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Author's title

Author*Unverified author*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationWed, 02 Jun 2010 19:54:41 +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/02/t1275508496kzp6u5qllal319o.htm/, Retrieved Thu, 28 Mar 2024 23:03:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77328, Retrieved Thu, 28 Mar 2024 23:03:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W62
Estimated Impact136
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Exponential Smoothing] [] [2010-06-02 19:54:41] [701fd7cac8325e39d69fe7641072905f] [Current]
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Dataseries X:
464
675
703
887
1139
1077
1318
1260
1120
963
996
960
530
883
894
1045
1199
1287
1565
1577
1076
918
1008
1063
544
635
804
980
1018
1064
1404
1286
1104
999
996
1015
615
722
832
977
1270
1437
1520
1708
1151
934
1159
1209
699
830
996
1124
1458
1270
1753
2258
1208
1241
1265
1828
809
997
1164
1205
1538
1513
1378
2083
1357
1536
1526
1376
779
1005
1193
1522
1539
1546
2116
2326
1596
1356
1553
1613
814
1150
1225
1691
1759
1754
2100
2062
2012
1897
1964
2186
966
1549
1538
1612
2078
2137
2907
2249
1883
1739
1828
1868
1138
1430
1809
1763
2200
2067
2503
2141
2103
1972
2181
2344
970
1199
1718
1683
2025
2051
2439
2353
2230
1852
2147
2286
1007
1665
1642
1518
1831
2207
2822
2393
2306
1785
2047
2171
1212
1335
2011
1860
1954
2152
2835
2224
2182
1992
2389
2724
891
1247
2017
2257
2255
2255
3057
3330
1896
2096
2374
2535
1041
1728
2201
2455
2204
2660
3670
2665
2639
2226
2586
2684
1185
1749
2459
2618
2585
3310
3923




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77328&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77328&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77328&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.129074112205745
beta0.000500934054976076
gamma0.322462326005777

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.129074112205745 \tabularnewline
beta & 0.000500934054976076 \tabularnewline
gamma & 0.322462326005777 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77328&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]0.129074112205745[/C][/ROW]
[ROW][C]beta[/C][C]0.000500934054976076[/C][/ROW]
[ROW][C]gamma[/C][C]0.322462326005777[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77328&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77328&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
alpha0.129074112205745
beta0.000500934054976076
gamma0.322462326005777







Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
13530488.83695900046341.163040999537
14883814.76918013628568.230819863715
15894834.64924201163159.3507579883687
161045999.19216524897245.8078347510281
1711991167.6015349569231.3984650430839
1812871265.8749276645721.1250723354269
1915651471.6836405559193.3163594440866
2015771416.83455770272160.165442297285
2110761269.50663614626-193.506636146263
229181065.72885869940-147.728858699401
2310081084.2152672451-76.2152672451004
2410631035.0381755838027.9618244161961
25544582.173549598269-38.1735495982692
26635950.279703272534-315.279703272534
27804917.8820476586-113.882047658599
289801063.43198202462-83.4319820246214
2910181215.98034271037-197.980342710371
3010641282.32424149349-218.324241493494
3114041473.86706678750-69.8670667874956
3212861417.88509443065-131.885094430645
3311041147.80505570157-43.8050557015699
34999982.5233897030116.4766102969901
359961041.06932055722-45.0693205572168
3610151025.42181012321-10.4218101232145
37615559.2035589790555.7964410209495
38722857.541913373212-135.541913373212
39832905.609678642965-73.6096786429654
409771069.12052501393-92.1205250139342
4112701190.3251274667779.6748725332277
4214371289.52881127662147.471188723384
4315201593.65374322978-73.6537432297798
4417081511.62678785961196.373212140391
4511511278.03622592088-127.036225920883
469341101.04125811502-167.041258115022
4711591121.0921475061437.9078524938625
4812091124.7664482118484.2335517881563
49699638.4276383008960.5723616991103
50830908.01061953216-78.0106195321601
51996989.4832224861966.51677751380385
5211241178.42304517839-54.4230451783903
5314581375.4535377775882.5464622224167
5412701505.99433837198-235.994338371978
5517531717.6584481686435.3415518313609
5622581723.28938701246534.710612987541
5712081396.55030916633-188.550309166326
5812411177.6247619925463.3752380074559
5912651298.02429530364-33.0242953036384
6018281305.41735025192522.582649748082
61809774.8326609436334.1673390563706
629971039.36945363520-42.3694536352036
6311641168.33975232397-4.33975232396506
6412051367.08090456414-162.080904564136
6515381626.2868854581-88.2868854581002
6615131646.33742562572-133.337425625715
6713781994.69039876606-616.690398766055
6820832063.1693690067219.8306309932782
6913571427.09831942623-70.0983194262324
7015361284.01934919386251.980650806142
7115261408.61492913749117.385070862512
7213761600.33223898861-224.332238988606
73779810.845167194428-31.8451671944277
7410051050.49573693738-45.4957369373781
7511931192.709374407260.290625592740071
7615221350.22596016804171.774039831964
7715391688.93680276946-149.936802769462
7815461688.23615636363-142.236156363628
7921161902.69253111387213.307468886131
8023262290.5926720051635.4073279948379
8115961558.1729423276237.8270576723808
8213561511.12962890956-155.129628909558
8315531548.211416314364.78858368563692
8416131632.52638986099-19.5263898609867
85814866.013219630146-52.0132196301461
8611501117.0259702048432.9740297951616
8712251295.3822019996-70.3822019995996
8816911506.36868386985184.631316130150
8917591772.35514762486-13.3551476248631
9017541791.71838832041-37.718388320415
9121002149.20213814788-49.202138147878
9220622475.75202043459-413.75202043459
