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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationTue, 15 Aug 2017 21:48:51 +0200
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/Aug/15/t150282654720t9u25egxigym4.htm/, Retrieved Sun, 19 May 2024 23:29:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307326, Retrieved Sun, 19 May 2024 23:29:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Exponential Smoothing] [] [2017-08-15 19:48:51] [1a8cec710a8245ea2c14b5d40c333c7c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
247832,00
246909,00
245973,00
244036,00
263198,00
262184,00
247832,00
238290,00
239213,00
239213,00
240240,00
242086,00
244959,00
244959,00
243113,00
238290,00
263198,00
266994,00
261261,00
247832,00
253578,00
244959,00
248846,00
250705,00
252642,00
247832,00
248846,00
242086,00
263198,00
269867,00
264134,00
253578,00
265057,00
252642,00
264134,00
263198,00
266071,00
255515,00
266994,00
266071,00
283296,00
279409,00
264134,00
256438,00
266994,00
252642,00
263198,00
265057,00
268944,00
260338,00
265057,00
267930,00
278486,00
269867,00
258388,00
245973,00
257465,00
225875,00
241163,00
249769,00
258388,00
245973,00
245973,00
245973,00
252642,00
243113,00
230607,00
220142,00
227734,00
198094,00
216255,00
226811,00
228748,00
218192,00
219115,00
216255,00
225875,00
219115,00
205790,00
196157,00
212446,00
177073,00
200044,00
210509,00
210509,00
198094,00
186615,00
185692,00
196157,00
186615,00
168467,00
155961,00
169390,00
137813,00
166517,00
181792,00
186615,00
176059,00
162721,00
172263,00
176059,00
173186,00
144469,00
131144,00
140673,00
111969,00
141609,00
152165,00
160771,00
146419,00
132990,00
140673,00
144469,00
136877,00
108173,00
95667,00
107146,00
75569,00
110019,00
131144,00

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307326&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=307326&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307326&T=0

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


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

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.659004759562144
beta0
gammaFALSE

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.659004759562144 \tabularnewline
beta & 0 \tabularnewline
gamma & FALSE \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307326&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]0.659004759562144[/C][/ROW]
[ROW][C]beta[/C][C]0[/C][/ROW]
[ROW][C]gamma[/C][C]FALSE[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307326&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307326&T=1

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


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

Estimated Parameters of Exponential Smoothing
ParameterValue
alpha0.659004759562144
beta0
gammaFALSE






Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
3245973245986-13
4244036245054.432938126-1018.43293812568
5263198243460.28078460619737.719215394
6262184255544.5316904526639.46830954819
7247832258996.972907406-11164.9729074061
8238290250716.202621043-12426.2026210431
9239213241604.275950492-2391.27595049213
10239213239105.413717691107.586282308679
11240240238253.3135897961986.68641020363
12242086238639.5493898783446.450610122
13244959239987.7767455444971.22325445575
14244959242340.8365310772618.16346892339
15243113243143.218718409-30.2187184088689
16238290242200.30443915-3910.30443914956
17263198238700.39520241324497.604797587
18266994253921.43336189513072.5666381048
19261261261613.3169961-352.316996099544
20247832260458.138418795-12626.1384187953
21253578251214.4531059192363.54689408126
22244959251849.041758567-6890.04175856663
23248846246385.4714460892460.5285539107
24250705247083.9714741553621.02852584497
25252642248547.2465071974094.75349280285
26247832250322.708548188-2490.70854818792
27248846247758.319760251087.68023975004
28242086247552.106215127-5466.10621512693
29263198243026.91620308620171.0837969139
30269867255396.75643077914470.2435692208
31264134264009.715814919124.284185080789
32253578263168.619684426-9590.61968442576
33265057255925.3556652399131.64433476119
34252642261020.152744475-8378.15274447514
35264134254575.9102095279558.08979047264
36263198259951.7368737713246.26312622882
37266071261168.0397247474902.96027525296
38255515263476.113882083-7961.11388208286
39266994257306.7019423749687.298057626
40266071262767.6774696473303.32253035333
41283296264021.58273951819274.4172604816
42279409275800.5154519623608.48454803752
43264134277255.523943926-13121.5239439256
44256438267685.37721217-11247.37721217
45266994259350.3020967597643.6979032408
46252642263464.53539565-10822.5353956501
47263198255409.4330593877788.56694061309
48265057259619.1357434195437.86425658071
49268944262279.7141703596664.28582964116
50260338265748.510251175-5410.51025117491
51265057261259.9582439913797.04175600916
52267930262839.2268334575090.77316654287
53278486265271.0705800613214.9294199399
54269867273056.771965078-3189.77196507831
55258388270031.697058174-11643.6970581738
56245973261435.445277938-15462.4452779376
57257465250322.6202453087142.37975469249
58225875254106.48249825-28231.4824982501
59241163234578.8011624086584.19883759203
60249769237994.81953428511774.1804657154
61258388244831.06050113513556.9394988653
62245973252842.148155983-6869.14815598296
63245973247392.346827053-1419.34682705265
64245973245533.990512556439.009487444477
65252642244900.2998542747741.70014572563
66243113249079.11709741-5966.11709741049
67230607244224.417534112-13617.4175341119
68220142234327.474566187-14185.4745661872
69227734224056.1793104223677.8206895779
70198094225556.88064967-27462.8806496701
71216255206535.711590259719.2884097496
72226811212017.76891183314793.2310881674
73228748220843.5786082387904.42139176244
74218192225129.629926994-6937.6299269938
75219115219634.698785024-519.698785024113
76216255218369.214812155-2114.21481215456
77225875216052.9371882089822.06281179207
78219115221602.723329897-2487.72332989724
79205790219040.301815021-13250.3018150212
80196157209385.289853287-13228.2898532873
81212446199744.78387910312701.2161208966
82177073207191.945755002-30118.9457550017
83200044186420.41714946213623.5828505385
84210509194475.42309025616033.5769097444
85210509204118.6265865836390.37341341714
86198094207406.913081404-9312.91308140414
87186615200346.65903537-13731.6590353703
88185692190374.430374377-4682.43037437674
89196157186365.6864713449791.31352865588
90186615191895.208689094-5280.20868909356
91168467187492.526031499-19025.5260314995
92155961174031.613823568-18070.6138235679
93169390161199.9933056278190.00669437283
94137813165674.246698065-27861.2466980647
95166517146390.55251670520126.447483295
96181792158730.97720127423061.0227987261
97186615173005.30098600613609.6990139945
98176059181051.157412436-4992.15741243609
99162721176838.301917157-14117.3019171573
100172263166611.9327615755651.06723842517
101176059169413.0129683036645.98703169727
102173186172869.75005418316.249945820484
103144469172155.160273686-27686.1602736865
104131144152986.848879327-21842.8488793267
105140673137669.3075054543003.69249454624
106111969138725.755155621-26756.7551556208
107141609120169.92615762821439.0738423723
108152165133375.37786035518789.6221396447
109160771144834.82828075515936.1717192446
110146419154413.841292937-7994.84129293723
111132990148222.202828948-15232.2028289476
112140673137261.1086660553411.8913339448
113144469138586.5612942345882.43870576634
114136877141540.116399166-4663.11639916626
115108173137544.100497723-29371.1004977234
11695667117265.405476146-21598.4054761456
117107146102108.9534684135037.0465315874
11875569104505.391106865-28936.3911068647
11911001984513.171642889225505.8283571108
120131144100398.633926830745.3660731997

