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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationMon, 23 Jan 2017 10:43:53 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Jan/23/t148516465805m5pnpy3tixhpx.htm/, Retrieved Thu, 31 Oct 2024 23:52:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=304608, Retrieved Thu, 31 Oct 2024 23:52:41 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Exponential Smoothing] [Exponential Smoot...] [2017-01-23 09:43:53] [3c8d1d1050061614560bf423eb580e6a] [Current]
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Dataseries X:
3035
2552
2704
2554
2014
1655
1721
1524
1596
2074
2199
2512
2933
2889
2938
2497
1870
1726
1607
1545
1396
1787
2076
2837
2787
3891
3179
2011
1636
1580
1489
1300
1356
1653
2013
2823
3102
2294
2385
2444
1748
1554
1498
1361
1346
1564
1640
2293
2815
3137
2679
1969
1870
1633
1529
1366
1357
1570
1535
2491
3084
2605
2573
2143
1693
1504
1461
1354
1333
1492
1781
1915




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304608&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=304608&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304608&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.00527852028951625
beta0.492309095625266
gamma0.108572443357086

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.00527852028951625 \tabularnewline
beta & 0.492309095625266 \tabularnewline
gamma & 0.108572443357086 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304608&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]0.00527852028951625[/C][/ROW]
[ROW][C]beta[/C][C]0.492309095625266[/C][/ROW]
[ROW][C]gamma[/C][C]0.108572443357086[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304608&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304608&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
alpha0.00527852028951625
beta0.492309095625266
gamma0.108572443357086







Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
1329332918.1850961538514.8149038461534
1428892875.28329354413.7167064559953
1529382928.994672515389.00532748461728
1624972505.53791752689-8.53791752689267
1718701892.75803965526-22.7580396552603
1817261737.34396009234-11.3439600923352
1916071716.83565084436-109.835650844363
2015451506.2720253060738.727974693928
2113961551.59323685567-155.59323685567
2217872017.90105214085-230.901052140847
2320762145.96131944723-69.9613194472345
2428372457.35597113394379.644028866055
2527872880.46044073373-93.4604407337274
2638912836.189475429371054.81052457063
2731792896.91389147735282.086108522645
2820112475.74001315583-464.740013155829
2916361860.56685681569-224.56685681569
3015801706.3463625518-126.346362551796
3114891675.32124465031-186.321244650307
3213001480.92717336612-180.927173366121
3313561504.0600693261-148.060069326104
3416531962.25173175058-309.251731750579
3520132107.0534791269-94.053479126901
3628232466.58910456874356.410895431258
3731022838.12665447289263.873345527108
3822942920.33366927885-626.33366927885
3923852884.94095368707-499.940953687069
4024442373.1607252643270.8392747356766
4117481782.3232931479-34.3232931479042
4215541635.77924646514-81.7792464651397
4314981594.69243852325-96.6924385232455
4413611397.76725527598-36.76725527598
4513461421.99857542526-75.9985754252632
4615641860.13713362889-296.137133628885
4716402025.25856780403-385.258567804028
4822932428.1593646029-135.159364602903