9320121647.94559089079364.054409109214
9418971579.19509767656317.804902323442
9519641733.09269504805230.907304951946
9621861848.74678049347337.25321950653
97966990.637162874265-24.6371628742654
9815491315.29531853704233.704681462955
9915381516.3056595086721.6943404913313
10016121865.89816072850-253.898160728497
10120782047.4138842663830.5861157336158
10221372065.9720585653271.0279414346755
10329072492.28903847496414.710961525036
10422492815.40117186052-566.401171860515
10518832075.63354545762-192.633545457625
10617391899.78141450023-160.781414500229
10718281973.93893170057-145.938931700572
10818682075.68898702426-207.688987024259
10911381014.12589478372123.874105216275
11014301448.76050845518-18.7605084551751
11118091560.14900034589248.850999654105
11217631871.68832633665-108.688326336651
11322002167.1395733262232.8604266737848
11420672197.97278776171-130.972787761711
11525032712.60059138710-209.600591387104
11621412675.05191677941-534.051916779406
11721032038.6226254684964.377374531513
11819721900.4865422168171.5134577831939
11921812011.98252307719169.017476922813
12023442141.93416303978202.065836960222
1219701141.29282653254-171.292826532538
12211991516.61682348787-317.616823487874
12317181667.4100784798650.5899215201352
12416831853.85438536200-170.854385361998
12520252181.80535089781-156.805350897809
12620512142.05746174646-91.0574617464604
12724392635.84388087434-196.84388087434
12823532505.50343662525-152.503436625251
12922302081.28217536558148.717824634422
13018521953.21950775809-101.219507758093
13121472069.8603723491877.1396276508167
13222862196.4049374747689.5950625252426
13310071083.99651255359-76.9965125535855
13416651428.83744025122236.16255974878
13516421769.46825088515-127.468250885149
13615181874.24915300942-356.24915300942
13718312190.2679331991-359.267933199102
13822072142.4891688881264.5108311118788
13928222636.13763741813185.862362581871
14023932562.88994936457-169.889949364575
14123062207.2804964215498.7195035784575
14217851994.05865432917-209.058654329167
14320472151.59126451920-104.591264519196
14421712259.86660013019-88.8666001301949
14512121069.36234318583142.637656814169
14613351543.63471134505-208.634711345049
14720111723.1722805291287.827719470902
14818601815.8833015816244.1166984183819
14919542199.31242062952-245.312420629516
15021522291.62126002699-139.621260026993
15128352816.8371657230918.1628342769109
15222242613.27011602859-389.270116028592
15321822297.00876454059-115.008764540588
15419921963.9555869164928.0444130835087
15523892187.4827704661201.517229533898
15627242345.20316503874378.79683496126
1578911193.38919948532-302.389199485323
15812471518.69079291897-271.690792918967
15920171833.62108883129183.378911168708
16022571844.12159399804412.878406001957
16122552202.6683818664152.3316181335927
16222552370.2214183267-115.221418326702
16330572973.8904276855283.1095723144804
16433302643.08637504267686.91362495733
16518962519.81158383102-623.81158383102
16620962136.98116213232-40.9811621323188
16723742419.93500335947-45.9350033594742
16825352603.90129612003-68.9012961200287
16910411147.16878251544-106.168782515444
17017281526.39053984195201.609460158049
17122012077.77000369211123.229996307889
17224552145.41238810246309.587611897541
17322042405.83168961193-201.831689611933
17426602500.46608959121159.533910408795
17536703251.46625919908418.533740800921
17626653108.31874948913-443.318749489129
17726392439.44977608105199.550223918949
17822262313.34448108028-87.3444810802825
17925862612.52680620413-26.526806204125
18026842807.31910509382-123.319105093822
18111851210.11578193156-25.1157819315579
18217491729.3410237612019.6589762388023
18324592272.62009321613186.379906783869
18426182406.4619875861211.538012413898
18525852514.6406185491970.3593814508117
18633102763.70256109067546.297438909328
18739233717.7065728895205.293427110496

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
13 & 530 & 488.836959000463 & 41.163040999537 \tabularnewline
14 & 883 & 814.769180136285 & 68.230819863715 \tabularnewline
15 & 894 & 834.649242011631 & 59.3507579883687 \tabularnewline
16 & 1045 & 999.192165248972 & 45.8078347510281 \tabularnewline
17 & 1199 & 1167.60153495692 & 31.3984650430839 \tabularnewline
18 & 1287 & 1265.87492766457 & 21.1250723354269 \tabularnewline
19 & 1565 & 1471.68364055591 & 93.3163594440866 \tabularnewline
20 & 1577 & 1416.83455770272 & 160.165442297285 \tabularnewline
21 & 1076 & 1269.50663614626 & -193.506636146263 \tabularnewline
22 & 918 & 1065.72885869940 & -147.728858699401 \tabularnewline
23 & 1008 & 1084.2152672451 & -76.2152672451004 \tabularnewline
24 & 1063 & 1035.03817558380 & 27.9618244161961 \tabularnewline
25 & 544 & 582.173549598269 & -38.1735495982692 \tabularnewline
26 & 635 & 950.279703272534 & -315.279703272534 \tabularnewline
27 & 804 & 917.8820476586 & -113.882047658599 \tabularnewline
28 & 980 & 1063.43198202462 & -83.4319820246214 \tabularnewline
29 & 1018 & 1215.98034271037 & -197.980342710371 \tabularnewline
30 & 1064 & 1282.32424149349 & -218.324241493494 \tabularnewline
31 & 1404 & 1473.86706678750 & -69.8670667874956 \tabularnewline
32 & 1286 & 1417.88509443065 & -131.885094430645 \tabularnewline
33 & 1104 & 1147.80505570157 & -43.8050557015699 \tabularnewline
34 & 999 & 982.52338970301 & 16.4766102969901 \tabularnewline
35 & 996 & 1041.06932055722 & -45.0693205572168 \tabularnewline
36 & 1015 & 1025.42181012321 & -10.4218101232145 \tabularnewline
37 & 615 & 559.20355897905 & 55.7964410209495 \tabularnewline
38 & 722 & 857.541913373212 & -135.541913373212 \tabularnewline
39 & 832 & 905.609678642965 & -73.6096786429654 \tabularnewline
40 & 977 & 1069.12052501393 & -92.1205250139342 \tabularnewline
41 & 1270 & 1190.32512746677 & 79.6748725332277 \tabularnewline
