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Author's title

Author*Unverified author*
R Software Modulerwasp_exponentialsmoothing.wasp
Title produced by softwareExponential Smoothing
Date of computationFri, 21 Dec 2012 04:37:14 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/21/t1356082646bc0xb7w9gke5czh.htm/, Retrieved Thu, 25 Apr 2024 01:46:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203380, Retrieved Thu, 25 Apr 2024 01:46:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Exponential Smoothing] [] [2012-12-21 08:56:25] [2f0f353a58a70fd7baf0f5141860d820]
- R PD    [Exponential Smoothing] [] [2012-12-21 09:37:14] [492ce95363299443ae43b669aa70c778] [Current]
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Dataseries X:
1.26
1.26
1.28
1.34
1.39
1.47
1.57
1.63
1.72
1.43
1.35
1.41
1.44
1.43
1.43
1.42
1.45
1.51
1.48
1.48
1.45
1.38
1.46
1.45
1.41
1.45
1.47
1.47
1.53
1.56
1.66
1.79
1.78
1.46
1.41
1.43
1.43
1.45
1.35
1.35
1.29
1.29
1.26
1.3
1.3
1.16
1.24
1.15
1.21
1.22
1.17
1.13
1.15
1.2
1.23
1.25
1.38
1.28
1.26
1.25
1.26
1.28
1.31
1.22
1.23
1.36
1.54
1.58
1.44
1.29
1.28
1.23




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203380&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203380&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203380&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Estimated Parameters of Exponential Smoothing
ParameterValue
alpha1
beta0
gammaFALSE

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 1 \tabularnewline
beta & 0 \tabularnewline
gamma & FALSE \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203380&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]1[/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=203380&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203380&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
alpha1
beta0
gammaFALSE







Interpolation Forecasts of Exponential Smoothing
tObservedFittedResiduals
31.281.260.02
41.341.280.0600000000000001
51.391.340.0499999999999998
61.471.390.0800000000000001
71.571.470.1
81.631.570.0599999999999998
91.721.630.0900000000000001
101.431.72-0.29
111.351.43-0.0799999999999998
121.411.350.0599999999999998
131.441.410.03
141.431.44-0.01
151.431.430
161.421.43-0.01
171.451.420.03
181.511.450.0600000000000001
191.481.51-0.03
201.481.480
211.451.48-0.03
221.381.45-0.0700000000000001
231.461.380.0800000000000001
241.451.46-0.01
251.411.45-0.04
261.451.410.04
271.471.450.02
281.471.470
291.531.470.0600000000000001
301.561.530.03
311.661.560.0999999999999999
321.791.660.13
331.781.79-0.01
341.461.78-0.32
351.411.46-0.05
361.431.410.02
371.431.430
381.451.430.02
391.351.45-0.0999999999999999
401.351.350
411.291.35-0.0600000000000001
421.291.290
431.261.29-0.03
441.31.260.04
451.31.30
461.161.3-0.14
471.241.160.0800000000000001
481.151.24-0.0900000000000001
491.211.150.0600000000000001
501.221.210.01
511.171.22-0.05
521.131.17-0.04
531.151.130.02
541.21.150.05
551.231.20.03
561.251.230.02
571.381.250.13
581.281.38-0.0999999999999999