4928152782.0831782431232.916821756879
5031372761.30415642621375.695843573789
5126792741.82978505779-62.8297850577883
5219692292.11543153957-323.115431539573
5318701684.93194360872185.068056391284
5416331532.0818013889100.918198611101
5515291488.484574368940.5154256310973
5613661297.2479066958368.7520933041719
5713571316.5658461584240.4341538415831
5815701730.61333708168-160.613337081683
5915351886.24642043456-351.246420434563
6024912315.84702670289175.152973297107
6130842689.8770715282394.122928471803
6226052709.27936902086-104.279369020859
6325732639.91844244236-66.9184424423552
6421432162.06868620961-19.0686862096086
6516931612.1605702227680.839429777239
6615041450.1882436872353.8117563127662
6714611400.212608687160.7873913129031
6813541212.5788725683141.421127431697
6913331229.85730461416103.142695385844
7014921623.32099204227-131.320992042268
7117811759.3947539379321.6052460620701
7219152249.65747500109-334.657475001085

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
13 & 2933 & 2918.18509615385 & 14.8149038461534 \tabularnewline
14 & 2889 & 2875.283293544 & 13.7167064559953 \tabularnewline
15 & 2938 & 2928.99467251538 & 9.00532748461728 \tabularnewline
16 & 2497 & 2505.53791752689 & -8.53791752689267 \tabularnewline
17 & 1870 & 1892.75803965526 & -22.7580396552603 \tabularnewline
18 & 1726 & 1737.34396009234 & -11.3439600923352 \tabularnewline
19 & 1607 & 1716.83565084436 & -109.835650844363 \tabularnewline
20 & 1545 & 1506.27202530607 & 38.727974693928 \tabularnewline
21 & 1396 & 1551.59323685567 & -155.59323685567 \tabularnewline
22 & 1787 & 2017.90105214085 & -230.901052140847 \tabularnewline
23 & 2076 & 2145.96131944723 & -69.9613194472345 \tabularnewline
24 & 2837 & 2457.35597113394 & 379.644028866055 \tabularnewline
25 & 2787 & 2880.46044073373 & -93.4604407337274 \tabularnewline
26 & 3891 & 2836.18947542937 & 1054.81052457063 \tabularnewline
27 & 3179 & 2896.91389147735 & 282.086108522645 \tabularnewline
28 & 2011 & 2475.74001315583 & -464.740013155829 \tabularnewline
29 & 1636 & 1860.56685681569 & -224.56685681569 \tabularnewline
30 & 1580 & 1706.3463625518 & -126.346362551796 \tabularnewline
31 & 1489 & 1675.32124465031 & -186.321244650307 \tabularnewline
32 & 1300 & 1480.92717336612 & -180.927173366121 \tabularnewline
33 & 1356 & 1504.0600693261 & -148.060069326104 \tabularnewline
34 & 1653 & 1962.25173175058 & -309.251731750579 \tabularnewline
35 & 2013 & 2107.0534791269 & -94.053479126901 \tabularnewline
36 & 2823 & 2466.58910456874 & 356.410895431258 \tabularnewline
37 & 3102 & 2838.12665447289 & 263.873345527108 \tabularnewline
38 & 2294 & 2920.33366927885 & -626.33366927885 \tabularnewline
39 & 2385 & 2884.94095368707 & -499.940953687069 \tabularnewline
40 & 2444 & 2373.16072526432 & 70.8392747356766 \tabularnewline
41 & 1748 & 1782.3232931479 & -34.3232931479042 \tabularnewline
42 & 1554 & 1635.77924646514 & -81.7792464651397 \tabularnewline
43 & 1498 & 1594.69243852325 & -96.6924385232455 \tabularnewline
44 & 1361 & 1397.76725527598 & -36.76725527598 \tabularnewline
45 & 1346 & 1421.99857542526 & -75.9985754252632 \tabularnewline
46 & 1564 & 1860.13713362889 & -296.137133628885 \tabularnewline
47 & 1640 & 2025.25856780403 & -385.258567804028 \tabularnewline
48 & 2293 & 2428.1593646029 & -135.159364602903 \tabularnewline