42 & 1437 & 1289.52881127662 & 147.471188723384 \tabularnewline
43 & 1520 & 1593.65374322978 & -73.6537432297798 \tabularnewline
44 & 1708 & 1511.62678785961 & 196.373212140391 \tabularnewline
45 & 1151 & 1278.03622592088 & -127.036225920883 \tabularnewline
46 & 934 & 1101.04125811502 & -167.041258115022 \tabularnewline
47 & 1159 & 1121.09214750614 & 37.9078524938625 \tabularnewline
48 & 1209 & 1124.76644821184 & 84.2335517881563 \tabularnewline
49 & 699 & 638.42763830089 & 60.5723616991103 \tabularnewline
50 & 830 & 908.01061953216 & -78.0106195321601 \tabularnewline
51 & 996 & 989.483222486196 & 6.51677751380385 \tabularnewline
52 & 1124 & 1178.42304517839 & -54.4230451783903 \tabularnewline
53 & 1458 & 1375.45353777758 & 82.5464622224167 \tabularnewline
54 & 1270 & 1505.99433837198 & -235.994338371978 \tabularnewline
55 & 1753 & 1717.65844816864 & 35.3415518313609 \tabularnewline
56 & 2258 & 1723.28938701246 & 534.710612987541 \tabularnewline
57 & 1208 & 1396.55030916633 & -188.550309166326 \tabularnewline
58 & 1241 & 1177.62476199254 & 63.3752380074559 \tabularnewline
59 & 1265 & 1298.02429530364 & -33.0242953036384 \tabularnewline
60 & 1828 & 1305.41735025192 & 522.582649748082 \tabularnewline
61 & 809 & 774.83266094363 & 34.1673390563706 \tabularnewline
62 & 997 & 1039.36945363520 & -42.3694536352036 \tabularnewline
63 & 1164 & 1168.33975232397 & -4.33975232396506 \tabularnewline
64 & 1205 & 1367.08090456414 & -162.080904564136 \tabularnewline
65 & 1538 & 1626.2868854581 & -88.2868854581002 \tabularnewline
66 & 1513 & 1646.33742562572 & -133.337425625715 \tabularnewline
67 & 1378 & 1994.69039876606 & -616.690398766055 \tabularnewline
68 & 2083 & 2063.16936900672 & 19.8306309932782 \tabularnewline
69 & 1357 & 1427.09831942623 & -70.0983194262324 \tabularnewline
70 & 1536 & 1284.01934919386 & 251.980650806142 \tabularnewline
71 & 1526 & 1408.61492913749 & 117.385070862512 \tabularnewline
72 & 1376 & 1600.33223898861 & -224.332238988606 \tabularnewline
73 & 779 & 810.845167194428 & -31.8451671944277 \tabularnewline
74 & 1005 & 1050.49573693738 & -45.4957369373781 \tabularnewline
75 & 1193 & 1192.70937440726 & 0.290625592740071 \tabularnewline
76 & 1522 & 1350.22596016804 & 171.774039831964 \tabularnewline
77 & 1539 & 1688.93680276946 & -149.936802769462 \tabularnewline
78 & 1546 & 1688.23615636363 & -142.236156363628 \tabularnewline
79 & 2116 & 1902.69253111387 & 213.307468886131 \tabularnewline
80 & 2326 & 2290.59267200516 & 35.4073279948379 \tabularnewline
81 & 1596 & 1558.17294232762 & 37.8270576723808 \tabularnewline
82 & 1356 & 1511.12962890956 & -155.129628909558 \tabularnewline
83 & 1553 & 1548.21141631436 & 4.78858368563692 \tabularnewline
84 & 1613 & 1632.52638986099 & -19.5263898609867 \tabularnewline
85 & 814 & 866.013219630146 & -52.0132196301461 \tabularnewline
86 & 1150 & 1117.02597020484 & 32.9740297951616 \tabularnewline
87 & 1225 & 1295.3822019996 & -70.3822019995996 \tabularnewline
88 & 1691 & 1506.36868386985 & 184.631316130150 \tabularnewline
89 & 1759 & 1772.35514762486 & -13.3551476248631 \tabularnewline
90 & 1754 & 1791.71838832041 & -37.718388320415 \tabularnewline
91 & 2100 & 2149.20213814788 & -49.202138147878 \tabularnewline
92 & 2062 & 2475.75202043459 & -413.75202043459 \tabularnewline
93 & 2012 & 1647.94559089079 & 364.054409109214 \tabularnewline
94 & 1897 & 1579.19509767656 & 317.804902323442 \tabularnewline
95 & 1964 & 1733.09269504805 & 230.907304951946 \tabularnewline
96 & 2186 & 1848.74678049347 & 337.25321950653 \tabularnewline
97 & 966 & 990.637162874265 & -24.6371628742654 \tabularnewline
98 & 1549 & 1315.29531853704 & 233.704681462955 \tabularnewline
99 & 1538 & 1516.30565950867 & 21.6943404913313 \tabularnewline
100 & 1612 & 1865.89816072850 & -253.898160728497 \tabularnewline
101 & 2078 & 2047.41388426638 & 30.5861157336158 \tabularnewline
102 & 2137 & 2065.97205856532 & 71.0279414346755 \tabularnewline
103 & 2907 & 2492.28903847496 & 414.710961525036 \tabularnewline
104 & 2249 & 2815.40117186052 & -566.401171860515 \tabularnewline
105 & 1883 & 2075.63354545762 & -192.633545457625 \tabularnewline
106 & 1739 & 1899.78141450023 & -160.781414500229 \tabularnewline
107 & 1828 & 1973.93893170057 & -145.938931700572 \tabularnewline
108 & 1868 & 2075.68898702426 & -207.688987024259 \tabularnewline
109 & 1138 & 1014.12589478372 & 123.874105216275 \tabularnewline
110 & 1430 & 1448.76050845518 & -18.7605084551751 \tabularnewline
111 & 1809 & 1560.14900034589 & 248.850999654105 \tabularnewline
112 & 1763 & 1871.68832633665 & -108.688326336651 \tabularnewline
113 & 2200 & 2167.13957332622 & 32.8604266737848 \tabularnewline
114 & 2067 & 2197.97278776171 & -130.972787761711 \tabularnewline
115 & 2503 & 2712.60059138710 & -209.600591387104 \tabularnewline
116 & 2141 & 2675.05191677941 & -534.051916779406 \tabularnewline
117 & 2103 & 2038.62262546849 & 64.377374531513 \tabularnewline
118 & 1972 & 1900.48654221681 & 71.5134577831939 \tabularnewline
119 & 2181 & 2011.98252307719 & 169.017476922813 \tabularnewline
120 & 2344 & 2141.93416303978 & 202.065836960222 \tabularnewline
121 & 970 & 1141.29282653254 & -171.292826532538 \tabularnewline
122 & 1199 & 1516.61682348787 & -317.616823487874 \tabularnewline
123 & 1718 & 1667.41007847986 & 50.5899215201352 \tabularnewline
124 & 1683 & 1853.85438536200 & -170.854385361998 \tabularnewline
125 & 2025 & 2181.80535089781 & -156.805350897809 \tabularnewline
126 & 2051 & 2142.05746174646 & -91.0574617464604 \tabularnewline
127 & 2439 & 2635.84388087434 & -196.84388087434 \tabularnewline
128 & 2353 & 2505.50343662525 & -152.503436625251 \tabularnewline
129 & 2230 & 2081.28217536558 & 148.717824634422 \tabularnewline
