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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Module
Title produced by softwareARIMA Forecasting
Date of computationFri, 24 Dec 2010 13:50:57 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t1293198527s274sd28d9cx9u7.htm/, Retrieved Fri, 01 May 2026 19:39:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114962, Retrieved Fri, 01 May 2026 19:39:57 +0000
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IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact321

Tree of Dependent Computations

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-       [ARIMA Forecasting] [] [2010-12-24 13:50:57] [afde384c4f4b6cc066f673fee2b73b52] [Current]
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Dataset

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114962&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114962&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114962&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Univariate ARIMA Extrapolation Forecast
timeY[t]F[t]95% LB95% UBp-value(H0: Y[t] = F[t])P(F[t]>Y[t-1])P(F[t]>Y[t-s])P(F[t]>Y[46])
3431555.4-------
3529780.7-------
3625656.6-------
3726193-------
3824095.9-------
3922440.2-------
4025951.7-------
4127634.5-------
4227930.6-------
4331247.3-------
4431823.7-------
4533078.7-------
4634032.4-------
472826532625.768630759.017134492.520200.06990.99860.0699
4825079.529290.402527297.176931283.628200.84330.99980
4924743.530005.393327861.58132149.2055010.99981e-04
5018845.527466.149625041.246829891.052500.98610.99680
5121224.727393.163124811.139829975.1865010.99990
5221920.629655.166926913.099232397.2346010.99599e-04
5322734.130967.034928053.435333880.6345010.98750.0196
5423972.832006.60328947.005435066.2006010.99550.0972
5525671.134116.242530914.146737318.3383010.96050.5205
5625798.134978.651131637.062938320.2392010.96790.7106
5727893.936055.511932582.882339528.1414010.95350.8732
5829557.837532.323233932.675841131.9707010.97170.9717
5927541.735982.002831939.98840024.017600.99910.99990.8278
6026470.132370.59528130.679136610.51090.00320.98720.99960.2212
6125185.133290.110828848.258337731.96322e-040.99870.99990.3716
6223363.830831.399426146.887735515.91129e-040.990910.0902
6324300.230330.878125450.019235211.7370.00770.99740.99990.0686
6425905.732650.069727575.739337724.40.00460.999410.2967
6529036.833966.35528697.80439234.9060.03330.998610.4902
6632866.535061.300529611.730540510.87050.21490.984910.6443
673326037267.805831641.759642893.8520.08130.937410.8702
6835288.537754.735631956.339643553.13150.20220.935710.8958
6934999.238846.83532882.238144811.4320.10310.87890.99980.9432
7034820.240404.071434277.470946530.6720.0370.95810.99970.9792