49 & 2815 & 2782.08317824312 & 32.916821756879 \tabularnewline
50 & 3137 & 2761.30415642621 & 375.695843573789 \tabularnewline
51 & 2679 & 2741.82978505779 & -62.8297850577883 \tabularnewline
52 & 1969 & 2292.11543153957 & -323.115431539573 \tabularnewline
53 & 1870 & 1684.93194360872 & 185.068056391284 \tabularnewline
54 & 1633 & 1532.0818013889 & 100.918198611101 \tabularnewline
55 & 1529 & 1488.4845743689 & 40.5154256310973 \tabularnewline
56 & 1366 & 1297.24790669583 & 68.7520933041719 \tabularnewline
57 & 1357 & 1316.56584615842 & 40.4341538415831 \tabularnewline
58 & 1570 & 1730.61333708168 & -160.613337081683 \tabularnewline
59 & 1535 & 1886.24642043456 & -351.246420434563 \tabularnewline
60 & 2491 & 2315.84702670289 & 175.152973297107 \tabularnewline
61 & 3084 & 2689.8770715282 & 394.122928471803 \tabularnewline
62 & 2605 & 2709.27936902086 & -104.279369020859 \tabularnewline
63 & 2573 & 2639.91844244236 & -66.9184424423552 \tabularnewline
64 & 2143 & 2162.06868620961 & -19.0686862096086 \tabularnewline
65 & 1693 & 1612.16057022276 & 80.839429777239 \tabularnewline
66 & 1504 & 1450.18824368723 & 53.8117563127662 \tabularnewline
67 & 1461 & 1400.2126086871 & 60.7873913129031 \tabularnewline
68 & 1354 & 1212.5788725683 & 141.421127431697 \tabularnewline
69 & 1333 & 1229.85730461416 & 103.142695385844 \tabularnewline
70 & 1492 & 1623.32099204227 & -131.320992042268 \tabularnewline
71 & 1781 & 1759.39475393793 & 21.6052460620701 \tabularnewline
72 & 1915 & 2249.65747500109 & -334.657475001085 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304608&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]2933[/C][C]2918.18509615385[/C][C]14.8149038461534[/C][/ROW]
[ROW][C]14[/C][C]2889[/C][C]2875.283293544[/C][C]13.7167064559953[/C][/ROW]
[ROW][C]15[/C][C]2938[/C][C]2928.99467251538[/C][C]9.00532748461728[/C][/ROW]
[ROW][C]16[/C][C]2497[/C][C]2505.53791752689[/C][C]-8.53791752689267[/C][/ROW]
[ROW][C]17[/C][C]1870[/C][C]1892.75803965526[/C][C]-22.7580396552603[/C][/ROW]
[ROW][C]18[/C][C]1726[/C][C]1737.34396009234[/C][C]-11.3439600923352[/C][/ROW]
[ROW][C]19[/C][C]1607[/C][C]1716.83565084436[/C][C]-109.835650844363[/C][/ROW]
[ROW][C]20[/C][C]1545[/C][C]1506.27202530607[/C][C]38.727974693928[/C][/ROW]
[ROW][C]21[/C][C]1396[/C][C]1551.59323685567[/C][C]-155.59323685567[/C][/ROW]
[ROW][C]22[/C][C]1787[/C][C]2017.90105214085[/C][C]-230.901052140847[/C][/ROW]
[ROW][C]23[/C][C]2076[/C][C]2145.96131944723[/C][C]-69.9613194472345[/C][/ROW]
[ROW][C]24[/C][C]2837[/C][C]2457.35597113394[/C][C]379.644028866055[/C][/ROW]
[ROW][C]25[/C][C]2787[/C][C]2880.46044073373[/C][C]-93.4604407337274[/C][/ROW]
[ROW][C]26[/C][C]3891[/C][C]2836.18947542937[/C][C]1054.81052457063[/C][/ROW]
[ROW][C]27[/C][C]3179[/C][C]2896.91389147735[/C][C]282.086108522645[/C][/ROW]
[ROW][C]28[/C][C]2011[/C][C]2475.74001315583[/C][C]-464.740013155829[/C][/ROW]
[ROW][C]29[/C][C]1636[/C][C]1860.56685681569[/C][C]-224.56685681569[/C][/ROW]
[ROW][C]30[/C][C]1580[/C][C]1706.3463625518[/C][C]-126.346362551796[/C][/ROW]
[ROW][C]31[/C][C]1489[/C][C]1675.32124465031[/C][C]-186.321244650307[/C][/ROW]
[ROW][C]32[/C][C]1300[/C][C]1480.92717336612[/C][C]-180.927173366121[/C][/ROW]
[ROW][C]33[/C][C]1356[/C][C]1504.0600693261[/C][C]-148.060069326104[/C][/ROW]
[ROW][C]34[/C][C]1653[/C][C]1962.25173175058[/C][C]-309.251731750579[/C][/ROW]