130 & 1852 & 1953.21950775809 & -101.219507758093 \tabularnewline
131 & 2147 & 2069.86037234918 & 77.1396276508167 \tabularnewline
132 & 2286 & 2196.40493747476 & 89.5950625252426 \tabularnewline
133 & 1007 & 1083.99651255359 & -76.9965125535855 \tabularnewline
134 & 1665 & 1428.83744025122 & 236.16255974878 \tabularnewline
135 & 1642 & 1769.46825088515 & -127.468250885149 \tabularnewline
136 & 1518 & 1874.24915300942 & -356.24915300942 \tabularnewline
137 & 1831 & 2190.2679331991 & -359.267933199102 \tabularnewline
138 & 2207 & 2142.48916888812 & 64.5108311118788 \tabularnewline
139 & 2822 & 2636.13763741813 & 185.862362581871 \tabularnewline
140 & 2393 & 2562.88994936457 & -169.889949364575 \tabularnewline
141 & 2306 & 2207.28049642154 & 98.7195035784575 \tabularnewline
142 & 1785 & 1994.05865432917 & -209.058654329167 \tabularnewline
143 & 2047 & 2151.59126451920 & -104.591264519196 \tabularnewline
144 & 2171 & 2259.86660013019 & -88.8666001301949 \tabularnewline
145 & 1212 & 1069.36234318583 & 142.637656814169 \tabularnewline
146 & 1335 & 1543.63471134505 & -208.634711345049 \tabularnewline
147 & 2011 & 1723.1722805291 & 287.827719470902 \tabularnewline
148 & 1860 & 1815.88330158162 & 44.1166984183819 \tabularnewline
149 & 1954 & 2199.31242062952 & -245.312420629516 \tabularnewline
150 & 2152 & 2291.62126002699 & -139.621260026993 \tabularnewline
151 & 2835 & 2816.83716572309 & 18.1628342769109 \tabularnewline
152 & 2224 & 2613.27011602859 & -389.270116028592 \tabularnewline
153 & 2182 & 2297.00876454059 & -115.008764540588 \tabularnewline
154 & 1992 & 1963.95558691649 & 28.0444130835087 \tabularnewline
155 & 2389 & 2187.4827704661 & 201.517229533898 \tabularnewline
156 & 2724 & 2345.20316503874 & 378.79683496126 \tabularnewline
157 & 891 & 1193.38919948532 & -302.389199485323 \tabularnewline
158 & 1247 & 1518.69079291897 & -271.690792918967 \tabularnewline
159 & 2017 & 1833.62108883129 & 183.378911168708 \tabularnewline
160 & 2257 & 1844.12159399804 & 412.878406001957 \tabularnewline
161 & 2255 & 2202.66838186641 & 52.3316181335927 \tabularnewline
162 & 2255 & 2370.2214183267 & -115.221418326702 \tabularnewline
163 & 3057 & 2973.89042768552 & 83.1095723144804 \tabularnewline
164 & 3330 & 2643.08637504267 & 686.91362495733 \tabularnewline
165 & 1896 & 2519.81158383102 & -623.81158383102 \tabularnewline
166 & 2096 & 2136.98116213232 & -40.9811621323188 \tabularnewline
167 & 2374 & 2419.93500335947 & -45.9350033594742 \tabularnewline
168 & 2535 & 2603.90129612003 & -68.9012961200287 \tabularnewline
169 & 1041 & 1147.16878251544 & -106.168782515444 \tabularnewline
170 & 1728 & 1526.39053984195 & 201.609460158049 \tabularnewline
171 & 2201 & 2077.77000369211 & 123.229996307889 \tabularnewline
172 & 2455 & 2145.41238810246 & 309.587611897541 \tabularnewline
173 & 2204 & 2405.83168961193 & -201.831689611933 \tabularnewline
174 & 2660 & 2500.46608959121 & 159.533910408795 \tabularnewline
175 & 3670 & 3251.46625919908 & 418.533740800921 \tabularnewline
176 & 2665 & 3108.31874948913 & -443.318749489129 \tabularnewline
177 & 2639 & 2439.44977608105 & 199.550223918949 \tabularnewline
178 & 2226 & 2313.34448108028 & -87.3444810802825 \tabularnewline
179 & 2586 & 2612.52680620413 & -26.526806204125 \tabularnewline
180 & 2684 & 2807.31910509382 & -123.319105093822 \tabularnewline
181 & 1185 & 1210.11578193156 & -25.1157819315579 \tabularnewline
182 & 1749 & 1729.34102376120 & 19.6589762388023 \tabularnewline
183 & 2459 & 2272.62009321613 & 186.379906783869 \tabularnewline
184 & 2618 & 2406.4619875861 & 211.538012413898 \tabularnewline
185 & 2585 & 2514.64061854919 & 70.3593814508117 \tabularnewline
186 & 3310 & 2763.70256109067 & 546.297438909328 \tabularnewline
187 & 3923 & 3717.7065728895 & 205.293427110496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77328&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]530[/C][C]488.836959000463[/C][C]41.163040999537[/C][/ROW]
[ROW][C]14[/C][C]883[/C][C]814.769180136285[/C][C]68.230819863715[/C][/ROW]
[ROW][C]15[/C][C]894[/C][C]834.649242011631[/C][C]59.3507579883687[/C][/ROW]
[ROW][C]16[/C][C]1045[/C][C]999.192165248972[/C][C]45.8078347510281[/C][/ROW]
[ROW][C]17[/C][C]1199[/C][C]1167.60153495692[/C][C]31.3984650430839[/C][/ROW]
[ROW][C]18[/C][C]1287[/C][C]1265.87492766457[/C][C]21.1250723354269[/C][/ROW]
[ROW][C]19[/C][C]1565[/C][C]1471.68364055591[/C][C]93.3163594440866[/C][/ROW]
[ROW][C]20[/C][C]1577[/C][C]1416.83455770272[/C][C]160.165442297285[/C][/ROW]
[ROW][C]21[/C][C]1076[/C][C]1269.50663614626[/C][C]-193.506636146263[/C][/ROW]
[ROW][C]22[/C][C]918[/C][C]1065.72885869940[/C][C]-147.728858699401[/C][/ROW]
[ROW][C]23[/C][C]1008[/C][C]1084.2152672451[/C][C]-76.2152672451004[/C][/ROW]
[ROW][C]24[/C][C]1063[/C][C]1035.03817558380[/C][C]27.9618244161961[/C][/ROW]
[ROW][C]25[/C][C]544[/C][C]582.173549598269[/C][C]-38.1735495982692[/C][/ROW]
[ROW][C]26[/C][C]635[/C][C]950.279703272534[/C][C]-315.279703272534[/C][/ROW]
[ROW][C]27[/C][C]804[/C][C]917.8820476586[/C][C]-113.882047658599[/C][/ROW]
[ROW][C]28[/C][C]980[/C][C]1063.43198202462[/C][C]-83.4319820246214[/C][/ROW]
[ROW][C]29[/C][C]1018[/C][C]1215.98034271037[/C][C]-197.980342710371[/C][/ROW]
[ROW][C]30[/C][C]1064[/C][C]1282.32424149349[/C][C]-218.324241493494[/C][/ROW]
[ROW][C]31[/C][C]1404[/C][C]1473.86706678750[/C][C]-69.8670667874956[/C][/ROW]
[ROW][C]32[/C][C]1286[/C][C]1417.88509443065[/C][C]-131.885094430645[/C][/ROW]
[ROW][C]33[/C][C]1104[/C][C]1147.80505570157[/C][C]-43.8050557015699[/C][/ROW]
[ROW][C]34[/C][C]999[/C][C]982.52338970301[/C][C]16.4766102969901[/C][/ROW]
[ROW][C]35[/C][C]996[/C][C]1041.06932055722[/C][C]-45.0693205572168[/C][/ROW]
[ROW][C]36[/C][C]1015[/C][C]1025.42181012321[/C][C]-10.4218101232145[/C][/ROW]