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
3 & 245973 & 245986 & -13 \tabularnewline
4 & 244036 & 245054.432938126 & -1018.43293812568 \tabularnewline
5 & 263198 & 243460.280784606 & 19737.719215394 \tabularnewline
6 & 262184 & 255544.531690452 & 6639.46830954819 \tabularnewline
7 & 247832 & 258996.972907406 & -11164.9729074061 \tabularnewline
8 & 238290 & 250716.202621043 & -12426.2026210431 \tabularnewline
9 & 239213 & 241604.275950492 & -2391.27595049213 \tabularnewline
10 & 239213 & 239105.413717691 & 107.586282308679 \tabularnewline
11 & 240240 & 238253.313589796 & 1986.68641020363 \tabularnewline
12 & 242086 & 238639.549389878 & 3446.450610122 \tabularnewline
13 & 244959 & 239987.776745544 & 4971.22325445575 \tabularnewline
14 & 244959 & 242340.836531077 & 2618.16346892339 \tabularnewline
15 & 243113 & 243143.218718409 & -30.2187184088689 \tabularnewline
16 & 238290 & 242200.30443915 & -3910.30443914956 \tabularnewline
17 & 263198 & 238700.395202413 & 24497.604797587 \tabularnewline
18 & 266994 & 253921.433361895 & 13072.5666381048 \tabularnewline
19 & 261261 & 261613.3169961 & -352.316996099544 \tabularnewline
20 & 247832 & 260458.138418795 & -12626.1384187953 \tabularnewline
21 & 253578 & 251214.453105919 & 2363.54689408126 \tabularnewline
22 & 244959 & 251849.041758567 & -6890.04175856663 \tabularnewline
23 & 248846 & 246385.471446089 & 2460.5285539107 \tabularnewline
24 & 250705 & 247083.971474155 & 3621.02852584497 \tabularnewline
25 & 252642 & 248547.246507197 & 4094.75349280285 \tabularnewline
26 & 247832 & 250322.708548188 & -2490.70854818792 \tabularnewline
27 & 248846 & 247758.31976025 & 1087.68023975004 \tabularnewline
28 & 242086 & 247552.106215127 & -5466.10621512693 \tabularnewline
29 & 263198 & 243026.916203086 & 20171.0837969139 \tabularnewline
30 & 269867 & 255396.756430779 & 14470.2435692208 \tabularnewline
31 & 264134 & 264009.715814919 & 124.284185080789 \tabularnewline
32 & 253578 & 263168.619684426 & -9590.61968442576 \tabularnewline
33 & 265057 & 255925.355665239 & 9131.64433476119 \tabularnewline
34 & 252642 & 261020.152744475 & -8378.15274447514 \tabularnewline
35 & 264134 & 254575.910209527 & 9558.08979047264 \tabularnewline
36 & 263198 & 259951.736873771 & 3246.26312622882 \tabularnewline
37 & 266071 & 261168.039724747 & 4902.96027525296 \tabularnewline
38 & 255515 & 263476.113882083 & -7961.11388208286 \tabularnewline
39 & 266994 & 257306.701942374 & 9687.298057626 \tabularnewline
40 & 266071 & 262767.677469647 & 3303.32253035333 \tabularnewline
41 & 283296 & 264021.582739518 & 19274.4172604816 \tabularnewline
42 & 279409 & 275800.515451962 & 3608.48454803752 \tabularnewline
43 & 264134 & 277255.523943926 & -13121.5239439256 \tabularnewline
44 & 256438 & 267685.37721217 & -11247.37721217 \tabularnewline
45 & 266994 & 259350.302096759 & 7643.6979032408 \tabularnewline
46 & 252642 & 263464.53539565 & -10822.5353956501 \tabularnewline
47 & 263198 & 255409.433059387 & 7788.56694061309 \tabularnewline
48 & 265057 & 259619.135743419 & 5437.86425658071 \tabularnewline
49 & 268944 & 262279.714170359 & 6664.28582964116 \tabularnewline
50 & 260338 & 265748.510251175 & -5410.51025117491 \tabularnewline
51 & 265057 & 261259.958243991 & 3797.04175600916 \tabularnewline
52 & 267930 & 262839.226833457 & 5090.77316654287 \tabularnewline
53 & 278486 & 265271.07058006 & 13214.9294199399 \tabularnewline
54 & 269867 & 273056.771965078 & -3189.77196507831 \tabularnewline
55 & 258388 & 270031.697058174 & -11643.6970581738 \tabularnewline