[ROW][C]35[/C][C]2013[/C][C]2107.0534791269[/C][C]-94.053479126901[/C][/ROW]
[ROW][C]36[/C][C]2823[/C][C]2466.58910456874[/C][C]356.410895431258[/C][/ROW]
[ROW][C]37[/C][C]3102[/C][C]2838.12665447289[/C][C]263.873345527108[/C][/ROW]
[ROW][C]38[/C][C]2294[/C][C]2920.33366927885[/C][C]-626.33366927885[/C][/ROW]
[ROW][C]39[/C][C]2385[/C][C]2884.94095368707[/C][C]-499.940953687069[/C][/ROW]
[ROW][C]40[/C][C]2444[/C][C]2373.16072526432[/C][C]70.8392747356766[/C][/ROW]
[ROW][C]41[/C][C]1748[/C][C]1782.3232931479[/C][C]-34.3232931479042[/C][/ROW]
[ROW][C]42[/C][C]1554[/C][C]1635.77924646514[/C][C]-81.7792464651397[/C][/ROW]
[ROW][C]43[/C][C]1498[/C][C]1594.69243852325[/C][C]-96.6924385232455[/C][/ROW]
[ROW][C]44[/C][C]1361[/C][C]1397.76725527598[/C][C]-36.76725527598[/C][/ROW]
[ROW][C]45[/C][C]1346[/C][C]1421.99857542526[/C][C]-75.9985754252632[/C][/ROW]
[ROW][C]46[/C][C]1564[/C][C]1860.13713362889[/C][C]-296.137133628885[/C][/ROW]
[ROW][C]47[/C][C]1640[/C][C]2025.25856780403[/C][C]-385.258567804028[/C][/ROW]
[ROW][C]48[/C][C]2293[/C][C]2428.1593646029[/C][C]-135.159364602903[/C][/ROW]
[ROW][C]49[/C][C]2815[/C][C]2782.08317824312[/C][C]32.916821756879[/C][/ROW]
[ROW][C]50[/C][C]3137[/C][C]2761.30415642621[/C][C]375.695843573789[/C][/ROW]
[ROW][C]51[/C][C]2679[/C][C]2741.82978505779[/C][C]-62.8297850577883[/C][/ROW]
[ROW][C]52[/C][C]1969[/C][C]2292.11543153957[/C][C]-323.115431539573[/C][/ROW]
[ROW][C]53[/C][C]1870[/C][C]1684.93194360872[/C][C]185.068056391284[/C][/ROW]
[ROW][C]54[/C][C]1633[/C][C]1532.0818013889[/C][C]100.918198611101[/C][/ROW]
[ROW][C]55[/C][C]1529[/C][C]1488.4845743689[/C][C]40.5154256310973[/C][/ROW]
[ROW][C]56[/C][C]1366[/C][C]1297.24790669583[/C][C]68.7520933041719[/C][/ROW]
[ROW][C]57[/C][C]1357[/C][C]1316.56584615842[/C][C]40.4341538415831[/C][/ROW]
[ROW][C]58[/C][C]1570[/C][C]1730.61333708168[/C][C]-160.613337081683[/C][/ROW]
[ROW][C]59[/C][C]1535[/C][C]1886.24642043456[/C][C]-351.246420434563[/C][/ROW]
[ROW][C]60[/C][C]2491[/C][C]2315.84702670289[/C][C]175.152973297107[/C][/ROW]
[ROW][C]61[/C][C]3084[/C][C]2689.8770715282[/C][C]394.122928471803[/C][/ROW]
[ROW][C]62[/C][C]2605[/C][C]2709.27936902086[/C][C]-104.279369020859[/C][/ROW]
[ROW][C]63[/C][C]2573[/C][C]2639.91844244236[/C][C]-66.9184424423552[/C][/ROW]
[ROW][C]64[/C][C]2143[/C][C]2162.06868620961[/C][C]-19.0686862096086[/C][/ROW]
[ROW][C]65[/C][C]1693[/C][C]1612.16057022276[/C][C]80.839429777239[/C][/ROW]
[ROW][C]66[/C][C]1504[/C][C]1450.18824368723[/C][C]53.8117563127662[/C][/ROW]
[ROW][C]67[/C][C]1461[/C][C]1400.2126086871[/C][C]60.7873913129031[/C][/ROW]
[ROW][C]68[/C][C]1354[/C][C]1212.5788725683[/C][C]141.421127431697[/C][/ROW]
[ROW][C]69[/C][C]1333[/C][C]1229.85730461416[/C][C]103.142695385844[/C][/ROW]
[ROW][C]70[/C][C]1492[/C][C]1623.32099204227[/C][C]-131.320992042268[/C][/ROW]
[ROW][C]71[/C][C]1781[/C][C]1759.39475393793[/C][C]21.6052460620701[/C][/ROW]
[ROW][C]72[/C][C]1915[/C][C]2249.65747500109[/C][C]-334.657475001085[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304608&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304608&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
1329332918.1850961538514.8149038461534
1428892875.28329354413.7167064559953
1529382928.994672515389.00532748461728
1624972505.53791752689-8.53791752689267
1718701892.75803965526-22.7580396552603
1817261737.34396009234-11.3439600923352
