986638851[/C][C]-459.409866388513[/C][/ROW]
[ROW][C]182[/C][C]3819[/C][C]3792.52826834768[/C][C]26.4717316523179[/C][/ROW]
[ROW][C]183[/C][C]4067[/C][C]3967.77056413013[/C][C]99.2294358698682[/C][/ROW]
[ROW][C]184[/C][C]4022[/C][C]3846.84221389780[/C][C]175.157786102205[/C][/ROW]
[ROW][C]185[/C][C]3937[/C][C]3654.72035250663[/C][C]282.279647493373[/C][/ROW]
[ROW][C]186[/C][C]4365[/C][C]3701.86740927603[/C][C]663.132590723971[/C][/ROW]
[ROW][C]187[/C][C]4290[/C][C]4417.47133932666[/C][C]-127.471339326661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77750&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77750&T=2

As an alternative you can also use a QR Code:  

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

Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
1320721985.8426816239386.1573183760677
1424342331.83381956774102.166180432265
1529562837.70749586882118.292504131177
1628282728.7277934576899.2722065423186
1726872639.2606723636247.7393276363823
1826292618.4112485881510.5887514118508
1931502809.57697266319340.423027336813
2041193751.37676577387367.623234226128
2130302757.36156032045272.638439679548
2230553592.02773556861-537.027735568609
2338214348.72407950558-527.72407950558
2440014209.7351640861-208.735164086099
2525292364.00602923632164.993970763677
2624722726.60730668541-254.607306685407
2731343192.82320107236-58.8232010723636
2827893053.95672088088-264.956720880879
2927582898.6628602674-140.6628602674
3029932836.62229787113156.377702128866
3132823143.07883611707138.921163882932
3234374061.68473144673-624.684731446733
3328042901.54979309679-97.5497930967904
3430763421.16448977267-345.164489772670
3537824188.40004272526-406.400042725262
3638894148.64968698426-259.649686984263
3722712397.63883920792-126.638839207915
3824522576.07994645867-124.079946458666
3930843102.66234208457-18.6623420845667
4025222888.21186409838-366.211864098378
4127692742.0594032403926.9405967596081
4234382777.29625715575660.703742844251
4328393128.38860904603-289.388609046026
4437463741.333886149644.6661138503614
4526322812.33696108994-180.336961089944
4628513233.66251037908-382.662510379085
4738713965.92261036955-94.9226103695464
4836184001.26623179294-383.26623179294
4923892266.63210520868122.367894791320
5023442468.55758762906-124.557587629064
5126783019.9821309966-341.982130996601
5224922647.14080399939-155.140803999393
5328582640.56474709947217.43525290053
5422462889.24455719202-643.244557192023
5528002766.8034436802333.196556319765
5638693496.06213210009372.937867899915
5730072542.66774864412464.332251355881
5830232973.1604733593449.8395266406642
5939073844.4511961780162.5488038219873
6042093806.84868640701402.151313592991
6123532329.7646061805423.2353938194615
6225702445.40280050067124.597199499333
6329032964.46494134045-61.4649413404509
6429102691.16850706248218.831492937523
6537822856.35147252505925.648527474953
6627592939.32822162209-180.328221622091
6729313103.25163278733-172.251632787325
6836413930.28429496249-289.284294962492
6927942936.06447428926-142.064474289257
7030703170.3794106414-100.379410641397
7135764033.43241840469-457.432418404686
7241064039.9114420606366.0885579393744
7324522403.1806742485548.8193257514458
7422062553.37813390341-347.378133903406
7524882952.68895069317-464.688950693167
7624162710.19466911439-294.194669114394
7725343021.53097666638-487.530976666377
7825212564.60394020959-43.6039402095853
7930932727.10450740374365.895492596256
8039033567.26062737423335.739372625771
8129072683.95972539023223.040274609765
8230252967.2029461697157.7970538302902
8338123730.8077540043281.1922459956754
8442093962.96892683598246.031073164016
8521382340.82441112322-202.824411123217
8624192332.6167682298386.3832317701654
8726222747.97003496763-125.970034967634
8829122602.07257418404309.927425815963
8927082934.00668175509-226.006681755093
9027982656.02211769573141.977882304272
9132542978.844039266275.155960734003
9228953807.74977932082-912.74977932082
9332632735.53052504221527.469474957786
9437363006.73757444092729.262425559083
9540773867.35356930211209.646430697892
9640974174.81369316516-77.8136931651561
9721752378.76906557102-203.769065571024
9831382466.17086096644671.829139033559
9928232897.55952585991-74.55952585991
10024982904.30720429103-406.307204291029
10128222986.37093875851-164.370938758506
10227382836.08156851991-98.08156851991
10341373174.54150425071962.458495749285
10435153727.02166685362-212.021666853620
10537853203.81232021901581.187679780989
10636323559.2792123314572.7207876685475
10745044187.13378152134316.866218478655
10844514428.8365387602722.1634612397338
10925502617.20779232954-67.2077923295383
11028673006.45075866478-139.450758664777
11134583111.82887619607346.171123803929
11229613076.37613699992-115.376136999919
11331633281.17149012045-118.171490120448
11428803169.19294939455-289.192949394546
11533313824.91406458938-493.914064589375
11630623831.90729050255-769.907290502546
11735343482.0612924445851.9387075554214
11836223604.9933839948617.0066160051406
11944644292.44644409626171.553555903743
12054114413.81936884119997.180631158812
12125642691.05023608226-127.050236082257
12228203046.81482232811-226.814822328106
12335083288.36918390758219.630816092424
12430883088.36093058357-0.360930583570735
12532993302.03297606169-3.03297606168780
12629393147.45246753272-208.452467532723
12733203746.47363493709-426.473634937086
12834183673.45993355708-255.459933557082
12936043644.38614000392-40.3861400039191
13034953745.99878241764-250.998782417642
13141634447.4672487195-284.467248719498
13248824765.1862314213116.813768578697
13322112572.63210130036-361.632101300363
13432602855.18846143743404.81153856257
13529923304.97813353914-312.978133539136
13624252958.45491158245-533.454911582449
13727073089.10291247523-382.102912475235
13832442804.36836860031439.631631399694
13939653400.58248683110564.417513168898
14033153495.70091234209-180.700912342089
14133333536.44233408617-203.442334086170
14235833544.8226600405838.1773399594249
14340214266.04483352958-245.044833529581
14449044708.4977029165195.502297083496
14522522372.17517874422-120.175178744218
14629522920.4823846076731.5176153923312
14735733095.39618782337477.603812176634
14830482778.03362813544269.966371864562
14930593061.41375285475-2.41375285474896
15027313089.00893130404-358.008931304042
15135633629.64351109778-66.6435110977814
15230923413.90280922877-321.902809228772
15334783427.8493470361450.1506529638605
15434783542.2437317922-64.2437317922008
15543084161.49572906673146.504270933275
15650294791.09931454002237.900685459981
15720752363.85625030521-288.856250305212
15832642939.52635862239324.473641377605
15933083292.4844894124515.5155105875529
16036882853.21933533991834.780664660094
16131363125.1331985090210.8668014909777
16228243047.65581804721-223.655818047206
16336443700.59537930672-56.5953793067156
16446943411.744370992811282.25562900719
16529143756.2720860273-842.272086027302
16636863735.98583927871-49.985839278705
16743584433.36590475871-75.3659047587116
16855875073.19211581412513.807884185875
16922652527.00686188418-262.006861884177
17036853308.33757430996376.662425690035
17137543583.28421186176170.715788138243
17237083431.18598058334276.814019416664
17332103386.62104665384-176.62104665384
17435173220.28636201448296.713637985523
17539054000.45180595504-95.451805955035
17636704134.66673322833-464.666733228330
17742213600.33798063106620.662019368937
17844044015.3344371608388.665562839199
17950864770.86653169258315.133468307419
18057255657.3092714746967.690728525311
18123672826.40986638851-459.409866388513
18238193792.5282683476826.4717316523179
18340673967.7705641301399.2294358698682
18440223846.84221389780175.157786102205
18539373654.72035250663282.279647493373
18643653701.86740927603663.132590723971
18742904417.47133932666-127.471339326661







Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
1884445.046176529933762.815197109195127.27715595067
1894321.652304035393633.623037738625009.68157033217
1904599.173010476533904.69674372475293.64927722836
1915292.08723713244590.493506906795993.680967358
1926068.361371671325358.960698905716777.76204443693
1933070.104434958282352.191102183863788.0177677327
1944252.640927071153525.495762427094979.78609171521
1954455.728014708763718.621144981825192.8348844357
1964353.921129825613606.114667039975101.72759261125
1974179.946801650213420.697430738624939.1961725618
1984315.128579094153543.690018128925086.56714005939
1994702.047061400153917.672370492895486.4217523074

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
188 & 4445.04617652993 & 3762.81519710919 & 5127.27715595067 \tabularnewline
189 & 4321.65230403539 & 3633.62303773862 & 5009.68157033217 \tabularnewline
190 & 4599.17301047653 & 3904.6967437247 & 5293.64927722836 \tabularnewline
191 & 5292.0872371324 & 4590.49350690679 & 5993.680967358 \tabularnewline
192 & 6068.36137167132 & 5358.96069890571 & 6777.76204443693 \tabularnewline
193 & 3070.10443495828 & 2352.19110218386 & 3788.0177677327 \tabularnewline
194 & 4252.64092707115 & 3525.49576242709 & 4979.78609171521 \tabularnewline
195 & 4455.72801470876 & 3718.62114498182 & 5192.8348844357 \tabularnewline
196 & 4353.92112982561 & 3606.11466703997 & 5101.72759261125 \tabularnewline
197 & 4179.94680165021 & 3420.69743073862 & 4939.1961725618 \tabularnewline
198 & 4315.12857909415 & 3543.69001812892 & 5086.56714005939 \tabularnewline
199 & 4702.04706140015 & 3917.67237049289 & 5486.4217523074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77750&T=3