56 & 245973 & 261435.445277938 & -15462.4452779376 \tabularnewline
57 & 257465 & 250322.620245308 & 7142.37975469249 \tabularnewline
58 & 225875 & 254106.48249825 & -28231.4824982501 \tabularnewline
59 & 241163 & 234578.801162408 & 6584.19883759203 \tabularnewline
60 & 249769 & 237994.819534285 & 11774.1804657154 \tabularnewline
61 & 258388 & 244831.060501135 & 13556.9394988653 \tabularnewline
62 & 245973 & 252842.148155983 & -6869.14815598296 \tabularnewline
63 & 245973 & 247392.346827053 & -1419.34682705265 \tabularnewline
64 & 245973 & 245533.990512556 & 439.009487444477 \tabularnewline
65 & 252642 & 244900.299854274 & 7741.70014572563 \tabularnewline
66 & 243113 & 249079.11709741 & -5966.11709741049 \tabularnewline
67 & 230607 & 244224.417534112 & -13617.4175341119 \tabularnewline
68 & 220142 & 234327.474566187 & -14185.4745661872 \tabularnewline
69 & 227734 & 224056.179310422 & 3677.8206895779 \tabularnewline
70 & 198094 & 225556.88064967 & -27462.8806496701 \tabularnewline
71 & 216255 & 206535.71159025 & 9719.2884097496 \tabularnewline
72 & 226811 & 212017.768911833 & 14793.2310881674 \tabularnewline
73 & 228748 & 220843.578608238 & 7904.42139176244 \tabularnewline
74 & 218192 & 225129.629926994 & -6937.6299269938 \tabularnewline
75 & 219115 & 219634.698785024 & -519.698785024113 \tabularnewline
76 & 216255 & 218369.214812155 & -2114.21481215456 \tabularnewline
77 & 225875 & 216052.937188208 & 9822.06281179207 \tabularnewline
78 & 219115 & 221602.723329897 & -2487.72332989724 \tabularnewline
79 & 205790 & 219040.301815021 & -13250.3018150212 \tabularnewline
80 & 196157 & 209385.289853287 & -13228.2898532873 \tabularnewline
81 & 212446 & 199744.783879103 & 12701.2161208966 \tabularnewline
82 & 177073 & 207191.945755002 & -30118.9457550017 \tabularnewline
83 & 200044 & 186420.417149462 & 13623.5828505385 \tabularnewline
84 & 210509 & 194475.423090256 & 16033.5769097444 \tabularnewline
85 & 210509 & 204118.626586583 & 6390.37341341714 \tabularnewline
86 & 198094 & 207406.913081404 & -9312.91308140414 \tabularnewline
87 & 186615 & 200346.65903537 & -13731.6590353703 \tabularnewline
88 & 185692 & 190374.430374377 & -4682.43037437674 \tabularnewline
89 & 196157 & 186365.686471344 & 9791.31352865588 \tabularnewline
90 & 186615 & 191895.208689094 & -5280.20868909356 \tabularnewline
91 & 168467 & 187492.526031499 & -19025.5260314995 \tabularnewline
92 & 155961 & 174031.613823568 & -18070.6138235679 \tabularnewline
93 & 169390 & 161199.993305627 & 8190.00669437283 \tabularnewline
94 & 137813 & 165674.246698065 & -27861.2466980647 \tabularnewline
95 & 166517 & 146390.552516705 & 20126.447483295 \tabularnewline
96 & 181792 & 158730.977201274 & 23061.0227987261 \tabularnewline
97 & 186615 & 173005.300986006 & 13609.6990139945 \tabularnewline
98 & 176059 & 181051.157412436 & -4992.15741243609 \tabularnewline
99 & 162721 & 176838.301917157 & -14117.3019171573 \tabularnewline
100 & 172263 & 166611.932761575 & 5651.06723842517 \tabularnewline
101 & 176059 & 169413.012968303 & 6645.98703169727 \tabularnewline
102 & 173186 & 172869.75005418 & 316.249945820484 \tabularnewline
103 & 144469 & 172155.160273686 & -27686.1602736865 \tabularnewline
104 & 131144 & 152986.848879327 & -21842.8488793267 \tabularnewline
105 & 140673 & 137669.307505454 & 3003.69249454624 \tabularnewline
106 & 111969 & 138725.755155621 & -26756.7551556208 \tabularnewline
107 & 141609 & 120169.926157628 & 21439.0738423723 \tabularnewline