1916071716.83565084436-109.835650844363
2015451506.2720253060738.727974693928
2113961551.59323685567-155.59323685567
2217872017.90105214085-230.901052140847
2320762145.96131944723-69.9613194472345
2428372457.35597113394379.644028866055
2527872880.46044073373-93.4604407337274
2638912836.189475429371054.81052457063
2731792896.91389147735282.086108522645
2820112475.74001315583-464.740013155829
2916361860.56685681569-224.56685681569
3015801706.3463625518-126.346362551796
3114891675.32124465031-186.321244650307
3213001480.92717336612-180.927173366121
3313561504.0600693261-148.060069326104
3416531962.25173175058-309.251731750579
3520132107.0534791269-94.053479126901
3628232466.58910456874356.410895431258
3731022838.12665447289263.873345527108
3822942920.33366927885-626.33366927885
3923852884.94095368707-499.940953687069
4024442373.1607252643270.8392747356766
4117481782.3232931479-34.3232931479042
4215541635.77924646514-81.7792464651397
4314981594.69243852325-96.6924385232455
4413611397.76725527598-36.76725527598
4513461421.99857542526-75.9985754252632
4615641860.13713362889-296.137133628885
4716402025.25856780403-385.258567804028
4822932428.1593646029-135.159364602903
4928152782.0831782431232.916821756879
5031372761.30415642621375.695843573789
5126792741.82978505779-62.8297850577883
5219692292.11543153957-323.115431539573
5318701684.93194360872185.068056391284
5416331532.0818013889100.918198611101
5515291488.484574368940.5154256310973
5613661297.2479066958368.7520933041719
5713571316.5658461584240.4341538415831
5815701730.61333708168-160.613337081683
5915351886.24642043456-351.246420434563
6024912315.84702670289175.152973297107
6130842689.8770715282394.122928471803
6226052709.27936902086-104.279369020859
6325732639.91844244236-66.9184424423552
6421432162.06868620961-19.0686862096086
6516931612.1605702227680.839429777239
6615041450.1882436872353.8117563127662
6714611400.212608687160.7873913129031
6813541212.5788725683141.421127431697
6913331229.85730461416103.142695385844
7014921623.32099204227-131.320992042268
7117811759.3947539379321.6052460620701
7219152249.65747500109-334.657475001085







Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
732645.163481984562147.207851945643143.11911202347
742608.152476760592110.181397881623106.12355563957
752543.142136506412045.143735558053041.14053745477
762070.752441402091572.711484953482568.7933978507
771531.723632307971033.621529089812029.82573552614
781366.18418949325867.9989938997341864.36938508678
791316.3166006104818.0230175632861814.61018365752
801136.55115001774638.1205414135071634.98175862198
811148.06229898902649.4626919468331646.6619060312
821514.504845264171015.700942388382013.30874813997
831666.974203279361167.927395144892166.02101141382
842117.777079150731618.445459213712617.10869908775

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
73 & 2645.16348198456 & 2147.20785194564 & 3143.11911202347 \tabularnewline
74 & 2608.15247676059 & 2110.18139788162 & 3106.12355563957 \tabularnewline
75 & 2543.14213650641 & 2045.14373555805 & 3041.14053745477 \tabularnewline
76 & 2070.75244140209 & 1572.71148495348 & 2568.7933978507 \tabularnewline
77 & 1531.72363230797 & 1033.62152908981 & 2029.82573552614 \tabularnewline
78 & 1366.18418949325 & 867.998993899734 & 1864.36938508678 \tabularnewline
79 & 1316.3166006104 & 818.023017563286 & 1814.61018365752 \tabularnewline
