Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationFri, 12 Aug 2011 12:10:42 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Aug/12/t1313165501m2x5pqehhqsl4ne.htm/, Retrieved Thu, 31 Oct 2024 22:58:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=123653, Retrieved Thu, 31 Oct 2024 22:58:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsMorel Sarah
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Exponential Smoothing] [exponential smoot...] [2011-08-12 16:10:42] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
588264
577918
567562
546859
756344
745987
588264
483527
493873
493873
504229
526055
462824
399492
347630
347630
546859
567562
409838
231412
325803
325803
399492
442021
431664
325803
378790
357986
536412
493873
325803
200263
315447
347630
378790
420195
336150
263595
294755
305101
577918
577918
420195
399492
462824
431664
515709
620447
641250
493873
452367
409838
694135
714939
661953
714939
704481
620447
714939
819676
862205
735641
651596
714939
987746
1071790
1051088
1092483
1082137
977399
1155825
1198354
1260562
1071790
998102
1082137
1282389
1460814
1418286
1418286
1439089
1366423
1555307
1555307
1523124
1344597
1376780
1397583
1534503
1712929
1586355
1649698
1596712
1565653
1807421
1754435
1680746
1576009
1680746
1733732
1796963
1880998
1796963
1848826
1785585
1775239
2037699
2059525
1975491
1828123
1953664
2006549
2069882
2164273
2069882
2143570
2111388
1996193
2237951
2237951




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net

\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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123653&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123653&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123653&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'George Udny Yule' @ yule.wessa.net







Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.999952902001476
betaFALSE
gammaFALSE

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.999952902001476 \tabularnewline
beta & FALSE \tabularnewline
gamma & FALSE \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123653&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]0.999952902001476[/C][/ROW]
[ROW][C]beta[/C][C]FALSE[/C][/ROW]
[ROW][C]gamma[/C][C]FALSE[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123653&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123653&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
alpha0.999952902001476
betaFALSE
gammaFALSE







Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
2577918588264-10346
3567562577918.487275893-10356.4872758928
4546859567562.487769822-20703.4877698225
5756344546859.975092836209484.024907164
6745987756334.133721704-10347.1337217042
7588264745987.487329289-157723.487329289
8483527588271.428460573-104744.428460573
9493873483531.93325293710341.066747063
10493873493872.5129564540.487043546396308
11504229493872.99997706110356.0000229388
12526055504228.51225312621826.4877468738
13462824526053.972016112-63229.9720161123
14399492462826.978005129-63334.9780051287
15347630399494.982950701-51864.9829507006
16347630347632.44273689-2.44273689045804
17546859347630.000115048199228.999884952
18567562546849.61671285820712.3832871425
19409838567561.024488203-157723.024488203
20231412409845.428438774-178433.428438774
21325803231420.40385734994382.5961426508
22325803325798.5547686264.44523137377109
23399492325802.99979063973689.0002093615
24442021399488.52939557742532.4706044231
25431664442018.996805762-10354.9968057623
26325803431664.487699624-105861.487699624
27378790325807.98586419152982.0141358086
28357986378787.504653176-20801.5046531765
29536412357986.979709235178425.020290765
30493873536403.596538658-42530.5965386578
31325803493875.003105973-168072.003105973
32200263325810.915854954-125547.915854954
33315447200268.913055556115178.086944444
34347630315441.57534263132188.4246573689
35378790347628.48398962331161.516010377
36420195378788.53235496541406.4676450351
37336150420193.049838248-84043.049838248
38263595336153.958259437-72558.9582594372
39294755263598.41738170931156.582618291
40305101294753.53258731810347.4674126821
41577918305100.512654995272817.487345005
42577918577905.15084238412.8491576161468
43420195577917.99939483-157722.99939483