108 & 152165 & 133375.377860355 & 18789.6221396447 \tabularnewline
109 & 160771 & 144834.828280755 & 15936.1717192446 \tabularnewline
110 & 146419 & 154413.841292937 & -7994.84129293723 \tabularnewline
111 & 132990 & 148222.202828948 & -15232.2028289476 \tabularnewline
112 & 140673 & 137261.108666055 & 3411.8913339448 \tabularnewline
113 & 144469 & 138586.561294234 & 5882.43870576634 \tabularnewline
114 & 136877 & 141540.116399166 & -4663.11639916626 \tabularnewline
115 & 108173 & 137544.100497723 & -29371.1004977234 \tabularnewline
116 & 95667 & 117265.405476146 & -21598.4054761456 \tabularnewline
117 & 107146 & 102108.953468413 & 5037.0465315874 \tabularnewline
118 & 75569 & 104505.391106865 & -28936.3911068647 \tabularnewline
119 & 110019 & 84513.1716428892 & 25505.8283571108 \tabularnewline
120 & 131144 & 100398.6339268 & 30745.3660731997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307326&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]3[/C][C]245973[/C][C]245986[/C][C]-13[/C][/ROW]
[ROW][C]4[/C][C]244036[/C][C]245054.432938126[/C][C]-1018.43293812568[/C][/ROW]
[ROW][C]5[/C][C]263198[/C][C]243460.280784606[/C][C]19737.719215394[/C][/ROW]
[ROW][C]6[/C][C]262184[/C][C]255544.531690452[/C][C]6639.46830954819[/C][/ROW]
[ROW][C]7[/C][C]247832[/C][C]258996.972907406[/C][C]-11164.9729074061[/C][/ROW]
[ROW][C]8[/C][C]238290[/C][C]250716.202621043[/C][C]-12426.2026210431[/C][/ROW]
[ROW][C]9[/C][C]239213[/C][C]241604.275950492[/C][C]-2391.27595049213[/C][/ROW]
[ROW][C]10[/C][C]239213[/C][C]239105.413717691[/C][C]107.586282308679[/C][/ROW]
[ROW][C]11[/C][C]240240[/C][C]238253.313589796[/C][C]1986.68641020363[/C][/ROW]
[ROW][C]12[/C][C]242086[/C][C]238639.549389878[/C][C]3446.450610122[/C][/ROW]
[ROW][C]13[/C][C]244959[/C][C]239987.776745544[/C][C]4971.22325445575[/C][/ROW]
[ROW][C]14[/C][C]244959[/C][C]242340.836531077[/C][C]2618.16346892339[/C][/ROW]
[ROW][C]15[/C][C]243113[/C][C]243143.218718409[/C][C]-30.2187184088689[/C][/ROW]
[ROW][C]16[/C][C]238290[/C][C]242200.30443915[/C][C]-3910.30443914956[/C][/ROW]
[ROW][C]17[/C][C]263198[/C][C]238700.395202413[/C][C]24497.604797587[/C][/ROW]
[ROW][C]18[/C][C]266994[/C][C]253921.433361895[/C][C]13072.5666381048[/C][/ROW]
[ROW][C]19[/C][C]261261[/C][C]261613.3169961[/C][C]-352.316996099544[/C][/ROW]
[ROW][C]20[/C][C]247832[/C][C]260458.138418795[/C][C]-12626.1384187953[/C][/ROW]
[ROW][C]21[/C][C]253578[/C][C]251214.453105919[/C][C]2363.54689408126[/C][/ROW]
[ROW][C]22[/C][C]244959[/C][C]251849.041758567[/C][C]-6890.04175856663[/C][/ROW]
[ROW][C]23[/C][C]248846[/C][C]246385.471446089[/C][C]2460.5285539107[/C][/ROW]
[ROW][C]24[/C][C]250705[/C][C]247083.971474155[/C][C]3621.02852584497[/C][/ROW]
[ROW][C]25[/C][C]252642[/C][C]248547.246507197[/C][C]4094.75349280285[/C][/ROW]
[ROW][C]26[/C][C]247832[/C][C]250322.708548188[/C][C]-2490.70854818792[/C][/ROW]
[ROW][C]27[/C][C]248846[/C][C]247758.31976025[/C][C]1087.68023975004[/C][/ROW]
[ROW][C]28[/C][C]242086[/C][C]247552.106215127[/C][C]-5466.10621512693[/C][/ROW]
[ROW][C]29[/C][C]263198[/C][C]243026.916203086[/C][C]20171.0837969139[/C][/ROW]
[ROW][C]30[/C][C]269867[/C][C]255396.756430779[/C][C]14470.2435692208[/C][/ROW]
[ROW][C]31[/C][C]264134[/C][C]264009.715814919[/C][C]124.284185080789[/C][/ROW]
[ROW][C]32[/C][C]253578[/C][C]263168.619684426[/C][C]-9590.61968442576[/C][/ROW]
[ROW][C]33[/C][C]265057[/C][C]255925.355665239[/C][C]9131.64433476119[/C][/ROW]
[ROW][C]34[/C][C]252642[/C][C]261020.152744475[/C][C]-8378.15274447514[/C][/ROW]