\begin{tabular}{lllllllll}
\hline
Univariate ARIMA Extrapolation Forecast \tabularnewline
time & Y[t] & F[t] & 95% LB & 95% UB & p-value(H0: Y[t] = F[t]) & P(F[t]>Y[t-1]) & P(F[t]>Y[t-s]) & P(F[t]>Y[46]) \tabularnewline
34 & 31555.4 & - & - & - & - & - & - & - \tabularnewline
35 & 29780.7 & - & - & - & - & - & - & - \tabularnewline
36 & 25656.6 & - & - & - & - & - & - & - \tabularnewline
37 & 26193 & - & - & - & - & - & - & - \tabularnewline
38 & 24095.9 & - & - & - & - & - & - & - \tabularnewline
39 & 22440.2 & - & - & - & - & - & - & - \tabularnewline
40 & 25951.7 & - & - & - & - & - & - & - \tabularnewline
41 & 27634.5 & - & - & - & - & - & - & - \tabularnewline
42 & 27930.6 & - & - & - & - & - & - & - \tabularnewline
43 & 31247.3 & - & - & - & - & - & - & - \tabularnewline
44 & 31823.7 & - & - & - & - & - & - & - \tabularnewline
45 & 33078.7 & - & - & - & - & - & - & - \tabularnewline
46 & 34032.4 & - & - & - & - & - & - & - \tabularnewline
47 & 28265 & 32625.7686 & 30759.0171 & 34492.5202 & 0 & 0.0699 & 0.9986 & 0.0699 \tabularnewline
48 & 25079.5 & 29290.4025 & 27297.1769 & 31283.6282 & 0 & 0.8433 & 0.9998 & 0 \tabularnewline
49 & 24743.5 & 30005.3933 & 27861.581 & 32149.2055 & 0 & 1 & 0.9998 & 1e-04 \tabularnewline
50 & 18845.5 & 27466.1496 & 25041.2468 & 29891.0525 & 0 & 0.9861 & 0.9968 & 0 \tabularnewline
51 & 21224.7 & 27393.1631 & 24811.1398 & 29975.1865 & 0 & 1 & 0.9999 & 0 \tabularnewline
52 & 21920.6 & 29655.1669 & 26913.0992 & 32397.2346 & 0 & 1 & 0.9959 & 9e-04 \tabularnewline
53 & 22734.1 & 30967.0349 & 28053.4353 & 33880.6345 & 0 & 1 & 0.9875 & 0.0196 \tabularnewline
54 & 23972.8 & 32006.603 & 28947.0054 & 35066.2006 & 0 & 1 & 0.9955 & 0.0972 \tabularnewline
55 & 25671.1 & 34116.2425 & 30914.1467 & 37318.3383 & 0 & 1 & 0.9605 & 0.5205 \tabularnewline
56 & 25798.1 & 34978.6511 & 31637.0629 & 38320.2392 & 0 & 1 & 0.9679 & 0.7106 \tabularnewline
57 & 27893.9 & 36055.5119 & 32582.8823 & 39528.1414 & 0 & 1 & 0.9535 & 0.8732 \tabularnewline
58 & 29557.8 & 37532.3232 & 33932.6758 & 41131.9707 & 0 & 1 & 0.9717 & 0.9717 \tabularnewline
59 & 27541.7 & 35982.0028 & 31939.988 & 40024.0176 & 0 & 0.9991 & 0.9999 & 0.8278 \tabularnewline
60 & 26470.1 & 32370.595 & 28130.6791 & 36610.5109 & 0.0032 & 0.9872 & 0.9996 & 0.2212 \tabularnewline
61 & 25185.1 & 33290.1108 & 28848.2583 & 37731.9632 & 2e-04 & 0.9987 & 0.9999 & 0.3716 \tabularnewline
62 & 23363.8 & 30831.3994 & 26146.8877 & 35515.9112 & 9e-04 & 0.9909 & 1 & 0.0902 \tabularnewline
63 & 24300.2 & 30330.8781 & 25450.0192 & 35211.737 & 0.0077 & 0.9974 & 0.9999 & 0.0686 \tabularnewline
64 & 25905.7 & 32650.0697 & 27575.7393 & 37724.4 & 0.0046 & 0.9994 & 1 & 0.2967 \tabularnewline
65 & 29036.8 & 33966.355 & 28697.804 & 39234.906 & 0.0333 & 0.9986 & 1 & 0.4902 \tabularnewline
66 & 32866.5 & 35061.3005 & 29611.7305 & 40510.8705 & 0.2149 & 0.9849 & 1 & 0.6443 \tabularnewline
67 & 33260 & 37267.8058 & 31641.7596 & 42893.852 & 0.0813 & 0.9374 & 1 & 0.8702 \tabularnewline
68 & 35288.5 & 37754.7356 & 31956.3396 & 43553.1315 & 0.2022 & 0.9357 & 1 & 0.8958 \tabularnewline
69 & 34999.2 & 38846.835 & 32882.2381 & 44811.432 & 0.1031 & 0.8789 & 0.9998 & 0.9432 \tabularnewline
70 & 34820.2 & 40404.0714 & 34277.4709 & 46530.672 & 0.037 & 0.9581 & 0.9997 & 0.9792 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114962&T=1