44399492420202.428437593-20710.4284375926
45462824399492.97541972863331.024580272
46431664462821.017235498-31157.0172354978
47515709431665.46743315284043.5325668483
48620447515705.041717827104741.958282173
49641250620442.06686340320807.9331365966
50493873641249.019987996-147376.019987996
51452367493879.941115572-41512.9411155718
52409838452368.955176439-42530.9551764394
53694135409840.003122864284294.996877136
54714939694121.61027465720817.3897253432
55661953714938.019542609-52985.0195426095
56714939661955.49548837252983.5045116278
57704481714936.504582983-10455.5045829827
58620447704481.492433339-84034.4924333394
59714939620450.957856494488.0421435995
60819676714934.549802331104741.450197669
61862205819671.06688733342533.9331126668
62735641862202.996736881-126561.996736881
63651596735646.960816736-84050.9608167355
64714939651599.95863202863339.0413679716
65987746714936.016857923272809.983142077
661071790987733.15119581784056.8488041833
6710510881071786.04109066-20698.0410906591
6810924831051088.9748363141394.0251636913
6910821371092481.05042426-10344.050424264
709773991082137.48718407-104738.487184072
711155825977403.932973115178421.067026885
7211983541155816.5967248542537.4032751515
7312605621198351.9965734462210.0034265567
7410717901260559.07003335-188769.07003335
759981021071798.89064538-73696.8906453818
761082137998105.47097604784031.5290239531
7712823891082133.04228317200255.95771683
7814608141282379.5683452178434.431654801
7914182861460805.5960954-42519.5960954013
8014182861418288.00258787-2.00258787418716
8114390891418286.0000943220802.9999056822
8213664231439088.02022034-72665.0202203412
8315553071366426.42237701188880.577622985
8415553071555298.104102838.89589716610499
8515231241555306.99958102-32182.999581021
8613445971523125.51575487-178528.515754867
8713767801344605.4083357732174.5916642286
8813975831376778.4846411320804.5153588706
8915345031397582.02014897136920.979851034
9017129291534496.55129589178432.448704107
9115863551712920.59618879-126565.596188794
9216496981586360.9609862663337.0390137376
9315967121649695.01695223-52983.0169522301
9415656531596714.49539405-31061.4953940541
9518074211565654.46293426241766.537065736
9617544351807409.61327999-52974.6132799941
9716807461754437.49499826-73691.494998258
9815760091680749.47072192-104740.470721923
9916807461576013.93306654104732.066933464
10017337321680741.0673292752990.9326707339
10117969631733729.5042331363233.4957668686
10218809981796960.0218289184037.9781710904
10317969631880994.04197943-84031.0419794281
10418488261796966.9576938951859.0423061089
10517855851848823.5575429-63238.557542902
10617752391785587.97840949-10348.9784094898
10720376991775239.48741617262459.51258383
10820595252037686.6386822621838.3613177361
10919754912059523.97145689-84032.971456891
11018281231975494.95778477-147371.957784766
11119536641828129.94092425125534.05907575
11220065491953658.0875970752890.912402929
11320698822006546.5089438963335.4910561142
11421642732069879.0170251494393.9829748643
11520698822164268.55423233-94386.5542323291
11621435702069886.4454177973683.5545822082
11721113882143566.52965205-32178.5296520549
11819961932111389.51554434-115196.515544342
11922379511996198.42552532241752.574474681
12022379512237939.613937611.3860623957589

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
2 & 577918 & 588264 & -10346 \tabularnewline
3 & 567562 & 577918.487275893 & -10356.4872758928 \tabularnewline
4 & 546859 & 567562.487769822 & -20703.4877698225 \tabularnewline
5 & 756344 & 546859.975092836 & 209484.024907164 \tabularnewline
6 & 745987 & 756334.133721704 & -10347.1337217042 \tabularnewline
7 & 588264 & 745987.487329289 & -157723.487329289 \tabularnewline
8 & 483527 & 588271.428460573 & -104744.428460573 \tabularnewline
9 & 493873 & 483531.933252937 & 10341.066747063 \tabularnewline
10 & 493873 & 493872.512956454 & 0.487043546396308 \tabularnewline
11 & 504229 & 493872.999977061 & 10356.0000229388 \tabularnewline
12 & 526055 & 504228.512253126 & 21826.4877468738 \tabularnewline
13 & 462824 & 526053.972016112 & -63229.9720161123 \tabularnewline
14 & 399492 & 462826.978005129 & -63334.9780051287 \tabularnewline
15 & 347630 & 399494.982950701 & -51864.9829507006 \tabularnewline
16 & 347630 & 347632.44273689 & -2.44273689045804 \tabularnewline