591.261.28-0.02
601.251.26-0.01
611.261.250.01
621.281.260.02
631.311.280.03
641.221.31-0.0900000000000001
651.231.220.01
661.361.230.13
671.541.360.18
681.581.540.04
691.441.58-0.14
701.291.44-0.15
711.281.29-0.01
721.231.28-0.05

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
3 & 1.28 & 1.26 & 0.02 \tabularnewline
4 & 1.34 & 1.28 & 0.0600000000000001 \tabularnewline
5 & 1.39 & 1.34 & 0.0499999999999998 \tabularnewline
6 & 1.47 & 1.39 & 0.0800000000000001 \tabularnewline
7 & 1.57 & 1.47 & 0.1 \tabularnewline
8 & 1.63 & 1.57 & 0.0599999999999998 \tabularnewline
9 & 1.72 & 1.63 & 0.0900000000000001 \tabularnewline
10 & 1.43 & 1.72 & -0.29 \tabularnewline
11 & 1.35 & 1.43 & -0.0799999999999998 \tabularnewline
12 & 1.41 & 1.35 & 0.0599999999999998 \tabularnewline
13 & 1.44 & 1.41 & 0.03 \tabularnewline
14 & 1.43 & 1.44 & -0.01 \tabularnewline
15 & 1.43 & 1.43 & 0 \tabularnewline
16 & 1.42 & 1.43 & -0.01 \tabularnewline
17 & 1.45 & 1.42 & 0.03 \tabularnewline
18 & 1.51 & 1.45 & 0.0600000000000001 \tabularnewline
19 & 1.48 & 1.51 & -0.03 \tabularnewline
20 & 1.48 & 1.48 & 0 \tabularnewline
21 & 1.45 & 1.48 & -0.03 \tabularnewline
22 & 1.38 & 1.45 & -0.0700000000000001 \tabularnewline
23 & 1.46 & 1.38 & 0.0800000000000001 \tabularnewline
24 & 1.45 & 1.46 & -0.01 \tabularnewline
25 & 1.41 & 1.45 & -0.04 \tabularnewline
26 & 1.45 & 1.41 & 0.04 \tabularnewline
27 & 1.47 & 1.45 & 0.02 \tabularnewline
28 & 1.47 & 1.47 & 0 \tabularnewline
29 & 1.53 & 1.47 & 0.0600000000000001 \tabularnewline
30 & 1.56 & 1.53 & 0.03 \tabularnewline
31 & 1.66 & 1.56 & 0.0999999999999999 \tabularnewline
32 & 1.79 & 1.66 & 0.13 \tabularnewline
33 & 1.78 & 1.79 & -0.01 \tabularnewline
34 & 1.46 & 1.78 & -0.32 \tabularnewline
35 & 1.41 & 1.46 & -0.05 \tabularnewline
36 & 1.43 & 1.41 & 0.02 \tabularnewline
37 & 1.43 & 1.43 & 0 \tabularnewline
38 & 1.45 & 1.43 & 0.02 \tabularnewline
39 & 1.35 & 1.45 & -0.0999999999999999 \tabularnewline
40 & 1.35 & 1.35 & 0 \tabularnewline
41 & 1.29 & 1.35 & -0.0600000000000001 \tabularnewline
42 & 1.29 & 1.29 & 0 \tabularnewline
43 & 1.26 & 1.29 & -0.03 \tabularnewline
44 & 1.3 & 1.26 & 0.04 \tabularnewline
45 & 1.3 & 1.3 & 0 \tabularnewline
46 & 1.16 & 1.3 & -0.14 \tabularnewline
47 & 1.24 & 1.16 & 0.0800000000000001 \tabularnewline
48 & 1.15 & 1.24 & -0.0900000000000001 \tabularnewline
49 & 1.21 & 1.15 & 0.0600000000000001 \tabularnewline
50 & 1.22 & 1.21 & 0.01 \tabularnewline
51 & 1.17 & 1.22 & -0.05 \tabularnewline
52 & 1.13 & 1.17 & -0.04 \tabularnewline
53 & 1.15 & 1.13 & 0.02 \tabularnewline
54 & 1.2 & 1.15 & 0.05 \tabularnewline
55 & 1.23 & 1.2 & 0.03 \tabularnewline
56 & 1.25 & 1.23 & 0.02 \tabularnewline
57 & 1.38 & 1.25 & 0.13 \tabularnewline
58 & 1.28 & 1.38 & -0.0999999999999999 \tabularnewline
59 & 1.26 & 1.28 & -0.02 \tabularnewline
60 & 1.25 & 1.26 & -0.01 \tabularnewline
61 & 1.26 & 1.25 & 0.01 \tabularnewline
62 & 1.28 & 1.26 & 0.02 \tabularnewline
63 & 1.31 & 1.28 & 0.03 \tabularnewline
64 & 1.22 & 1.31 & -0.0900000000000001 \tabularnewline