[ROW][C]37[/C][C]615[/C][C]559.20355897905[/C][C]55.7964410209495[/C][/ROW]
[ROW][C]38[/C][C]722[/C][C]857.541913373212[/C][C]-135.541913373212[/C][/ROW]
[ROW][C]39[/C][C]832[/C][C]905.609678642965[/C][C]-73.6096786429654[/C][/ROW]
[ROW][C]40[/C][C]977[/C][C]1069.12052501393[/C][C]-92.1205250139342[/C][/ROW]
[ROW][C]41[/C][C]1270[/C][C]1190.32512746677[/C][C]79.6748725332277[/C][/ROW]
[ROW][C]42[/C][C]1437[/C][C]1289.52881127662[/C][C]147.471188723384[/C][/ROW]
[ROW][C]43[/C][C]1520[/C][C]1593.65374322978[/C][C]-73.6537432297798[/C][/ROW]
[ROW][C]44[/C][C]1708[/C][C]1511.62678785961[/C][C]196.373212140391[/C][/ROW]
[ROW][C]45[/C][C]1151[/C][C]1278.03622592088[/C][C]-127.036225920883[/C][/ROW]
[ROW][C]46[/C][C]934[/C][C]1101.04125811502[/C][C]-167.041258115022[/C][/ROW]
[ROW][C]47[/C][C]1159[/C][C]1121.09214750614[/C][C]37.9078524938625[/C][/ROW]
[ROW][C]48[/C][C]1209[/C][C]1124.76644821184[/C][C]84.2335517881563[/C][/ROW]
[ROW][C]49[/C][C]699[/C][C]638.42763830089[/C][C]60.5723616991103[/C][/ROW]
[ROW][C]50[/C][C]830[/C][C]908.01061953216[/C][C]-78.0106195321601[/C][/ROW]
[ROW][C]51[/C][C]996[/C][C]989.483222486196[/C][C]6.51677751380385[/C][/ROW]
[ROW][C]52[/C][C]1124[/C][C]1178.42304517839[/C][C]-54.4230451783903[/C][/ROW]
[ROW][C]53[/C][C]1458[/C][C]1375.45353777758[/C][C]82.5464622224167[/C][/ROW]
[ROW][C]54[/C][C]1270[/C][C]1505.99433837198[/C][C]-235.994338371978[/C][/ROW]
[ROW][C]55[/C][C]1753[/C][C]1717.65844816864[/C][C]35.3415518313609[/C][/ROW]
[ROW][C]56[/C][C]2258[/C][C]1723.28938701246[/C][C]534.710612987541[/C][/ROW]
[ROW][C]57[/C][C]1208[/C][C]1396.55030916633[/C][C]-188.550309166326[/C][/ROW]
[ROW][C]58[/C][C]1241[/C][C]1177.62476199254[/C][C]63.3752380074559[/C][/ROW]
[ROW][C]59[/C][C]1265[/C][C]1298.02429530364[/C][C]-33.0242953036384[/C][/ROW]
[ROW][C]60[/C][C]1828[/C][C]1305.41735025192[/C][C]522.582649748082[/C][/ROW]
[ROW][C]61[/C][C]809[/C][C]774.83266094363[/C][C]34.1673390563706[/C][/ROW]
[ROW][C]62[/C][C]997[/C][C]1039.36945363520[/C][C]-42.3694536352036[/C][/ROW]
[ROW][C]63[/C][C]1164[/C][C]1168.33975232397[/C][C]-4.33975232396506[/C][/ROW]
[ROW][C]64[/C][C]1205[/C][C]1367.08090456414[/C][C]-162.080904564136[/C][/ROW]
[ROW][C]65[/C][C]1538[/C][C]1626.2868854581[/C][C]-88.2868854581002[/C][/ROW]
[ROW][C]66[/C][C]1513[/C][C]1646.33742562572[/C][C]-133.337425625715[/C][/ROW]
[ROW][C]67[/C][C]1378[/C][C]1994.69039876606[/C][C]-616.690398766055[/C][/ROW]
[ROW][C]68[/C][C]2083[/C][C]2063.16936900672[/C][C]19.8306309932782[/C][/ROW]
[ROW][C]69[/C][C]1357[/C][C]1427.09831942623[/C][C]-70.0983194262324[/C][/ROW]
[ROW][C]70[/C][C]1536[/C][C]1284.01934919386[/C][C]251.980650806142[/C][/ROW]
[ROW][C]71[/C][C]1526[/C][C]1408.61492913749[/C][C]117.385070862512[/C][/ROW]
[ROW][C]72[/C][C]1376[/C][C]1600.33223898861[/C][C]-224.332238988606[/C][/ROW]
[ROW][C]73[/C][C]779[/C][C]810.845167194428[/C][C]-31.8451671944277[/C][/ROW]
[ROW][C]74[/C][C]1005[/C][C]1050.49573693738[/C][C]-45.4957369373781[/C][/ROW]
[ROW][C]75[/C][C]1193[/C][C]1192.70937440726[/C][C]0.290625592740071[/C][/ROW]
[ROW][C]76[/C][C]1522[/C][C]1350.22596016804[/C][C]171.774039831964[/C][/ROW]
[ROW][C]77[/C][C]1539[/C][C]1688.93680276946[/C][C]-149.936802769462[/C][/ROW]
[ROW][C]78[/C][C]1546[/C][C]1688.23615636363[/C][C]-142.236156363628[/C][/ROW]
[ROW][C]79[/C][C]2116[/C][C]1902.69253111387[/C][C]213.307468886131[/C][/ROW]
[ROW][C]80[/C][C]2326[/C][C]2290.59267200516[/C][C]35.4073279948379[/C][/ROW]
[ROW][C]81[/C][C]1596[/C][C]1558.17294232762[/C][C]37.8270576723808[/C][/ROW]
[ROW][C]82[/C][C]1356[/C][C]1511.12962890956[/C][C]-155.129628909558[/C][/ROW]
[ROW][C]83[/C][C]1553[/C][C]1548.21141631436[/C][C]4.78858368563692[/C][/ROW]
[ROW][C]84[/C][C]1613[/C][C]1632.52638986099[/C][C]-19.5263898609867[/C][/ROW]
[ROW][C]85[/C][C]814[/C][C]866.013219630146[/C][C]-52.0132196301461[/C][/ROW]
[ROW][C]86[/C][C]1150[/C][C]1117.02597020484[/C][C]32.9740297951616[/C][/ROW]
[ROW][C]87[/C][C]1225[/C][C]1295.3822019996[/C][C]-70.3822019995996[/C][/ROW]
[ROW][C]88[/C][C]1691[/C][C]1506.36868386985[/C][C]184.631316130150[/C][/ROW]
[ROW][C]89[/C][C]1759[/C][C]1772.35514762486[/C][C]-13.3551476248631[/C][/ROW]
[ROW][C]90[/C][C]1754[/C][C]1791.71838832041[/C][C]-37.718388320415[/C][/ROW]
[ROW][C]91[/C][C]2100[/C][C]2149.20213814788[/C][C]-49.202138147878[/C][/ROW]
[ROW][C]92[/C][C]2062[/C][C]2475.75202043459[/C][C]-413.75202043459[/C][/ROW]
[ROW][C]93[/C][C]2012[/C][C]1647.94559089079[/C][C]364.054409109214[/C][/ROW]
[ROW][C]94[/C][C]1897[/C][C]1579.19509767656[/C][C]317.804902323442[/C][/ROW]
[ROW][C]95[/C][C]1964[/C][C]1733.09269504805[/C][C]230.907304951946[/C][/ROW]
[ROW][C]96[/C][C]2186[/C][C]1848.74678049347[/C][C]337.25321950653[/C][/ROW]
[ROW][C]97[/C][C]966[/C][C]990.637162874265[/C][C]-24.6371628742654[/C][/ROW]
[ROW][C]98[/C][C]1549[/C][C]1315.29531853704[/C][C]233.704681462955[/C][/ROW]
[ROW][C]99[/C][C]1538[/C][C]1516.30565950867[/C][C]21.6943404913313[/C][/ROW]
[ROW][C]100[/C][C]1612[/C][C]1865.89816072850[/C][C]-253.898160728497[/C][/ROW]
[ROW][C]101[/C][C]2078[/C][C]2047.41388426638[/C][C]30.5861157336158[/C][/ROW]
[ROW][C]102[/C][C]2137[/C][C]2065.97205856532[/C][C]71.0279414346755[/C][/ROW]
[ROW][C]103[/C][C]2907[/C][C]2492.28903847496[/C][C]414.710961525036[/C][/ROW]
[ROW][C]104[/C][C]2249[/C][C]2815.40117186052[/C][C]-566.401171860515[/C][/ROW]
[ROW][C]105[/C][C]1883[/C][C]2075.63354545762[/C][C]-192.633545457625[/C][/ROW]
[ROW][C]106[/C][C]1739[/C][C]1899.78141450023[/C][C]-160.781414500229[/C][/ROW]
[ROW][C]107[/C][C]1828[/C][C]1973.93893170057[/C][C]-145.938931700572[/C][/ROW]
[ROW][C]108[/C][C]1868[/C][C]2075.68898702426[/C][C]-207.688987024259[/C][/ROW]
[ROW][C]109[/C][C]1138[/C][C]1014.12589478372[/C][C]123.874105216275[/C][/ROW]