[ROW][C]35[/C][C]264134[/C][C]254575.910209527[/C][C]9558.08979047264[/C][/ROW]
[ROW][C]36[/C][C]263198[/C][C]259951.736873771[/C][C]3246.26312622882[/C][/ROW]
[ROW][C]37[/C][C]266071[/C][C]261168.039724747[/C][C]4902.96027525296[/C][/ROW]
[ROW][C]38[/C][C]255515[/C][C]263476.113882083[/C][C]-7961.11388208286[/C][/ROW]
[ROW][C]39[/C][C]266994[/C][C]257306.701942374[/C][C]9687.298057626[/C][/ROW]
[ROW][C]40[/C][C]266071[/C][C]262767.677469647[/C][C]3303.32253035333[/C][/ROW]
[ROW][C]41[/C][C]283296[/C][C]264021.582739518[/C][C]19274.4172604816[/C][/ROW]
[ROW][C]42[/C][C]279409[/C][C]275800.515451962[/C][C]3608.48454803752[/C][/ROW]
[ROW][C]43[/C][C]264134[/C][C]277255.523943926[/C][C]-13121.5239439256[/C][/ROW]
[ROW][C]44[/C][C]256438[/C][C]267685.37721217[/C][C]-11247.37721217[/C][/ROW]
[ROW][C]45[/C][C]266994[/C][C]259350.302096759[/C][C]7643.6979032408[/C][/ROW]
[ROW][C]46[/C][C]252642[/C][C]263464.53539565[/C][C]-10822.5353956501[/C][/ROW]
[ROW][C]47[/C][C]263198[/C][C]255409.433059387[/C][C]7788.56694061309[/C][/ROW]
[ROW][C]48[/C][C]265057[/C][C]259619.135743419[/C][C]5437.86425658071[/C][/ROW]
[ROW][C]49[/C][C]268944[/C][C]262279.714170359[/C][C]6664.28582964116[/C][/ROW]
[ROW][C]50[/C][C]260338[/C][C]265748.510251175[/C][C]-5410.51025117491[/C][/ROW]
[ROW][C]51[/C][C]265057[/C][C]261259.958243991[/C][C]3797.04175600916[/C][/ROW]
[ROW][C]52[/C][C]267930[/C][C]262839.226833457[/C][C]5090.77316654287[/C][/ROW]
[ROW][C]53[/C][C]278486[/C][C]265271.07058006[/C][C]13214.9294199399[/C][/ROW]
[ROW][C]54[/C][C]269867[/C][C]273056.771965078[/C][C]-3189.77196507831[/C][/ROW]
[ROW][C]55[/C][C]258388[/C][C]270031.697058174[/C][C]-11643.6970581738[/C][/ROW]
[ROW][C]56[/C][C]245973[/C][C]261435.445277938[/C][C]-15462.4452779376[/C][/ROW]
[ROW][C]57[/C][C]257465[/C][C]250322.620245308[/C][C]7142.37975469249[/C][/ROW]
[ROW][C]58[/C][C]225875[/C][C]254106.48249825[/C][C]-28231.4824982501[/C][/ROW]
[ROW][C]59[/C][C]241163[/C][C]234578.801162408[/C][C]6584.19883759203[/C][/ROW]
[ROW][C]60[/C][C]249769[/C][C]237994.819534285[/C][C]11774.1804657154[/C][/ROW]
[ROW][C]61[/C][C]258388[/C][C]244831.060501135[/C][C]13556.9394988653[/C][/ROW]
[ROW][C]62[/C][C]245973[/C][C]252842.148155983[/C][C]-6869.14815598296[/C][/ROW]
[ROW][C]63[/C][C]245973[/C][C]247392.346827053[/C][C]-1419.34682705265[/C][/ROW]
[ROW][C]64[/C][C]245973[/C][C]245533.990512556[/C][C]439.009487444477[/C][/ROW]
[ROW][C]65[/C][C]252642[/C][C]244900.299854274[/C][C]7741.70014572563[/C][/ROW]
[ROW][C]66[/C][C]243113[/C][C]249079.11709741[/C][C]-5966.11709741049[/C][/ROW]
[ROW][C]67[/C][C]230607[/C][C]244224.417534112[/C][C]-13617.4175341119[/C][/ROW]
[ROW][C]68[/C][C]220142[/C][C]234327.474566187[/C][C]-14185.4745661872[/C][/ROW]
[ROW][C]69[/C][C]227734[/C][C]224056.179310422[/C][C]3677.8206895779[/C][/ROW]
[ROW][C]70[/C][C]198094[/C][C]225556.88064967[/C][C]-27462.8806496701[/C][/ROW]
[ROW][C]71[/C][C]216255[/C][C]206535.71159025[/C][C]9719.2884097496[/C][/ROW]
[ROW][C]72[/C][C]226811[/C][C]212017.768911833[/C][C]14793.2310881674[/C][/ROW]
[ROW][C]73[/C][C]228748[/C][C]220843.578608238[/C][C]7904.42139176244[/C][/ROW]
[ROW][C]74[/C][C]218192[/C][C]225129.629926994[/C][C]-6937.6299269938[/C][/ROW]
[ROW][C]75[/C][C]219115[/C][C]219634.698785024[/C][C]-519.698785024113[/C][/ROW]
[ROW][C]76[/C][C]216255[/C][C]218369.214812155[/C][C]-2114.21481215456[/C][/ROW]
[ROW][C]77[/C][C]225875[/C][C]216052.937188208[/C][C]9822.06281179207[/C][/ROW]
[ROW][C]78[/C][C]219115[/C][C]221602.723329897[/C][C]-2487.72332989724[/C][/ROW]