65 & 1.23 & 1.22 & 0.01 \tabularnewline
66 & 1.36 & 1.23 & 0.13 \tabularnewline
67 & 1.54 & 1.36 & 0.18 \tabularnewline
68 & 1.58 & 1.54 & 0.04 \tabularnewline
69 & 1.44 & 1.58 & -0.14 \tabularnewline
70 & 1.29 & 1.44 & -0.15 \tabularnewline
71 & 1.28 & 1.29 & -0.01 \tabularnewline
72 & 1.23 & 1.28 & -0.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203380&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]1.28[/C][C]1.26[/C][C]0.02[/C][/ROW]
[ROW][C]4[/C][C]1.34[/C][C]1.28[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]5[/C][C]1.39[/C][C]1.34[/C][C]0.0499999999999998[/C][/ROW]
[ROW][C]6[/C][C]1.47[/C][C]1.39[/C][C]0.0800000000000001[/C][/ROW]
[ROW][C]7[/C][C]1.57[/C][C]1.47[/C][C]0.1[/C][/ROW]
[ROW][C]8[/C][C]1.63[/C][C]1.57[/C][C]0.0599999999999998[/C][/ROW]
[ROW][C]9[/C][C]1.72[/C][C]1.63[/C][C]0.0900000000000001[/C][/ROW]
[ROW][C]10[/C][C]1.43[/C][C]1.72[/C][C]-0.29[/C][/ROW]
[ROW][C]11[/C][C]1.35[/C][C]1.43[/C][C]-0.0799999999999998[/C][/ROW]
[ROW][C]12[/C][C]1.41[/C][C]1.35[/C][C]0.0599999999999998[/C][/ROW]
[ROW][C]13[/C][C]1.44[/C][C]1.41[/C][C]0.03[/C][/ROW]
[ROW][C]14[/C][C]1.43[/C][C]1.44[/C][C]-0.01[/C][/ROW]
[ROW][C]15[/C][C]1.43[/C][C]1.43[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]1.42[/C][C]1.43[/C][C]-0.01[/C][/ROW]
[ROW][C]17[/C][C]1.45[/C][C]1.42[/C][C]0.03[/C][/ROW]
[ROW][C]18[/C][C]1.51[/C][C]1.45[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]19[/C][C]1.48[/C][C]1.51[/C][C]-0.03[/C][/ROW]
[ROW][C]20[/C][C]1.48[/C][C]1.48[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]1.45[/C][C]1.48[/C][C]-0.03[/C][/ROW]
[ROW][C]22[/C][C]1.38[/C][C]1.45[/C][C]-0.0700000000000001[/C][/ROW]
[ROW][C]23[/C][C]1.46[/C][C]1.38[/C][C]0.0800000000000001[/C][/ROW]
[ROW][C]24[/C][C]1.45[/C][C]1.46[/C][C]-0.01[/C][/ROW]
[ROW][C]25[/C][C]1.41[/C][C]1.45[/C][C]-0.04[/C][/ROW]
[ROW][C]26[/C][C]1.45[/C][C]1.41[/C][C]0.04[/C][/ROW]
[ROW][C]27[/C][C]1.47[/C][C]1.45[/C][C]0.02[/C][/ROW]
[ROW][C]28[/C][C]1.47[/C][C]1.47[/C][C]0[/C][/ROW]
[ROW][C]29[/C][C]1.53[/C][C]1.47[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]30[/C][C]1.56[/C][C]1.53[/C][C]0.03[/C][/ROW]
[ROW][C]31[/C][C]1.66[/C][C]1.56[/C][C]0.0999999999999999[/C][/ROW]
[ROW][C]32[/C][C]1.79[/C][C]1.66[/C][C]0.13[/C][/ROW]
[ROW][C]33[/C][C]1.78[/C][C]1.79[/C][C]-0.01[/C][/ROW]
[ROW][C]34[/C][C]1.46[/C][C]1.78[/C][C]-0.32[/C][/ROW]
[ROW][C]35[/C][C]1.41[/C][C]1.46[/C][C]-0.05[/C][/ROW]
[ROW][C]36[/C][C]1.43[/C][C]1.41[/C][C]0.02[/C][/ROW]
[ROW][C]37[/C][C]1.43[/C][C]1.43[/C][C]0[/C][/ROW]
[ROW][C]38[/C][C]1.45[/C][C]1.43[/C][C]0.02[/C][/ROW]
[ROW][C]39[/C][C]1.35[/C][C]1.45[/C][C]-0.0999999999999999[/C][/ROW]
[ROW][C]40[/C][C]1.35[/C][C]1.35[/C][C]0[/C][/ROW]
[ROW][C]41[/C][C]1.29[/C][C]1.35[/C][C]-0.0600000000000001[/C][/ROW]
[ROW][C]42[/C][C]1.29[/C][C]1.29[/C][C]0[/C][/ROW]
[ROW][C]43[/C][C]1.26[/C][C]1.29[/C][C]-0.03[/C][/ROW]
[ROW][C]44[/C][C]1.3[/C][C]1.26[/C][C]0.04[/C][/ROW]
[ROW][C]45[/C][C]1.3[/C][C]1.3[/C][C]0[/C][/ROW]
[ROW][C]46[/C][C]1.16[/C][C]1.3[/C][C]-0.14[/C][/ROW]