17 & 546859 & 347630.000115048 & 199228.999884952 \tabularnewline
18 & 567562 & 546849.616712858 & 20712.3832871425 \tabularnewline
19 & 409838 & 567561.024488203 & -157723.024488203 \tabularnewline
20 & 231412 & 409845.428438774 & -178433.428438774 \tabularnewline
21 & 325803 & 231420.403857349 & 94382.5961426508 \tabularnewline
22 & 325803 & 325798.554768626 & 4.44523137377109 \tabularnewline
23 & 399492 & 325802.999790639 & 73689.0002093615 \tabularnewline
24 & 442021 & 399488.529395577 & 42532.4706044231 \tabularnewline
25 & 431664 & 442018.996805762 & -10354.9968057623 \tabularnewline
26 & 325803 & 431664.487699624 & -105861.487699624 \tabularnewline
27 & 378790 & 325807.985864191 & 52982.0141358086 \tabularnewline
28 & 357986 & 378787.504653176 & -20801.5046531765 \tabularnewline
29 & 536412 & 357986.979709235 & 178425.020290765 \tabularnewline
30 & 493873 & 536403.596538658 & -42530.5965386578 \tabularnewline
31 & 325803 & 493875.003105973 & -168072.003105973 \tabularnewline
32 & 200263 & 325810.915854954 & -125547.915854954 \tabularnewline
33 & 315447 & 200268.913055556 & 115178.086944444 \tabularnewline
34 & 347630 & 315441.575342631 & 32188.4246573689 \tabularnewline
35 & 378790 & 347628.483989623 & 31161.516010377 \tabularnewline
36 & 420195 & 378788.532354965 & 41406.4676450351 \tabularnewline
37 & 336150 & 420193.049838248 & -84043.049838248 \tabularnewline
38 & 263595 & 336153.958259437 & -72558.9582594372 \tabularnewline
39 & 294755 & 263598.417381709 & 31156.582618291 \tabularnewline
40 & 305101 & 294753.532587318 & 10347.4674126821 \tabularnewline
41 & 577918 & 305100.512654995 & 272817.487345005 \tabularnewline
42 & 577918 & 577905.150842384 & 12.8491576161468 \tabularnewline
43 & 420195 & 577917.99939483 & -157722.99939483 \tabularnewline
44 & 399492 & 420202.428437593 & -20710.4284375926 \tabularnewline
45 & 462824 & 399492.975419728 & 63331.024580272 \tabularnewline
46 & 431664 & 462821.017235498 & -31157.0172354978 \tabularnewline
47 & 515709 & 431665.467433152 & 84043.5325668483 \tabularnewline
48 & 620447 & 515705.041717827 & 104741.958282173 \tabularnewline
49 & 641250 & 620442.066863403 & 20807.9331365966 \tabularnewline
50 & 493873 & 641249.019987996 & -147376.019987996 \tabularnewline
51 & 452367 & 493879.941115572 & -41512.9411155718 \tabularnewline
52 & 409838 & 452368.955176439 & -42530.9551764394 \tabularnewline
53 & 694135 & 409840.003122864 & 284294.996877136 \tabularnewline
54 & 714939 & 694121.610274657 & 20817.3897253432 \tabularnewline
55 & 661953 & 714938.019542609 & -52985.0195426095 \tabularnewline
56 & 714939 & 661955.495488372 & 52983.5045116278 \tabularnewline
57 & 704481 & 714936.504582983 & -10455.5045829827 \tabularnewline
58 & 620447 & 704481.492433339 & -84034.4924333394 \tabularnewline
59 & 714939 & 620450.9578564 & 94488.0421435995 \tabularnewline
60 & 819676 & 714934.549802331 & 104741.450197669 \tabularnewline
61 & 862205 & 819671.066887333 & 42533.9331126668 \tabularnewline
62 & 735641 & 862202.996736881 & -126561.996736881 \tabularnewline
63 & 651596 & 735646.960816736 & -84050.9608167355 \tabularnewline
64 & 714939 & 651599.958632028 & 63339.0413679716 \tabularnewline
65 & 987746 & 714936.016857923 & 272809.983142077 \tabularnewline
66 & 1071790 & 987733.151195817 & 84056.8488041833 \tabularnewline
67 & 1051088 & 1071786.04109066 & -20698.0410906591 \tabularnewline
68 & 1092483 & 1051088.97483631 & 41394.0251636913 \tabularnewline
69 & 1082137 & 1092481.05042426 & -10344.050424264 \tabularnewline
70 & 977399 & 1082137.48718407 & -104738.487184072 \tabularnewline
71 & 1155825 & 977403.932973115 & 178421.067026885 \tabularnewline
72 & 1198354 & 1155816.59672485 & 42537.4032751515 \tabularnewline
73 & 1260562 & 1198351.99657344 & 62210.0034265567 \tabularnewline
74 & 1071790 & 1260559.07003335 & -188769.07003335 \tabularnewline
75 & 998102 & 1071798.89064538 & -73696.8906453818 \tabularnewline
76 & 1082137 & 998105.470976047 & 84031.5290239531 \tabularnewline
77 & 1282389 & 1082133.04228317 & 200255.95771683 \tabularnewline
78 & 1460814 & 1282379.5683452 & 178434.431654801 \tabularnewline
79 & 1418286 & 1460805.5960954 & -42519.5960954013 \tabularnewline
80 & 1418286 & 1418288.00258787 & -2.00258787418716 \tabularnewline