[TABLE]
[ROW][C]Extrapolation Forecasts of Exponential Smoothing[/C][/ROW]
[ROW][C]t[/C][C]Forecast[/C][C]95% Lower Bound[/C][C]95% Upper Bound[/C][/ROW]
[ROW][C]188[/C][C]4445.04617652993[/C][C]3762.81519710919[/C][C]5127.27715595067[/C][/ROW]
[ROW][C]189[/C][C]4321.65230403539[/C][C]3633.62303773862[/C][C]5009.68157033217[/C][/ROW]
[ROW][C]190[/C][C]4599.17301047653[/C][C]3904.6967437247[/C][C]5293.64927722836[/C][/ROW]
[ROW][C]191[/C][C]5292.0872371324[/C][C]4590.49350690679[/C][C]5993.680967358[/C][/ROW]
[ROW][C]192[/C][C]6068.36137167132[/C][C]5358.96069890571[/C][C]6777.76204443693[/C][/ROW]
[ROW][C]193[/C][C]3070.10443495828[/C][C]2352.19110218386[/C][C]3788.0177677327[/C][/ROW]
[ROW][C]194[/C][C]4252.64092707115[/C][C]3525.49576242709[/C][C]4979.78609171521[/C][/ROW]
[ROW][C]195[/C][C]4455.72801470876[/C][C]3718.62114498182[/C][C]5192.8348844357[/C][/ROW]
[ROW][C]196[/C][C]4353.92112982561[/C][C]3606.11466703997[/C][C]5101.72759261125[/C][/ROW]
[ROW][C]197[/C][C]4179.94680165021[/C][C]3420.69743073862[/C][C]4939.1961725618[/C][/ROW]
[ROW][C]198[/C][C]4315.12857909415[/C][C]3543.69001812892[/C][C]5086.56714005939[/C][/ROW]
[ROW][C]199[/C][C]4702.04706140015[/C][C]3917.67237049289[/C][C]5486.4217523074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77750&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77750&T=3

As an alternative you can also use a QR Code:  

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

Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
1884445.046176529933762.815197109195127.27715595067
1894321.652304035393633.623037738625009.68157033217
1904599.173010476533904.69674372475293.64927722836
1915292.08723713244590.493506906795993.680967358
1926068.361371671325358.960698905716777.76204443693
1933070.104434958282352.191102183863788.0177677327
1944252.640927071153525.495762427094979.78609171521
1954455.728014708763718.621144981825192.8348844357
1964353.921129825613606.114667039975101.72759261125
1974179.946801650213420.697430738624939.1961725618
1984315.128579094153543.690018128925086.56714005939
1994702.047061400153917.672370492895486.4217523074



Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = additive ;
Parameters (R input):
par1 = 12 ; par2 = Triple ; par3 = additive ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
if (par2 == 'Single') K <- 1
if (par2 == 'Double') K <- 2
if (par2 == 'Triple') K <- par1
nx <- length(x)
nxmK <- nx - K
x <- ts(x, frequency = par1)
if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F)
if (par2 == 'Double') fit <- HoltWinters(x, gamma=F)
if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3)
fit
myresid <- x - fit$fitted[,'xhat']
bitmap(file='test1.png')
op <- par(mfrow=c(2,1))
plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing')
plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors')
par(op)
dev.off()
bitmap(file='test2.png')
p <- predict(fit, par1, prediction.interval=TRUE)
np <- length(p[,1])
plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing')
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF')
spectrum(myresid,main='Residals Periodogram')
cpgram(myresid,main='Residal Cumulative Periodogram')
qqnorm(myresid,main='Residual Normal QQ Plot')
qqline(myresid)
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,fit$alpha)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,fit$beta)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'gamma',header=TRUE)
a<-table.element(a,fit$gamma)
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,'Interpolation Forecasts of Exponential Smoothing',4,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,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:nxmK) {
a<-table.row.start(a)
a<-table.element(a,i+K,header=TRUE)
a<-table.element(a,x[i+K])
a<-table.element(a,fit$fitted[i,'xhat'])
a<-table.element(a,myresid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Extrapolation Forecasts of Exponential Smoothing',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Forecast',header=TRUE)
a<-table.element(a,'95% Lower Bound',header=TRUE)
a<-table.element(a,'95% Upper Bound',header=TRUE)
a<-table.row.end(a)
for (i in 1:np) {
a<-table.row.start(a)
a<-table.element(a,nx+i,header=TRUE)
a<-table.element(a,p[i,'fit'])
a<-table.element(a,p[i,'lwr'])
a<-table.element(a,p[i,'upr'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')