[ROW][C]47[/C][C]1.24[/C][C]1.16[/C][C]0.0800000000000001[/C][/ROW]
[ROW][C]48[/C][C]1.15[/C][C]1.24[/C][C]-0.0900000000000001[/C][/ROW]
[ROW][C]49[/C][C]1.21[/C][C]1.15[/C][C]0.0600000000000001[/C][/ROW]
[ROW][C]50[/C][C]1.22[/C][C]1.21[/C][C]0.01[/C][/ROW]
[ROW][C]51[/C][C]1.17[/C][C]1.22[/C][C]-0.05[/C][/ROW]
[ROW][C]52[/C][C]1.13[/C][C]1.17[/C][C]-0.04[/C][/ROW]
[ROW][C]53[/C][C]1.15[/C][C]1.13[/C][C]0.02[/C][/ROW]
[ROW][C]54[/C][C]1.2[/C][C]1.15[/C][C]0.05[/C][/ROW]
[ROW][C]55[/C][C]1.23[/C][C]1.2[/C][C]0.03[/C][/ROW]
[ROW][C]56[/C][C]1.25[/C][C]1.23[/C][C]0.02[/C][/ROW]
[ROW][C]57[/C][C]1.38[/C][C]1.25[/C][C]0.13[/C][/ROW]
[ROW][C]58[/C][C]1.28[/C][C]1.38[/C][C]-0.0999999999999999[/C][/ROW]
[ROW][C]59[/C][C]1.26[/C][C]1.28[/C][C]-0.02[/C][/ROW]
[ROW][C]60[/C][C]1.25[/C][C]1.26[/C][C]-0.01[/C][/ROW]
[ROW][C]61[/C][C]1.26[/C][C]1.25[/C][C]0.01[/C][/ROW]
[ROW][C]62[/C][C]1.28[/C][C]1.26[/C][C]0.02[/C][/ROW]
[ROW][C]63[/C][C]1.31[/C][C]1.28[/C][C]0.03[/C][/ROW]
[ROW][C]64[/C][C]1.22[/C][C]1.31[/C][C]-0.0900000000000001[/C][/ROW]
[ROW][C]65[/C][C]1.23[/C][C]1.22[/C][C]0.01[/C][/ROW]
[ROW][C]66[/C][C]1.36[/C][C]1.23[/C][C]0.13[/C][/ROW]
[ROW][C]67[/C][C]1.54[/C][C]1.36[/C][C]0.18[/C][/ROW]
[ROW][C]68[/C][C]1.58[/C][C]1.54[/C][C]0.04[/C][/ROW]
[ROW][C]69[/C][C]1.44[/C][C]1.58[/C][C]-0.14[/C][/ROW]
[ROW][C]70[/C][C]1.29[/C][C]1.44[/C][C]-0.15[/C][/ROW]
[ROW][C]71[/C][C]1.28[/C][C]1.29[/C][C]-0.01[/C][/ROW]
[ROW][C]72[/C][C]1.23[/C][C]1.28[/C][C]-0.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203380&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203380&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
31.281.260.02
41.341.280.0600000000000001
51.391.340.0499999999999998
61.471.390.0800000000000001
71.571.470.1
81.631.570.0599999999999998
91.721.630.0900000000000001
101.431.72-0.29
111.351.43-0.0799999999999998
121.411.350.0599999999999998
131.441.410.03
141.431.44-0.01
151.431.430
161.421.43-0.01
171.451.420.03
181.511.450.0600000000000001
191.481.51-0.03
201.481.480
211.451.48-0.03
221.381.45-0.0700000000000001
231.461.380.0800000000000001
241.451.46-0.01
251.411.45-0.04
261.451.410.04
271.471.450.02
281.471.470
291.531.470.0600000000000001
301.561.530.03
311.661.560.0999999999999999
321.791.660.13
331.781.79-0.01
341.461.78-0.32
351.411.46-0.05
361.431.410.02
371.431.430
381.451.430.02
391.351.45-0.0999999999999999
401.351.350
411.291.35-0.0600000000000001
421.291.290
431.261.29-0.03
441.31.260.04
451.31.30
461.161.3-0.14
471.241.160.0800000000000001
481.151.24-0.0900000000000001
491.211.150.0600000000000001
501.221.210.01
511.171.22-0.05
521.131.17-0.04
531.151.130.02
541.21.150.05
551.231.20.03
561.251.230.02
571.381.250.13
581.281.38-0.0999999999999999
591.261.28-0.02
601.251.26-0.01
611.261.250.01
621.281.260.02
631.311.280.03
641.221.31-0.0900000000000001
651.231.220.01
661.361.230.13
671.541.360.18
681.581.540.04
691.441.58-0.14
701.291.44-0.15
711.281.29-0.01
721.231.28-0.05







Extrapolation Forecasts of Exponential Smoothing
tForecast95% Lower Bound95% Upper Bound