[ROW][C]79[/C][C]205790[/C][C]219040.301815021[/C][C]-13250.3018150212[/C][/ROW]
[ROW][C]80[/C][C]196157[/C][C]209385.289853287[/C][C]-13228.2898532873[/C][/ROW]
[ROW][C]81[/C][C]212446[/C][C]199744.783879103[/C][C]12701.2161208966[/C][/ROW]
[ROW][C]82[/C][C]177073[/C][C]207191.945755002[/C][C]-30118.9457550017[/C][/ROW]
[ROW][C]83[/C][C]200044[/C][C]186420.417149462[/C][C]13623.5828505385[/C][/ROW]
[ROW][C]84[/C][C]210509[/C][C]194475.423090256[/C][C]16033.5769097444[/C][/ROW]
[ROW][C]85[/C][C]210509[/C][C]204118.626586583[/C][C]6390.37341341714[/C][/ROW]
[ROW][C]86[/C][C]198094[/C][C]207406.913081404[/C][C]-9312.91308140414[/C][/ROW]
[ROW][C]87[/C][C]186615[/C][C]200346.65903537[/C][C]-13731.6590353703[/C][/ROW]
[ROW][C]88[/C][C]185692[/C][C]190374.430374377[/C][C]-4682.43037437674[/C][/ROW]
[ROW][C]89[/C][C]196157[/C][C]186365.686471344[/C][C]9791.31352865588[/C][/ROW]
[ROW][C]90[/C][C]186615[/C][C]191895.208689094[/C][C]-5280.20868909356[/C][/ROW]
[ROW][C]91[/C][C]168467[/C][C]187492.526031499[/C][C]-19025.5260314995[/C][/ROW]
[ROW][C]92[/C][C]155961[/C][C]174031.613823568[/C][C]-18070.6138235679[/C][/ROW]
[ROW][C]93[/C][C]169390[/C][C]161199.993305627[/C][C]8190.00669437283[/C][/ROW]
[ROW][C]94[/C][C]137813[/C][C]165674.246698065[/C][C]-27861.2466980647[/C][/ROW]
[ROW][C]95[/C][C]166517[/C][C]146390.552516705[/C][C]20126.447483295[/C][/ROW]
[ROW][C]96[/C][C]181792[/C][C]158730.977201274[/C][C]23061.0227987261[/C][/ROW]
[ROW][C]97[/C][C]186615[/C][C]173005.300986006[/C][C]13609.6990139945[/C][/ROW]
[ROW][C]98[/C][C]176059[/C][C]181051.157412436[/C][C]-4992.15741243609[/C][/ROW]
[ROW][C]99[/C][C]162721[/C][C]176838.301917157[/C][C]-14117.3019171573[/C][/ROW]
[ROW][C]100[/C][C]172263[/C][C]166611.932761575[/C][C]5651.06723842517[/C][/ROW]
[ROW][C]101[/C][C]176059[/C][C]169413.012968303[/C][C]6645.98703169727[/C][/ROW]
[ROW][C]102[/C][C]173186[/C][C]172869.75005418[/C][C]316.249945820484[/C][/ROW]
[ROW][C]103[/C][C]144469[/C][C]172155.160273686[/C][C]-27686.1602736865[/C][/ROW]
[ROW][C]104[/C][C]131144[/C][C]152986.848879327[/C][C]-21842.8488793267[/C][/ROW]
[ROW][C]105[/C][C]140673[/C][C]137669.307505454[/C][C]3003.69249454624[/C][/ROW]
[ROW][C]106[/C][C]111969[/C][C]138725.755155621[/C][C]-26756.7551556208[/C][/ROW]
[ROW][C]107[/C][C]141609[/C][C]120169.926157628[/C][C]21439.0738423723[/C][/ROW]
[ROW][C]108[/C][C]152165[/C][C]133375.377860355[/C][C]18789.6221396447[/C][/ROW]
[ROW][C]109[/C][C]160771[/C][C]144834.828280755[/C][C]15936.1717192446[/C][/ROW]
[ROW][C]110[/C][C]146419[/C][C]154413.841292937[/C][C]-7994.84129293723[/C][/ROW]
[ROW][C]111[/C][C]132990[/C][C]148222.202828948[/C][C]-15232.2028289476[/C][/ROW]
[ROW][C]112[/C][C]140673[/C][C]137261.108666055[/C][C]3411.8913339448[/C][/ROW]
[ROW][C]113[/C][C]144469[/C][C]138586.561294234[/C][C]5882.43870576634[/C][/ROW]
[ROW][C]114[/C][C]136877[/C][C]141540.116399166[/C][C]-4663.11639916626[/C][/ROW]
[ROW][C]115[/C][C]108173[/C][C]137544.100497723[/C][C]-29371.1004977234[/C][/ROW]
[ROW][C]116[/C][C]95667[/C][C]117265.405476146[/C][C]-21598.4054761456[/C][/ROW]
[ROW][C]117[/C][C]107146[/C][C]102108.953468413[/C][C]5037.0465315874[/C][/ROW]
[ROW][C]118[/C][C]75569[/C][C]104505.391106865[/C][C]-28936.3911068647[/C][/ROW]
[ROW][C]119[/C][C]110019[/C][C]84513.1716428892[/C][C]25505.8283571108[/C][/ROW]
[ROW][C]120[/C][C]131144[/C][C]100398.6339268[/C][C]30745.3660731997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307326&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307326&T=2