[ROW][C]110[/C][C]1430[/C][C]1448.76050845518[/C][C]-18.7605084551751[/C][/ROW]
[ROW][C]111[/C][C]1809[/C][C]1560.14900034589[/C][C]248.850999654105[/C][/ROW]
[ROW][C]112[/C][C]1763[/C][C]1871.68832633665[/C][C]-108.688326336651[/C][/ROW]
[ROW][C]113[/C][C]2200[/C][C]2167.13957332622[/C][C]32.8604266737848[/C][/ROW]
[ROW][C]114[/C][C]2067[/C][C]2197.97278776171[/C][C]-130.972787761711[/C][/ROW]
[ROW][C]115[/C][C]2503[/C][C]2712.60059138710[/C][C]-209.600591387104[/C][/ROW]
[ROW][C]116[/C][C]2141[/C][C]2675.05191677941[/C][C]-534.051916779406[/C][/ROW]
[ROW][C]117[/C][C]2103[/C][C]2038.62262546849[/C][C]64.377374531513[/C][/ROW]
[ROW][C]118[/C][C]1972[/C][C]1900.48654221681[/C][C]71.5134577831939[/C][/ROW]
[ROW][C]119[/C][C]2181[/C][C]2011.98252307719[/C][C]169.017476922813[/C][/ROW]
[ROW][C]120[/C][C]2344[/C][C]2141.93416303978[/C][C]202.065836960222[/C][/ROW]
[ROW][C]121[/C][C]970[/C][C]1141.29282653254[/C][C]-171.292826532538[/C][/ROW]
[ROW][C]122[/C][C]1199[/C][C]1516.61682348787[/C][C]-317.616823487874[/C][/ROW]
[ROW][C]123[/C][C]1718[/C][C]1667.41007847986[/C][C]50.5899215201352[/C][/ROW]
[ROW][C]124[/C][C]1683[/C][C]1853.85438536200[/C][C]-170.854385361998[/C][/ROW]
[ROW][C]125[/C][C]2025[/C][C]2181.80535089781[/C][C]-156.805350897809[/C][/ROW]
[ROW][C]126[/C][C]2051[/C][C]2142.05746174646[/C][C]-91.0574617464604[/C][/ROW]
[ROW][C]127[/C][C]2439[/C][C]2635.84388087434[/C][C]-196.84388087434[/C][/ROW]
[ROW][C]128[/C][C]2353[/C][C]2505.50343662525[/C][C]-152.503436625251[/C][/ROW]
[ROW][C]129[/C][C]2230[/C][C]2081.28217536558[/C][C]148.717824634422[/C][/ROW]
[ROW][C]130[/C][C]1852[/C][C]1953.21950775809[/C][C]-101.219507758093[/C][/ROW]
[ROW][C]131[/C][C]2147[/C][C]2069.86037234918[/C][C]77.1396276508167[/C][/ROW]
[ROW][C]132[/C][C]2286[/C][C]2196.40493747476[/C][C]89.5950625252426[/C][/ROW]
[ROW][C]133[/C][C]1007[/C][C]1083.99651255359[/C][C]-76.9965125535855[/C][/ROW]
[ROW][C]134[/C][C]1665[/C][C]1428.83744025122[/C][C]236.16255974878[/C][/ROW]
[ROW][C]135[/C][C]1642[/C][C]1769.46825088515[/C][C]-127.468250885149[/C][/ROW]
[ROW][C]136[/C][C]1518[/C][C]1874.24915300942[/C][C]-356.24915300942[/C][/ROW]
[ROW][C]137[/C][C]1831[/C][C]2190.2679331991[/C][C]-359.267933199102[/C][/ROW]
[ROW][C]138[/C][C]2207[/C][C]2142.48916888812[/C][C]64.5108311118788[/C][/ROW]
[ROW][C]139[/C][C]2822[/C][C]2636.13763741813[/C][C]185.862362581871[/C][/ROW]
[ROW][C]140[/C][C]2393[/C][C]2562.88994936457[/C][C]-169.889949364575[/C][/ROW]
[ROW][C]141[/C][C]2306[/C][C]2207.28049642154[/C][C]98.7195035784575[/C][/ROW]
[ROW][C]142[/C][C]1785[/C][C]1994.05865432917[/C][C]-209.058654329167[/C][/ROW]
[ROW][C]143[/C][C]2047[/C][C]2151.59126451920[/C][C]-104.591264519196[/C][/ROW]
[ROW][C]144[/C][C]2171[/C][C]2259.86660013019[/C][C]-88.8666001301949[/C][/ROW]
[ROW][C]145[/C][C]1212[/C][C]1069.36234318583[/C][C]142.637656814169[/C][/ROW]
[ROW][C]146[/C][C]1335[/C][C]1543.63471134505[/C][C]-208.634711345049[/C][/ROW]
[ROW][C]147[/C][C]2011[/C][C]1723.1722805291[/C][C]287.827719470902[/C][/ROW]
[ROW][C]148[/C][C]1860[/C][C]1815.88330158162[/C][C]44.1166984183819[/C][/ROW]
[ROW][C]149[/C][C]1954[/C][C]2199.31242062952[/C][C]-245.312420629516[/C][/ROW]
[ROW][C]150[/C][C]2152[/C][C]2291.62126002699[/C][C]-139.621260026993[/C][/ROW]
[ROW][C]151[/C][C]2835[/C][C]2816.83716572309[/C][C]18.1628342769109[/C][/ROW]
[ROW][C]152[/C][C]2224[/C][C]2613.27011602859[/C][C]-389.270116028592[/C][/ROW]
[ROW][C]153[/C][C]2182[/C][C]2297.00876454059[/C][C]-115.008764540588[/C][/ROW]
[ROW][C]154[/C][C]1992[/C][C]1963.95558691649[/C][C]28.0444130835087[/C][/ROW]
[ROW][C]155[/C][C]2389[/C][C]2187.4827704661[/C][C]201.517229533898[/C][/ROW]
[ROW][C]156[/C][C]2724[/C][C]2345.20316503874[/C][C]378.79683496126[/C][/ROW]
[ROW][C]157[/C][C]891[/C][C]1193.38919948532[/C][C]-302.389199485323[/C][/ROW]
[ROW][C]158[/C][C]1247[/C][C]1518.69079291897[/C][C]-271.690792918967[/C][/ROW]
[ROW][C]159[/C][C]2017[/C][C]1833.62108883129[/C][C]183.378911168708[/C][/ROW]
[ROW][C]160[/C][C]2257[/C][C]1844.12159399804[/C][C]412.878406001957[/C][/ROW]
[ROW][C]161[/C][C]2255[/C][C]2202.66838186641[/C][C]52.3316181335927[/C][/ROW]
[ROW][C]162[/C][C]2255[/C][C]2370.2214183267[/C][C]-115.221418326702[/C][/ROW]
[ROW][C]163[/C][C]3057[/C][C]2973.89042768552[/C][C]83.1095723144804[/C][/ROW]
[ROW][C]164[/C][C]3330[/C][C]2643.08637504267[/C][C]686.91362495733[/C][/ROW]
[ROW][C]165[/C][C]1896[/C][C]2519.81158383102[/C][C]-623.81158383102[/C][/ROW]
[ROW][C]166[/C][C]2096[/C][C]2136.98116213232[/C][C]-40.9811621323188[/C][/ROW]
[ROW][C]167[/C][C]2374[/C][C]2419.93500335947[/C][C]-45.9350033594742[/C][/ROW]
[ROW][C]168[/C][C]2535[/C][C]2603.90129612003[/C][C]-68.9012961200287[/C][/ROW]
[ROW][C]169[/C][C]1041[/C][C]1147.16878251544[/C][C]-106.168782515444[/C][/ROW]
[ROW][C]170[/C][C]1728[/C][C]1526.39053984195[/C][C]201.609460158049[/C][/ROW]
[ROW][C]171[/C][C]2201[/C][C]2077.77000369211[/C][C]123.229996307889[/C][/ROW]
[ROW][C]172[/C][C]2455[/C][C]2145.41238810246[/C][C]309.587611897541[/C][/ROW]
[ROW][C]173[/C][C]2204[/C][C]2405.83168961193[/C][C]-201.831689611933[/C][/ROW]
[ROW][C]174[/C][C]2660[/C][C]2500.46608959121[/C][C]159.533910408795[/C][/ROW]
[ROW][C]175[/C][C]3670[/C][C]3251.46625919908[/C][C]418.533740800921[/C][/ROW]
[ROW][C]176[/C][C]2665[/C][C]3108.31874948913[/C][C]-443.318749489129[/C][/ROW]
[ROW][C]177[/C][C]2639[/C][C]2439.44977608105[/C][C]199.550223918949[/C][/ROW]
[ROW][C]178[/C][C]2226[/C][C]2313.34448108028[/C][C]-87.3444810802825[/C][/ROW]
[ROW][C]179[/C][C]2586[/C][C]2612.52680620413[/C][C]-26.526806204125[/C][/ROW]
[ROW][C]180[/C][C]2684[/C][C]2807.31910509382[/C][C]-123.319105093822[/C][/ROW]
[ROW][C]181[/C][C]1185[/C][C]1210.11578193156[/C][C]-25.1157819315579[/C][/ROW]