731.231.066002855888581.39399714411142
741.230.9980730146071711.46192698539283
751.230.945948614102821.51405138589718
761.230.9020057117771541.55799428822285
771.230.8632912376510291.59670876234897
781.230.8282906776533351.63170932234666
791.230.7961043409563541.66389565904365
801.230.7661460292143411.69385397078566
811.230.7380085676657311.72199143233427
821.230.7113954948450331.74860450515497
831.230.6860830062925681.77391699370743
841.230.6618972282056411.79810277179436

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
73 & 1.23 & 1.06600285588858 & 1.39399714411142 \tabularnewline
74 & 1.23 & 0.998073014607171 & 1.46192698539283 \tabularnewline
75 & 1.23 & 0.94594861410282 & 1.51405138589718 \tabularnewline
76 & 1.23 & 0.902005711777154 & 1.55799428822285 \tabularnewline
77 & 1.23 & 0.863291237651029 & 1.59670876234897 \tabularnewline
78 & 1.23 & 0.828290677653335 & 1.63170932234666 \tabularnewline
79 & 1.23 & 0.796104340956354 & 1.66389565904365 \tabularnewline
80 & 1.23 & 0.766146029214341 & 1.69385397078566 \tabularnewline
81 & 1.23 & 0.738008567665731 & 1.72199143233427 \tabularnewline
82 & 1.23 & 0.711395494845033 & 1.74860450515497 \tabularnewline
83 & 1.23 & 0.686083006292568 & 1.77391699370743 \tabularnewline
84 & 1.23 & 0.661897228205641 & 1.79810277179436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203380&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]1.23[/C][C]1.06600285588858[/C][C]1.39399714411142[/C][/ROW]
[ROW][C]74[/C][C]1.23[/C][C]0.998073014607171[/C][C]1.46192698539283[/C][/ROW]
[ROW][C]75[/C][C]1.23[/C][C]0.94594861410282[/C][C]1.51405138589718[/C][/ROW]
[ROW][C]76[/C][C]1.23[/C][C]0.902005711777154[/C][C]1.55799428822285[/C][/ROW]
[ROW][C]77[/C][C]1.23[/C][C]0.863291237651029[/C][C]1.59670876234897[/C][/ROW]
[ROW][C]78[/C][C]1.23[/C][C]0.828290677653335[/C][C]1.63170932234666[/C][/ROW]
[ROW][C]79[/C][C]1.23[/C][C]0.796104340956354[/C][C]1.66389565904365[/C][/ROW]
[ROW][C]80[/C][C]1.23[/C][C]0.766146029214341[/C][C]1.69385397078566[/C][/ROW]
[ROW][C]81[/C][C]1.23[/C][C]0.738008567665731[/C][C]1.72199143233427[/C][/ROW]
[ROW][C]82[/C][C]1.23[/C][C]0.711395494845033[/C][C]1.74860450515497[/C][/ROW]
[ROW][C]83[/C][C]1.23[/C][C]0.686083006292568[/C][C]1.77391699370743[/C][/ROW]
[ROW][C]84[/C][C]1.23[/C][C]0.661897228205641[/C][C]1.79810277179436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203380&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203380&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
731.231.066002855888581.39399714411142
741.230.9980730146071711.46192698539283
751.230.945948614102821.51405138589718
761.230.9020057117771541.55799428822285
771.230.8632912376510291.59670876234897
781.230.8282906776533351.63170932234666
791.230.7961043409563541.66389565904365
801.230.7661460292143411.69385397078566
811.230.7380085676657311.72199143233427
821.230.7113954948450331.74860450515497
831.230.6860830062925681.77391699370743
841.230.6618972282056411.79810277179436



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