80 & 1136.55115001774 & 638.120541413507 & 1634.98175862198 \tabularnewline
81 & 1148.06229898902 & 649.462691946833 & 1646.6619060312 \tabularnewline
82 & 1514.50484526417 & 1015.70094238838 & 2013.30874813997 \tabularnewline
83 & 1666.97420327936 & 1167.92739514489 & 2166.02101141382 \tabularnewline
84 & 2117.77707915073 & 1618.44545921371 & 2617.10869908775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304608&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]73[/C][C]2645.16348198456[/C][C]2147.20785194564[/C][C]3143.11911202347[/C][/ROW]
[ROW][C]74[/C][C]2608.15247676059[/C][C]2110.18139788162[/C][C]3106.12355563957[/C][/ROW]
[ROW][C]75[/C][C]2543.14213650641[/C][C]2045.14373555805[/C][C]3041.14053745477[/C][/ROW]
[ROW][C]76[/C][C]2070.75244140209[/C][C]1572.71148495348[/C][C]2568.7933978507[/C][/ROW]
[ROW][C]77[/C][C]1531.72363230797[/C][C]1033.62152908981[/C][C]2029.82573552614[/C][/ROW]
[ROW][C]78[/C][C]1366.18418949325[/C][C]867.998993899734[/C][C]1864.36938508678[/C][/ROW]
[ROW][C]79[/C][C]1316.3166006104[/C][C]818.023017563286[/C][C]1814.61018365752[/C][/ROW]
[ROW][C]80[/C][C]1136.55115001774[/C][C]638.120541413507[/C][C]1634.98175862198[/C][/ROW]
[ROW][C]81[/C][C]1148.06229898902[/C][C]649.462691946833[/C][C]1646.6619060312[/C][/ROW]
[ROW][C]82[/C][C]1514.50484526417[/C][C]1015.70094238838[/C][C]2013.30874813997[/C][/ROW]
[ROW][C]83[/C][C]1666.97420327936[/C][C]1167.92739514489[/C][C]2166.02101141382[/C][/ROW]
[ROW][C]84[/C][C]2117.77707915073[/C][C]1618.44545921371[/C][C]2617.10869908775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304608&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304608&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
732645.163481984562147.207851945643143.11911202347
742608.152476760592110.181397881623106.12355563957
752543.142136506412045.143735558053041.14053745477
762070.752441402091572.711484953482568.7933978507
771531.723632307971033.621529089812029.82573552614
781366.18418949325867.9989938997341864.36938508678
791316.3166006104818.0230175632861814.61018365752
801136.55115001774638.1205414135071634.98175862198
811148.06229898902649.4626919468331646.6619060312
821514.504845264171015.700942388382013.30874813997
831666.974203279361167.927395144892166.02101141382
842117.777079150731618.445459213712617.10869908775



Parameters (Session):
Parameters (R input):
par1 = 12 ; par2 = Triple ; par3 = additive ; par4 = 12 ;
R code (references can be found in the software module):
par4 <- '12'
par3 <- 'additive'
par2 <- 'Double'
par1 <- '12'
par1 <- as.numeric(par1)
par4 <- as.numeric(par4)
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$fitted[,'xhat']
bitmap(file='test1.png')
op <- par(mfrow=c(2,1))
plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing')
plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors')
par(op)
dev.off()
bitmap(file='test2.png')
p <- predict(fit, par4, prediction.interval=TRUE)
np <- length(p[,1])
plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing')
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF')
spectrum(myresid,main='Residals Periodogram')
cpgram(myresid,main='Residal Cumulative Periodogram')
qqnorm(myresid,main='Residual Normal QQ Plot')
qqline(myresid)
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,fit$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')