81 & 1439089 & 1418286.00009432 & 20802.9999056822 \tabularnewline
82 & 1366423 & 1439088.02022034 & -72665.0202203412 \tabularnewline
83 & 1555307 & 1366426.42237701 & 188880.577622985 \tabularnewline
84 & 1555307 & 1555298.10410283 & 8.89589716610499 \tabularnewline
85 & 1523124 & 1555306.99958102 & -32182.999581021 \tabularnewline
86 & 1344597 & 1523125.51575487 & -178528.515754867 \tabularnewline
87 & 1376780 & 1344605.40833577 & 32174.5916642286 \tabularnewline
88 & 1397583 & 1376778.48464113 & 20804.5153588706 \tabularnewline
89 & 1534503 & 1397582.02014897 & 136920.979851034 \tabularnewline
90 & 1712929 & 1534496.55129589 & 178432.448704107 \tabularnewline
91 & 1586355 & 1712920.59618879 & -126565.596188794 \tabularnewline
92 & 1649698 & 1586360.96098626 & 63337.0390137376 \tabularnewline
93 & 1596712 & 1649695.01695223 & -52983.0169522301 \tabularnewline
94 & 1565653 & 1596714.49539405 & -31061.4953940541 \tabularnewline
95 & 1807421 & 1565654.46293426 & 241766.537065736 \tabularnewline
96 & 1754435 & 1807409.61327999 & -52974.6132799941 \tabularnewline
97 & 1680746 & 1754437.49499826 & -73691.494998258 \tabularnewline
98 & 1576009 & 1680749.47072192 & -104740.470721923 \tabularnewline
99 & 1680746 & 1576013.93306654 & 104732.066933464 \tabularnewline
100 & 1733732 & 1680741.06732927 & 52990.9326707339 \tabularnewline
101 & 1796963 & 1733729.50423313 & 63233.4957668686 \tabularnewline
102 & 1880998 & 1796960.02182891 & 84037.9781710904 \tabularnewline
103 & 1796963 & 1880994.04197943 & -84031.0419794281 \tabularnewline
104 & 1848826 & 1796966.95769389 & 51859.0423061089 \tabularnewline
105 & 1785585 & 1848823.5575429 & -63238.557542902 \tabularnewline
106 & 1775239 & 1785587.97840949 & -10348.9784094898 \tabularnewline
107 & 2037699 & 1775239.48741617 & 262459.51258383 \tabularnewline
108 & 2059525 & 2037686.63868226 & 21838.3613177361 \tabularnewline
109 & 1975491 & 2059523.97145689 & -84032.971456891 \tabularnewline
110 & 1828123 & 1975494.95778477 & -147371.957784766 \tabularnewline
111 & 1953664 & 1828129.94092425 & 125534.05907575 \tabularnewline
112 & 2006549 & 1953658.08759707 & 52890.912402929 \tabularnewline
113 & 2069882 & 2006546.50894389 & 63335.4910561142 \tabularnewline
114 & 2164273 & 2069879.01702514 & 94393.9829748643 \tabularnewline
115 & 2069882 & 2164268.55423233 & -94386.5542323291 \tabularnewline
116 & 2143570 & 2069886.44541779 & 73683.5545822082 \tabularnewline
117 & 2111388 & 2143566.52965205 & -32178.5296520549 \tabularnewline
118 & 1996193 & 2111389.51554434 & -115196.515544342 \tabularnewline
119 & 2237951 & 1996198.42552532 & 241752.574474681 \tabularnewline
120 & 2237951 & 2237939.6139376 & 11.3860623957589 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123653&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]2[/C][C]577918[/C][C]588264[/C][C]-10346[/C][/ROW]
[ROW][C]3[/C][C]567562[/C][C]577918.487275893[/C][C]-10356.4872758928[/C][/ROW]
[ROW][C]4[/C][C]546859[/C][C]567562.487769822[/C][C]-20703.4877698225[/C][/ROW]
[ROW][C]5[/C][C]756344[/C][C]546859.975092836[/C][C]209484.024907164[/C][/ROW]
[ROW][C]6[/C][C]745987[/C][C]756334.133721704[/C][C]-10347.1337217042[/C][/ROW]
[ROW][C]7[/C][C]588264[/C][C]745987.487329289[/C][C]-157723.487329289[/C][/ROW]
[ROW][C]8[/C][C]483527[/C][C]588271.428460573[/C][C]-104744.428460573[/C][/ROW]
[ROW][C]9[/C][C]493873[/C][C]483531.933252937[/C][C]10341.066747063[/C][/ROW]
[ROW][C]10[/C][C]493873[/C][C]493872.512956454[/C][C]0.487043546396308[/C][/ROW]
[ROW][C]11[/C][C]504229[/C][C]493872.999977061[/C][C]10356.0000229388[/C][/ROW]
[ROW][C]12[/C][C]526055[/C][C]504228.512253126[/C][C]21826.4877468738[/C][/ROW]
[ROW][C]13[/C][C]462824[/C][C]526053.972016112[/C][C]-63229.9720161123[/C][/ROW]
[ROW][C]14[/C][C]399492[/C][C]462826.978005129[/C][C]-63334.9780051287[/C][/ROW]
[ROW][C]15[/C][C]347630[/C][C]399494.982950701[/C][C]-51864.9829507006[/C][/ROW]
[ROW][C]16[/C][C]347630[/C][C]347632.44273689[/C][C]-2.44273689045804[/C][/ROW]
[ROW][C]17[/C][C]546859[/C][C]347630.000115048[/C][C]199228.999884952[/C][/ROW]
[ROW][C]18[/C][C]567562[/C][C]546849.616712858[/C][C]20712.3832871425[/C][/ROW]
[ROW][C]19[/C][C]409838[/C][C]567561.024488203[/C][C]-157723.024488203[/C][/ROW]