[ROW][C]182[/C][C]1749[/C][C]1729.34102376120[/C][C]19.6589762388023[/C][/ROW]
[ROW][C]183[/C][C]2459[/C][C]2272.62009321613[/C][C]186.379906783869[/C][/ROW]
[ROW][C]184[/C][C]2618[/C][C]2406.4619875861[/C][C]211.538012413898[/C][/ROW]
[ROW][C]185[/C][C]2585[/C][C]2514.64061854919[/C][C]70.3593814508117[/C][/ROW]
[ROW][C]186[/C][C]3310[/C][C]2763.70256109067[/C][C]546.297438909328[/C][/ROW]
[ROW][C]187[/C][C]3923[/C][C]3717.7065728895[/C][C]205.293427110496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77328&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77328&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
13530488.83695900046341.163040999537
14883814.76918013628568.230819863715
15894834.64924201163159.3507579883687
161045999.19216524897245.8078347510281
1711991167.6015349569231.3984650430839
1812871265.8749276645721.1250723354269
1915651471.6836405559193.3163594440866
2015771416.83455770272160.165442297285
2110761269.50663614626-193.506636146263
229181065.72885869940-147.728858699401
2310081084.2152672451-76.2152672451004
2410631035.0381755838027.9618244161961
25544582.173549598269-38.1735495982692
26635950.279703272534-315.279703272534
27804917.8820476586-113.882047658599
289801063.43198202462-83.4319820246214
2910181215.98034271037-197.980342710371
3010641282.32424149349-218.324241493494
3114041473.86706678750-69.8670667874956
3212861417.88509443065-131.885094430645
3311041147.80505570157-43.8050557015699
34999982.5233897030116.4766102969901
359961041.06932055722-45.0693205572168
3610151025.42181012321-10.4218101232145
37615559.2035589790555.7964410209495
38722857.541913373212-135.541913373212
39832905.609678642965-73.6096786429654
409771069.12052501393-92.1205250139342
4112701190.3251274667779.6748725332277
4214371289.52881127662147.471188723384
4315201593.65374322978-73.6537432297798
4417081511.62678785961196.373212140391
4511511278.03622592088-127.036225920883
469341101.04125811502-167.041258115022
4711591121.0921475061437.9078524938625
4812091124.7664482118484.2335517881563
49699638.4276383008960.5723616991103
50830908.01061953216-78.0106195321601
51996989.4832224861966.51677751380385
5211241178.42304517839-54.4230451783903
5314581375.4535377775882.5464622224167
5412701505.99433837198-235.994338371978
5517531717.6584481686435.3415518313609
5622581723.28938701246534.710612987541
5712081396.55030916633-188.550309166326
5812411177.6247619925463.3752380074559
5912651298.02429530364-33.0242953036384
6018281305.41735025192522.582649748082
61809774.8326609436334.1673390563706
629971039.36945363520-42.3694536352036
6311641168.33975232397-4.33975232396506
6412051367.08090456414-162.080904564136
6515381626.2868854581-88.2868854581002
6615131646.33742562572-133.337425625715
6713781994.69039876606-616.690398766055
6820832063.1693690067219.8306309932782
6913571427.09831942623-70.0983194262324
7015361284.01934919386251.980650806142
7115261408.61492913749117.385070862512
7213761600.33223898861-224.332238988606
73779810.845167194428-31.8451671944277
7410051050.49573693738-45.4957369373781
7511931192.709374407260.290625592740071
7615221350.22596016804171.774039831964
7715391688.93680276946-149.936802769462
7815461688.23615636363-142.236156363628
7921161902.69253111387213.307468886131
8023262290.5926720051635.4073279948379
8115961558.1729423276237.8270576723808
8213561511.12962890956-155.129628909558
8315531548.211416314364.78858368563692
8416131632.52638986099-19.5263898609867
85814866.013219630146-52.0132196301461
8611501117.0259702048432.9740297951616
8712251295.3822019996-70.3822019995996
8816911506.36868386985184.631316130150
8917591772.35514762486-13.3551476248631
9017541791.71838832041-37.718388320415
9121002149.20213814788-49.202138147878
9220622475.75202043459-413.75202043459
9320121647.94559089079364.054409109214
9418971579.19509767656317.804902323442
9519641733.09269504805230.907304951946
9621861848.74678049347337.25321950653
97966990.637162874265-24.6371628742654
9815491315.29531853704233.704681462955
9915381516.3056595086721.6943404913313
10016121865.89816072850-253.898160728497
10120782047.4138842663830.5861157336158
10221372065.9720585653271.0279414346755
10329072492.28903847496414.710961525036
10422492815.40117186052-566.401171860515
10518832075.63354545762-192.633545457625
10617391899.78141450023-160.781414500229
10718281973.93893170057-145.938931700572
10818682075.68898702426-207.688987024259
10911381014.12589478372123.874105216275
11014301448.76050845518-18.7605084551751
11118091560.14900034589248.850999654105
11217631871.68832633665-108.688326336651
11322002167.1395733262232.8604266737848
11420672197.97278776171-130.972787761711
11525032712.60059138710-209.600591387104
11621412675.05191677941-534.051916779406
11721032038.6226254684964.377374531513
11819721900.4865422168171.5134577831939
11921812011.98252307719169.017476922813
12023442141.93416303978202.065836960222
1219701141.29282653254-171.292826532538
12211991516.61682348787-317.616823487874
12317181667.4100784798650.5899215201352
12416831853.85438536200-170.854385361998
12520252181.80535089781-156.805350897809
12620512142.05746174646-91.0574617464604
12724392635.84388087434-196.84388087434
12823532505.50343662525-152.503436625251
12922302081.28217536558148.717824634422
13018521953.21950775809-101.219507758093
13121472069.8603723491877.1396276508167
13222862196.4049374747689.5950625252426
13310071083.99651255359-76.9965125535855
13416651428.83744025122236.16255974878
13516421769.46825088515-127.468250885149
13615181874.24915300942-356.24915300942
13718312190.2679331991-359.267933199102
13822072142.4891688881264.5108311118788
13928222636.13763741813185.862362581871
14023932562.88994936457-169.889949364575