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


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

Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
3245973245986-13
4244036245054.432938126-1018.43293812568
5263198243460.28078460619737.719215394
6262184255544.5316904526639.46830954819
7247832258996.972907406-11164.9729074061
8238290250716.202621043-12426.2026210431
9239213241604.275950492-2391.27595049213
10239213239105.413717691107.586282308679
11240240238253.3135897961986.68641020363
12242086238639.5493898783446.450610122
13244959239987.7767455444971.22325445575
14244959242340.8365310772618.16346892339
15243113243143.218718409-30.2187184088689
16238290242200.30443915-3910.30443914956
17263198238700.39520241324497.604797587
18266994253921.43336189513072.5666381048
19261261261613.3169961-352.316996099544
20247832260458.138418795-12626.1384187953
21253578251214.4531059192363.54689408126
22244959251849.041758567-6890.04175856663
23248846246385.4714460892460.5285539107
24250705247083.9714741553621.02852584497
25252642248547.2465071974094.75349280285
26247832250322.708548188-2490.70854818792
27248846247758.319760251087.68023975004
28242086247552.106215127-5466.10621512693
29263198243026.91620308620171.0837969139
30269867255396.75643077914470.2435692208
31264134264009.715814919124.284185080789
32253578263168.619684426-9590.61968442576
33265057255925.3556652399131.64433476119
34252642261020.152744475-8378.15274447514
35264134254575.9102095279558.08979047264
36263198259951.7368737713246.26312622882
37266071261168.0397247474902.96027525296
38255515263476.113882083-7961.11388208286
39266994257306.7019423749687.298057626
40266071262767.6774696473303.32253035333
41283296264021.58273951819274.4172604816
42279409275800.5154519623608.48454803752
43264134277255.523943926-13121.5239439256
44256438267685.37721217-11247.37721217
45266994259350.3020967597643.6979032408
46252642263464.53539565-10822.5353956501
47263198255409.4330593877788.56694061309
48265057259619.1357434195437.86425658071
49268944262279.7141703596664.28582964116
50260338265748.510251175-5410.51025117491
51265057261259.9582439913797.04175600916
52267930262839.2268334575090.77316654287
53278486265271.0705800613214.9294199399
54269867273056.771965078-3189.77196507831
55258388270031.697058174-11643.6970581738
56245973261435.445277938-15462.4452779376
57257465250322.6202453087142.37975469249
58225875254106.48249825-28231.4824982501
59241163234578.8011624086584.19883759203
60249769237994.81953428511774.1804657154
61258388244831.06050113513556.9394988653
62245973252842.148155983-6869.14815598296
63245973247392.346827053-1419.34682705265
64245973245533.990512556439.009487444477
65252642244900.2998542747741.70014572563
66243113249079.11709741-5966.11709741049
67230607244224.417534112-13617.4175341119
68220142234327.474566187-14185.4745661872
69227734224056.1793104223677.8206895779
70198094225556.88064967-27462.8806496701
71216255206535.711590259719.2884097496
72226811212017.76891183314793.2310881674
73228748220843.5786082387904.42139176244
74218192225129.629926994-6937.6299269938
75219115219634.698785024-519.698785024113
76216255218369.214812155-2114.21481215456
77225875216052.9371882089822.06281179207
78219115221602.723329897-2487.72332989724
79205790219040.301815021-13250.3018150212
80196157209385.289853287-13228.2898532873
81212446199744.78387910312701.2161208966
82177073207191.945755002-30118.9457550017
83200044186420.41714946213623.5828505385
84210509194475.42309025616033.5769097444
85210509204118.6265865836390.37341341714
86198094207406.913081404-9312.91308140414
87186615200346.65903537-13731.6590353703
88185692190374.430374377-4682.43037437674
89196157186365.6864713449791.31352865588
90186615191895.208689094-5280.20868909356
91168467187492.526031499-19025.5260314995
92155961174031.613823568-18070.6138235679
93169390161199.9933056278190.00669437283
94137813165674.246698065-27861.2466980647
95166517146390.55251670520126.447483295
96181792158730.97720127423061.0227987261
97186615173005.30098600613609.6990139945
98176059181051.157412436-4992.15741243609
99162721176838.301917157-14117.3019171573
100172263166611.9327615755651.06723842517
101176059169413.0129683036645.98703169727
102173186172869.75005418316.249945820484
103144469172155.160273686-27686.1602736865
104131144152986.848879327-21842.8488793267
105140673137669.3075054543003.69249454624
106111969138725.755155621-26756.7551556208
107141609120169.92615762821439.0738423723
108152165133375.37786035518789.6221396447
109160771144834.82828075515936.1717192446
110146419154413.841292937-7994.84129293723
111132990148222.202828948-15232.2028289476
112140673137261.1086660553411.8913339448
113144469138586.5612942345882.43870576634
114136877141540.116399166-4663.11639916626
115108173137544.100497723-29371.1004977234
11695667117265.405476146-21598.4054761456
117107146102108.9534684135037.0465315874
11875569104505.391106865-28936.3911068647
11911001984513.171642889225505.8283571108
120131144100398.633926830745.3660731997






Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
121119736.97650351994034.4208571322145439.532149907
122118813.97650351988032.1503930949149595.802613944
123117890.97650351982756.6589403563153025.294066682
124116967.97650351977963.8777116492155972.07529539
125116044.97650351973521.8160553265158568.136951712
126115121.97650351969349.5106922969160894.442314742
127114198.97650351965393.0539287302163004.899078309
128113275.97650351961614.4092575182164937.54374952
129112352.97650351957985.5507574913166720.402249547
130111429.97650351954485.1221777187168374.83082932
131110506.97650351951096.4060120366169917.546995002
132109583.97650351947806.0246269783171361.92838006

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
121 & 119736.976503519 & 94034.4208571322 & 145439.532149907 \tabularnewline
122 & 118813.976503519 & 88032.1503930949 & 149595.802613944 \tabularnewline
123 & 117890.976503519 & 82756.6589403563 & 153025.294066682 \tabularnewline
124 & 116967.976503519 & 77963.8777116492 & 155972.07529539 \tabularnewline
125 & 116044.976503519 & 73521.8160553265 & 158568.136951712 \tabularnewline
126 & 115121.976503519 & 69349.5106922969 & 160894.442314742 \tabularnewline
127 & 114198.976503519 & 65393.0539287302 & 163004.899078309 \tabularnewline
128 & 113275.976503519 & 61614.4092575182 & 164937.54374952 \tabularnewline
129 & 112352.976503519 & 57985.5507574913 & 166720.402249547 \tabularnewline
130 & 111429.976503519 & 54485.1221777187 & 168374.83082932 \tabularnewline
131 & 110506.976503519 & 51096.4060120366 & 169917.546995002 \tabularnewline
132 & 109583.976503519 & 47806.0246269783 & 171361.92838006 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307326&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]119736.976503519[/C][C]94034.4208571322[/C][C]145439.532149907[/C][/ROW]
[ROW][C]122[/C][C]118813.976503519[/C][C]88032.1503930949[/C][C]149595.802613944[/C][/ROW]
[ROW][C]123[/C][C]117890.976503519[/C][C]82756.6589403563[/C][C]153025.294066682[/C][/ROW]
[ROW][C]124[/C][C]116967.976503519[/C][C]77963.8777116492[/C][C]155972.07529539[/C][/ROW]
[ROW][C]125[/C][C]116044.976503519[/C][C]73521.8160553265[/C][C]158568.136951712[/C][/ROW]
[ROW][C]126[/C][C]115121.976503519[/C][C]69349.5106922969[/C][C]160894.442314742[/C][/ROW]
[ROW][C]127[/C][C]114198.976503519[/C][C]65393.0539287302[/C][C]163004.899078309[/C][/ROW]
[ROW][C]128[/C][C]113275.976503519[/C][C]61614.4092575182[/C][C]164937.54374952[/C][/ROW]
[ROW][C]129[/C][C]112352.976503519[/C][C]57985.5507574913[/C][C]166720.402249547[/C][/ROW]
[ROW][C]130[/C][C]111429.976503519[/C][C]54485.1221777187[/C][C]168374.83082932[/C][/ROW]
[ROW][C]131[/C][C]110506.976503519[/C][C]51096.4060120366[/C][C]169917.546995002[/C][/ROW]
[ROW][C]132[/C][C]109583.976503519[/C][C]47806.0246269783[/C][C]171361.92838006[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307326&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307326&T=3

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


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

Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
121119736.97650351994034.4208571322145439.532149907
122118813.97650351988032.1503930949149595.802613944
123117890.97650351982756.6589403563153025.294066682
124116967.97650351977963.8777116492155972.07529539
125116044.97650351973521.8160553265158568.136951712
126115121.97650351969349.5106922969160894.442314742
127114198.97650351965393.0539287302163004.899078309
128113275.97650351961614.4092575182164937.54374952
129112352.97650351957985.5507574913166720.402249547
130111429.97650351954485.1221777187168374.83082932
131110506.97650351951096.4060120366169917.546995002
132109583.97650351947806.0246269783171361.92838006


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 12 ; par2 = Double ; par3 = additive ; par4 = 12 ;
R code (references can be found in the software module):
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')