[ROW][C]20[/C][C]231412[/C][C]409845.428438774[/C][C]-178433.428438774[/C][/ROW]
[ROW][C]21[/C][C]325803[/C][C]231420.403857349[/C][C]94382.5961426508[/C][/ROW]
[ROW][C]22[/C][C]325803[/C][C]325798.554768626[/C][C]4.44523137377109[/C][/ROW]
[ROW][C]23[/C][C]399492[/C][C]325802.999790639[/C][C]73689.0002093615[/C][/ROW]
[ROW][C]24[/C][C]442021[/C][C]399488.529395577[/C][C]42532.4706044231[/C][/ROW]
[ROW][C]25[/C][C]431664[/C][C]442018.996805762[/C][C]-10354.9968057623[/C][/ROW]
[ROW][C]26[/C][C]325803[/C][C]431664.487699624[/C][C]-105861.487699624[/C][/ROW]
[ROW][C]27[/C][C]378790[/C][C]325807.985864191[/C][C]52982.0141358086[/C][/ROW]
[ROW][C]28[/C][C]357986[/C][C]378787.504653176[/C][C]-20801.5046531765[/C][/ROW]
[ROW][C]29[/C][C]536412[/C][C]357986.979709235[/C][C]178425.020290765[/C][/ROW]
[ROW][C]30[/C][C]493873[/C][C]536403.596538658[/C][C]-42530.5965386578[/C][/ROW]
[ROW][C]31[/C][C]325803[/C][C]493875.003105973[/C][C]-168072.003105973[/C][/ROW]
[ROW][C]32[/C][C]200263[/C][C]325810.915854954[/C][C]-125547.915854954[/C][/ROW]
[ROW][C]33[/C][C]315447[/C][C]200268.913055556[/C][C]115178.086944444[/C][/ROW]
[ROW][C]34[/C][C]347630[/C][C]315441.575342631[/C][C]32188.4246573689[/C][/ROW]
[ROW][C]35[/C][C]378790[/C][C]347628.483989623[/C][C]31161.516010377[/C][/ROW]
[ROW][C]36[/C][C]420195[/C][C]378788.532354965[/C][C]41406.4676450351[/C][/ROW]
[ROW][C]37[/C][C]336150[/C][C]420193.049838248[/C][C]-84043.049838248[/C][/ROW]
[ROW][C]38[/C][C]263595[/C][C]336153.958259437[/C][C]-72558.9582594372[/C][/ROW]
[ROW][C]39[/C][C]294755[/C][C]263598.417381709[/C][C]31156.582618291[/C][/ROW]
[ROW][C]40[/C][C]305101[/C][C]294753.532587318[/C][C]10347.4674126821[/C][/ROW]
[ROW][C]41[/C][C]577918[/C][C]305100.512654995[/C][C]272817.487345005[/C][/ROW]
[ROW][C]42[/C][C]577918[/C][C]577905.150842384[/C][C]12.8491576161468[/C][/ROW]
[ROW][C]43[/C][C]420195[/C][C]577917.99939483[/C][C]-157722.99939483[/C][/ROW]
[ROW][C]44[/C][C]399492[/C][C]420202.428437593[/C][C]-20710.4284375926[/C][/ROW]
[ROW][C]45[/C][C]462824[/C][C]399492.975419728[/C][C]63331.024580272[/C][/ROW]
[ROW][C]46[/C][C]431664[/C][C]462821.017235498[/C][C]-31157.0172354978[/C][/ROW]
[ROW][C]47[/C][C]515709[/C][C]431665.467433152[/C][C]84043.5325668483[/C][/ROW]
[ROW][C]48[/C][C]620447[/C][C]515705.041717827[/C][C]104741.958282173[/C][/ROW]
[ROW][C]49[/C][C]641250[/C][C]620442.066863403[/C][C]20807.9331365966[/C][/ROW]
[ROW][C]50[/C][C]493873[/C][C]641249.019987996[/C][C]-147376.019987996[/C][/ROW]
[ROW][C]51[/C][C]452367[/C][C]493879.941115572[/C][C]-41512.9411155718[/C][/ROW]
[ROW][C]52[/C][C]409838[/C][C]452368.955176439[/C][C]-42530.9551764394[/C][/ROW]
[ROW][C]53[/C][C]694135[/C][C]409840.003122864[/C][C]284294.996877136[/C][/ROW]
[ROW][C]54[/C][C]714939[/C][C]694121.610274657[/C][C]20817.3897253432[/C][/ROW]
[ROW][C]55[/C][C]661953[/C][C]714938.019542609[/C][C]-52985.0195426095[/C][/ROW]
[ROW][C]56[/C][C]714939[/C][C]661955.495488372[/C][C]52983.5045116278[/C][/ROW]
[ROW][C]57[/C][C]704481[/C][C]714936.504582983[/C][C]-10455.5045829827[/C][/ROW]
[ROW][C]58[/C][C]620447[/C][C]704481.492433339[/C][C]-84034.4924333394[/C][/ROW]
[ROW][C]59[/C][C]714939[/C][C]620450.9578564[/C][C]94488.0421435995[/C][/ROW]
[ROW][C]60[/C][C]819676[/C][C]714934.549802331[/C][C]104741.450197669[/C][/ROW]
[ROW][C]61[/C][C]862205[/C][C]819671.066887333[/C][C]42533.9331126668[/C][/ROW]
[ROW][C]62[/C][C]735641[/C][C]862202.996736881[/C][C]-126561.996736881[/C][/ROW]
[ROW][C]63[/C][C]651596[/C][C]735646.960816736[/C][C]-84050.9608167355[/C][/ROW]
[ROW][C]64[/C][C]714939[/C][C]651599.958632028[/C][C]63339.0413679716[/C][/ROW]
[ROW][C]65[/C][C]987746[/C][C]714936.016857923[/C][C]272809.983142077[/C][/ROW]
[ROW][C]66[/C][C]1071790[/C][C]987733.151195817[/C][C]84056.8488041833[/C][/ROW]
[ROW][C]67[/C][C]1051088[/C][C]1071786.04109066[/C][C]-20698.0410906591[/C][/ROW]
[ROW][C]68[/C][C]1092483[/C][C]1051088.97483631[/C][C]41394.0251636913[/C][/ROW]
[ROW][C]69[/C][C]1082137[/C][C]1092481.05042426[/C][C]-10344.050424264[/C][/ROW]
[ROW][C]70[/C][C]977399[/C][C]1082137.48718407[/C][C]-104738.487184072[/C][/ROW]
[ROW][C]71[/C][C]1155825[/C][C]977403.932973115[/C][C]178421.067026885[/C][/ROW]
[ROW][C]72[/C][C]1198354[/C][C]1155816.59672485[/C][C]42537.4032751515[/C][/ROW]