14123062207.2804964215498.7195035784575
14217851994.05865432917-209.058654329167
14320472151.59126451920-104.591264519196
14421712259.86660013019-88.8666001301949
14512121069.36234318583142.637656814169
14613351543.63471134505-208.634711345049
14720111723.1722805291287.827719470902
14818601815.8833015816244.1166984183819
14919542199.31242062952-245.312420629516
15021522291.62126002699-139.621260026993
15128352816.8371657230918.1628342769109
15222242613.27011602859-389.270116028592
15321822297.00876454059-115.008764540588
15419921963.9555869164928.0444130835087
15523892187.4827704661201.517229533898
15627242345.20316503874378.79683496126
1578911193.38919948532-302.389199485323
15812471518.69079291897-271.690792918967
15920171833.62108883129183.378911168708
16022571844.12159399804412.878406001957
16122552202.6683818664152.3316181335927
16222552370.2214183267-115.221418326702
16330572973.8904276855283.1095723144804
16433302643.08637504267686.91362495733
16518962519.81158383102-623.81158383102
16620962136.98116213232-40.9811621323188
16723742419.93500335947-45.9350033594742
16825352603.90129612003-68.9012961200287
16910411147.16878251544-106.168782515444
17017281526.39053984195201.609460158049
17122012077.77000369211123.229996307889
17224552145.41238810246309.587611897541
17322042405.83168961193-201.831689611933
17426602500.46608959121159.533910408795
17536703251.46625919908418.533740800921
17626653108.31874948913-443.318749489129
17726392439.44977608105199.550223918949
17822262313.34448108028-87.3444810802825
17925862612.52680620413-26.526806204125
18026842807.31910509382-123.319105093822
18111851210.11578193156-25.1157819315579
18217491729.3410237612019.6589762388023
18324592272.62009321613186.379906783869
18426182406.4619875861211.538012413898
18525852514.6406185491970.3593814508117
18633102763.70256109067546.297438909328
18739233717.7065728895205.293427110496







Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
1883260.02873534973093.573349242663426.48412145673
1892777.935692564812605.634356102492950.23702902713
1902520.714213099912343.029053724572698.39937247526
1912882.031064138252691.535115777363072.52701249914
1923070.015375190072868.842728025853271.18802235429
1931339.166896369851164.130499484551514.20329325516
1941935.492876539041736.788474493152134.19727858494
1952588.331217896242357.03501925072819.62741654178
1962715.311913395442472.630231855792957.99359493509
1972759.205251370232509.197648878463009.21285386200
1983159.387086232222882.637872936613436.13629952782
1993991.070263793193704.34959518944277.79093239699

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
188 & 3260.0287353497 & 3093.57334924266 & 3426.48412145673 \tabularnewline
189 & 2777.93569256481 & 2605.63435610249 & 2950.23702902713 \tabularnewline
190 & 2520.71421309991 & 2343.02905372457 & 2698.39937247526 \tabularnewline
191 & 2882.03106413825 & 2691.53511577736 & 3072.52701249914 \tabularnewline
192 & 3070.01537519007 & 2868.84272802585 & 3271.18802235429 \tabularnewline
193 & 1339.16689636985 & 1164.13049948455 & 1514.20329325516 \tabularnewline
194 & 1935.49287653904 & 1736.78847449315 & 2134.19727858494 \tabularnewline
195 & 2588.33121789624 & 2357.0350192507 & 2819.62741654178 \tabularnewline
196 & 2715.31191339544 & 2472.63023185579 & 2957.99359493509 \tabularnewline
197 & 2759.20525137023 & 2509.19764887846 & 3009.21285386200 \tabularnewline
198 & 3159.38708623222 & 2882.63787293661 & 3436.13629952782 \tabularnewline
199 & 3991.07026379319 & 3704.3495951894 & 4277.79093239699 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77328&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]3260.0287353497[/C][C]3093.57334924266[/C][C]3426.48412145673[/C][/ROW]
[ROW][C]189[/C][C]2777.93569256481[/C][C]2605.63435610249[/C][C]2950.23702902713[/C][/ROW]
[ROW][C]190[/C][C]2520.71421309991[/C][C]2343.02905372457[/C][C]2698.39937247526[/C][/ROW]
[ROW][C]191[/C][C]2882.03106413825[/C][C]2691.53511577736[/C][C]3072.52701249914[/C][/ROW]
[ROW][C]192[/C][C]3070.01537519007[/C][C]2868.84272802585[/C][C]3271.18802235429[/C][/ROW]
[ROW][C]193[/C][C]1339.16689636985[/C][C]1164.13049948455[/C][C]1514.20329325516[/C][/ROW]
[ROW][C]194[/C][C]1935.49287653904[/C][C]1736.78847449315[/C][C]2134.19727858494[/C][/ROW]
[ROW][C]195[/C][C]2588.33121789624[/C][C]2357.0350192507[/C][C]2819.62741654178[/C][/ROW]
[ROW][C]196[/C][C]2715.31191339544[/C][C]2472.63023185579[/C][C]2957.99359493509[/C][/ROW]
[ROW][C]197[/C][C]2759.20525137023[/C][C]2509.19764887846[/C][C]3009.21285386200[/C][/ROW]
[ROW][C]198[/C][C]3159.38708623222[/C][C]2882.63787293661[/C][C]3436.13629952782[/C][/ROW]
[ROW][C]199[/C][C]3991.07026379319[/C][C]3704.3495951894[/C][C]4277.79093239699[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77328&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77328&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
1883260.02873534973093.573349242663426.48412145673
1892777.935692564812605.634356102492950.23702902713
1902520.714213099912343.029053724572698.39937247526
1912882.031064138252691.535115777363072.52701249914
1923070.015375190072868.842728025853271.18802235429
1931339.166896369851164.130499484551514.20329325516
1941935.492876539041736.788474493152134.19727858494
1952588.331217896242357.03501925072819.62741654178
1962715.311913395442472.630231855792957.99359493509
1972759.205251370232509.197648878463009.21285386200
1983159.387086232222882.637872936613436.13629952782
1993991.070263793193704.34959518944277.79093239699



Parameters (Session):
par1 = 12 ; par2 = Triple ; par3 = multiplicative ;
Parameters (R input):
par1 = 12 ; par2 = Triple ; par3 = multiplicative ;
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')