[ROW][C]73[/C][C]1260562[/C][C]1198351.99657344[/C][C]62210.0034265567[/C][/ROW]
[ROW][C]74[/C][C]1071790[/C][C]1260559.07003335[/C][C]-188769.07003335[/C][/ROW]
[ROW][C]75[/C][C]998102[/C][C]1071798.89064538[/C][C]-73696.8906453818[/C][/ROW]
[ROW][C]76[/C][C]1082137[/C][C]998105.470976047[/C][C]84031.5290239531[/C][/ROW]
[ROW][C]77[/C][C]1282389[/C][C]1082133.04228317[/C][C]200255.95771683[/C][/ROW]
[ROW][C]78[/C][C]1460814[/C][C]1282379.5683452[/C][C]178434.431654801[/C][/ROW]
[ROW][C]79[/C][C]1418286[/C][C]1460805.5960954[/C][C]-42519.5960954013[/C][/ROW]
[ROW][C]80[/C][C]1418286[/C][C]1418288.00258787[/C][C]-2.00258787418716[/C][/ROW]
[ROW][C]81[/C][C]1439089[/C][C]1418286.00009432[/C][C]20802.9999056822[/C][/ROW]
[ROW][C]82[/C][C]1366423[/C][C]1439088.02022034[/C][C]-72665.0202203412[/C][/ROW]
[ROW][C]83[/C][C]1555307[/C][C]1366426.42237701[/C][C]188880.577622985[/C][/ROW]
[ROW][C]84[/C][C]1555307[/C][C]1555298.10410283[/C][C]8.89589716610499[/C][/ROW]
[ROW][C]85[/C][C]1523124[/C][C]1555306.99958102[/C][C]-32182.999581021[/C][/ROW]
[ROW][C]86[/C][C]1344597[/C][C]1523125.51575487[/C][C]-178528.515754867[/C][/ROW]
[ROW][C]87[/C][C]1376780[/C][C]1344605.40833577[/C][C]32174.5916642286[/C][/ROW]
[ROW][C]88[/C][C]1397583[/C][C]1376778.48464113[/C][C]20804.5153588706[/C][/ROW]
[ROW][C]89[/C][C]1534503[/C][C]1397582.02014897[/C][C]136920.979851034[/C][/ROW]
[ROW][C]90[/C][C]1712929[/C][C]1534496.55129589[/C][C]178432.448704107[/C][/ROW]
[ROW][C]91[/C][C]1586355[/C][C]1712920.59618879[/C][C]-126565.596188794[/C][/ROW]
[ROW][C]92[/C][C]1649698[/C][C]1586360.96098626[/C][C]63337.0390137376[/C][/ROW]
[ROW][C]93[/C][C]1596712[/C][C]1649695.01695223[/C][C]-52983.0169522301[/C][/ROW]
[ROW][C]94[/C][C]1565653[/C][C]1596714.49539405[/C][C]-31061.4953940541[/C][/ROW]
[ROW][C]95[/C][C]1807421[/C][C]1565654.46293426[/C][C]241766.537065736[/C][/ROW]
[ROW][C]96[/C][C]1754435[/C][C]1807409.61327999[/C][C]-52974.6132799941[/C][/ROW]
[ROW][C]97[/C][C]1680746[/C][C]1754437.49499826[/C][C]-73691.494998258[/C][/ROW]
[ROW][C]98[/C][C]1576009[/C][C]1680749.47072192[/C][C]-104740.470721923[/C][/ROW]
[ROW][C]99[/C][C]1680746[/C][C]1576013.93306654[/C][C]104732.066933464[/C][/ROW]
[ROW][C]100[/C][C]1733732[/C][C]1680741.06732927[/C][C]52990.9326707339[/C][/ROW]
[ROW][C]101[/C][C]1796963[/C][C]1733729.50423313[/C][C]63233.4957668686[/C][/ROW]
[ROW][C]102[/C][C]1880998[/C][C]1796960.02182891[/C][C]84037.9781710904[/C][/ROW]
[ROW][C]103[/C][C]1796963[/C][C]1880994.04197943[/C][C]-84031.0419794281[/C][/ROW]
[ROW][C]104[/C][C]1848826[/C][C]1796966.95769389[/C][C]51859.0423061089[/C][/ROW]
[ROW][C]105[/C][C]1785585[/C][C]1848823.5575429[/C][C]-63238.557542902[/C][/ROW]
[ROW][C]106[/C][C]1775239[/C][C]1785587.97840949[/C][C]-10348.9784094898[/C][/ROW]
[ROW][C]107[/C][C]2037699[/C][C]1775239.48741617[/C][C]262459.51258383[/C][/ROW]
[ROW][C]108[/C][C]2059525[/C][C]2037686.63868226[/C][C]21838.3613177361[/C][/ROW]
[ROW][C]109[/C][C]1975491[/C][C]2059523.97145689[/C][C]-84032.971456891[/C][/ROW]
[ROW][C]110[/C][C]1828123[/C][C]1975494.95778477[/C][C]-147371.957784766[/C][/ROW]
[ROW][C]111[/C][C]1953664[/C][C]1828129.94092425[/C][C]125534.05907575[/C][/ROW]
[ROW][C]112[/C][C]2006549[/C][C]1953658.08759707[/C][C]52890.912402929[/C][/ROW]
[ROW][C]113[/C][C]2069882[/C][C]2006546.50894389[/C][C]63335.4910561142[/C][/ROW]
[ROW][C]114[/C][C]2164273[/C][C]2069879.01702514[/C][C]94393.9829748643[/C][/ROW]
[ROW][C]115[/C][C]2069882[/C][C]2164268.55423233[/C][C]-94386.5542323291[/C][/ROW]
[ROW][C]116[/C][C]2143570[/C][C]2069886.44541779[/C][C]73683.5545822082[/C][/ROW]
[ROW][C]117[/C][C]2111388[/C][C]2143566.52965205[/C][C]-32178.5296520549[/C][/ROW]
[ROW][C]118[/C][C]1996193[/C][C]2111389.51554434[/C][C]-115196.515544342[/C][/ROW]
[ROW][C]119[/C][C]2237951[/C][C]1996198.42552532[/C][C]241752.574474681[/C][/ROW]
[ROW][C]120[/C][C]2237951[/C][C]2237939.6139376[/C][C]11.3860623957589[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123653&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123653&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
2577918588264-10346
3567562577918.487275893-10356.4872758928
4546859567562.487769822-20703.4877698225
5756344546859.975092836209484.024907164
6745987756334.133721704-10347.1337217042
7588264745987.487329289-157723.487329289
8483527588271.428460573-104744.428460573
9493873483531.93325293710341.066747063
10493873493872.5129564540.487043546396308
11504229493872.99997706110356.0000229388
12526055504228.51225312621826.4877468738
13462824526053.972016112-63229.9720161123
14399492462826.978005129-63334.9780051287
15347630399494.982950701-51864.9829507006
16347630347632.44273689-2.44273689045804
17546859347630.000115048199228.999884952
18567562546849.61671285820712.3832871425
19409838567561.024488203-157723.024488203
20231412409845.428438774-178433.428438774
21325803231420.40385734994382.5961426508
22325803325798.5547686264.44523137377109
23399492325802.99979063973689.0002093615
24442021399488.52939557742532.4706044231
25431664442018.996805762-10354.9968057623
26325803431664.487699624-105861.487699624
27378790325807.98586419152982.0141358086
28357986378787.504653176-20801.5046531765
29536412357986.979709235178425.020290765
30493873536403.596538658-42530.5965386578
31325803493875.003105973-168072.003105973
32200263325810.915854954-125547.915854954
33315447200268.913055556115178.086944444
34347630315441.57534263132188.4246573689
35378790347628.48398962331161.516010377
36420195378788.53235496541406.4676450351
37336150420193.049838248-84043.049838248
38263595336153.958259437-72558.9582594372
39294755263598.41738170931156.582618291
40305101294753.53258731810347.4674126821
41577918305100.512654995272817.487345005
42577918577905.15084238412.8491576161468
43420195577917.99939483-157722.99939483
44399492420202.428437593-20710.4284375926
45462824399492.97541972863331.024580272
46431664462821.017235498-31157.0172354978
47515709431665.46743315284043.5325668483
48620447515705.041717827104741.958282173
49641250620442.06686340320807.9331365966
50493873641249.019987996-147376.019987996
51452367493879.941115572-41512.9411155718
52409838452368.955176439-42530.9551764394
53694135409840.003122864284294.996877136
54714939694121.61027465720817.3897253432
55661953714938.019542609-52985.0195426095
56714939661955.49548837252983.5045116278
57704481714936.504582983-10455.5045829827
58620447704481.492433339-84034.4924333394
59714939620450.957856494488.0421435995
60819676714934.549802331104741.450197669
61862205819671.06688733342533.9331126668
62735641862202.996736881-126561.996736881
63651596735646.960816736-84050.9608167355
64714939651599.95863202863339.0413679716
65987746714936.016857923272809.983142077
661071790987733.15119581784056.8488041833
6710510881071786.04109066-20698.0410906591
6810924831051088.9748363141394.0251636913
6910821371092481.05042426-10344.050424264
709773991082137.48718407-104738.487184072
711155825977403.932973115178421.067026885
7211983541155816.5967248542537.4032751515
7312605621198351.9965734462210.0034265567
7410717901260559.07003335-188769.07003335
759981021071798.89064538-73696.8906453818
761082137998105.47097604784031.5290239531
7712823891082133.04228317200255.95771683
7814608141282379.5683452178434.431654801
7914182861460805.5960954-42519.5960954013
8014182861418288.00258787-2.00258787418716
8114390891418286.0000943220802.9999056822
8213664231439088.02022034-72665.0202203412
8315553071366426.42237701188880.577622985
8415553071555298.104102838.89589716610499
8515231241555306.99958102-32182.999581021
8613445971523125.51575487-178528.515754867
8713767801344605.4083357732174.5916642286
8813975831376778.4846411320804.5153588706
8915345031397582.02014897136920.979851034
9017129291534496.55129589178432.448704107
9115863551712920.59618879-126565.596188794
9216496981586360.9609862663337.0390137376
9315967121649695.01695223-52983.0169522301
9415656531596714.49539405-31061.4953940541
9518074211565654.46293426241766.537065736
9617544351807409.61327999-52974.6132799941
9716807461754437.49499826-73691.494998258
9815760091680749.47072192-104740.470721923
9916807461576013.93306654104732.066933464
10017337321680741.0673292752990.9326707339
10117969631733729.5042331363233.4957668686
10218809981796960.0218289184037.9781710904
10317969631880994.04197943-84031.0419794281
10418488261796966.9576938951859.0423061089
10517855851848823.5575429-63238.557542902
10617752391785587.97840949-10348.9784094898
10720376991775239.48741617262459.51258383
10820595252037686.6386822621838.3613177361
10919754912059523.97145689-84032.971456891
11018281231975494.95778477-147371.957784766
11119536641828129.94092425125534.05907575
11220065491953658.0875970752890.912402929
11320698822006546.5089438963335.4910561142
11421642732069879.0170251494393.9829748643
11520698822164268.55423233-94386.5542323291
11621435702069886.4454177973683.5545822082
11721113882143566.52965205-32178.5296520549
11819961932111389.51554434-115196.515544342
11922379511996198.42552532241752.574474681
12022379512237939.613937611.3860623957589







Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
1212237950.999463742029621.27673192446280.72219557
1222237950.999463741943335.218119462532566.78080802
1232237950.999463741877124.664697722598777.33422976
1242237950.999463741821306.271782882654595.7271446
1252237950.999463741772129.129702522703772.86922496
1262237950.999463741727669.508920122748232.49000736
1272237950.999463741686784.61366452789117.38526298
1282237950.999463741648729.843972382827172.1549551
1292237950.999463741612987.996301032862914.00262645
1302237950.999463741579182.49644792896719.50247958
1312237950.999463741547029.060450872928872.93847661
1322237950.999463741516306.827414322959595.17151316

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
121 & 2237950.99946374 & 2029621.2767319 & 2446280.72219557 \tabularnewline
122 & 2237950.99946374 & 1943335.21811946 & 2532566.78080802 \tabularnewline
123 & 2237950.99946374 & 1877124.66469772 & 2598777.33422976 \tabularnewline
124 & 2237950.99946374 & 1821306.27178288 & 2654595.7271446 \tabularnewline
125 & 2237950.99946374 & 1772129.12970252 & 2703772.86922496 \tabularnewline
126 & 2237950.99946374 & 1727669.50892012 & 2748232.49000736 \tabularnewline
127 & 2237950.99946374 & 1686784.6136645 & 2789117.38526298 \tabularnewline
128 & 2237950.99946374 & 1648729.84397238 & 2827172.1549551 \tabularnewline
129 & 2237950.99946374 & 1612987.99630103 & 2862914.00262645 \tabularnewline
130 & 2237950.99946374 & 1579182.4964479 & 2896719.50247958 \tabularnewline
131 & 2237950.99946374 & 1547029.06045087 & 2928872.93847661 \tabularnewline
132 & 2237950.99946374 & 1516306.82741432 & 2959595.17151316 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=123653&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]121[/C][C]2237950.99946374[/C][C]2029621.2767319[/C][C]2446280.72219557[/C][/ROW]
[ROW][C]122[/C][C]2237950.99946374[/C][C]1943335.21811946[/C][C]2532566.78080802[/C][/ROW]
[ROW][C]123[/C][C]2237950.99946374[/C][C]1877124.66469772[/C][C]2598777.33422976[/C][/ROW]
[ROW][C]124[/C][C]2237950.99946374[/C][C]1821306.27178288[/C][C]2654595.7271446[/C][/ROW]
[ROW][C]125[/C][C]2237950.99946374[/C][C]1772129.12970252[/C][C]2703772.86922496[/C][/ROW]
[ROW][C]126[/C][C]2237950.99946374[/C][C]1727669.50892012[/C][C]2748232.49000736[/C][/ROW]
[ROW][C]127[/C][C]2237950.99946374[/C][C]1686784.6136645[/C][C]2789117.38526298[/C][/ROW]
[ROW][C]128[/C][C]2237950.99946374[/C][C]1648729.84397238[/C][C]2827172.1549551[/C][/ROW]
[ROW][C]129[/C][C]2237950.99946374[/C][C]1612987.99630103[/C][C]2862914.00262645[/C][/ROW]
[ROW][C]130[/C][C]2237950.99946374[/C][C]1579182.4964479[/C][C]2896719.50247958[/C][/ROW]
[ROW][C]131[/C][C]2237950.99946374[/C][C]1547029.06045087[/C][C]2928872.93847661[/C][/ROW]
[ROW][C]132[/C][C]2237950.99946374[/C][C]1516306.82741432[/C][C]2959595.17151316[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=123653&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=123653&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
1212237950.999463742029621.27673192446280.72219557
1222237950.999463741943335.218119462532566.78080802
1232237950.999463741877124.664697722598777.33422976
1242237950.999463741821306.271782882654595.7271446
1252237950.999463741772129.129702522703772.86922496
1262237950.999463741727669.508920122748232.49000736
1272237950.999463741686784.61366452789117.38526298
1282237950.999463741648729.843972382827172.1549551
1292237950.999463741612987.996301032862914.00262645
1302237950.999463741579182.49644792896719.50247958
1312237950.999463741547029.060450872928872.93847661
1322237950.999463741516306.827414322959595.17151316



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