[TABLE]
[ROW][C]Univariate ARIMA Extrapolation Forecast[/C][/ROW]
[ROW][C]time[/C][C]Y[t][/C][C]F[t][/C][C]95% LB[/C][C]95% UB[/C][C]p-value(H0: Y[t] = F[t])[/C][C]P(F[t]>Y[t-1])[/C][C]P(F[t]>Y[t-s])[/C][C]P(F[t]>Y[46])[/C][/ROW]
[ROW][C]34[/C][C]31555.4[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]35[/C][C]29780.7[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]36[/C][C]25656.6[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]37[/C][C]26193[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]38[/C][C]24095.9[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]39[/C][C]22440.2[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]40[/C][C]25951.7[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]41[/C][C]27634.5[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]42[/C][C]27930.6[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]43[/C][C]31247.3[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]44[/C][C]31823.7[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]45[/C][C]33078.7[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]46[/C][C]34032.4[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]47[/C][C]28265[/C][C]32625.7686[/C][C]30759.0171[/C][C]34492.5202[/C][C]0[/C][C]0.0699[/C][C]0.9986[/C][C]0.0699[/C][/ROW]
[ROW][C]48[/C][C]25079.5[/C][C]29290.4025[/C][C]27297.1769[/C][C]31283.6282[/C][C]0[/C][C]0.8433[/C][C]0.9998[/C][C]0[/C][/ROW]
[ROW][C]49[/C][C]24743.5[/C][C]30005.3933[/C][C]27861.581[/C][C]32149.2055[/C][C]0[/C][C]1[/C][C]0.9998[/C][C]1e-04[/C][/ROW]
[ROW][C]50[/C][C]18845.5[/C][C]27466.1496[/C][C]25041.2468[/C][C]29891.0525[/C][C]0[/C][C]0.9861[/C][C]0.9968[/C][C]0[/C][/ROW]
[ROW][C]51[/C][C]21224.7[/C][C]27393.1631[/C][C]24811.1398[/C][C]29975.1865[/C][C]0[/C][C]1[/C][C]0.9999[/C][C]0[/C][/ROW]
[ROW][C]52[/C][C]21920.6[/C][C]29655.1669[/C][C]26913.0992[/C][C]32397.2346[/C][C]0[/C][C]1[/C][C]0.9959[/C][C]9e-04[/C][/ROW]
[ROW][C]53[/C][C]22734.1[/C][C]30967.0349[/C][C]28053.4353[/C][C]33880.6345[/C][C]0[/C][C]1[/C][C]0.9875[/C][C]0.0196[/C][/ROW]
[ROW][C]54[/C][C]23972.8[/C][C]32006.603[/C][C]28947.0054[/C][C]35066.2006[/C][C]0[/C][C]1[/C][C]0.9955[/C][C]0.0972[/C][/ROW]
[ROW][C]55[/C][C]25671.1[/C][C]34116.2425[/C][C]30914.1467[/C][C]37318.3383[/C][C]0[/C][C]1[/C][C]0.9605[/C][C]0.5205[/C][/ROW]
[ROW][C]56[/C][C]25798.1[/C][C]34978.6511[/C][C]31637.0629[/C][C]38320.2392[/C][C]0[/C][C]1[/C][C]0.9679[/C][C]0.7106[/C][/ROW]
[ROW][C]57[/C][C]27893.9[/C][C]36055.5119[/C][C]32582.8823[/C][C]39528.1414[/C][C]0[/C][C]1[/C][C]0.9535[/C][C]0.8732[/C][/ROW]
[ROW][C]58[/C][C]29557.8[/C][C]37532.3232[/C][C]33932.6758[/C][C]41131.9707[/C][C]0[/C][C]1[/C][C]0.9717[/C][C]0.9717[/C][/ROW]
[ROW][C]59[/C][C]27541.7[/C][C]35982.0028[/C][C]31939.988[/C][C]40024.0176[/C][C]0[/C][C]0.9991[/C][C]0.9999[/C][C]0.8278[/C][/ROW]
[ROW][C]60[/C][C]26470.1[/C][C]32370.595[/C][C]28130.6791[/C][C]36610.5109[/C][C]0.0032[/C][C]0.9872[/C][C]0.9996[/C][C]0.2212[/C][/ROW]
[ROW][C]61[/C][C]25185.1[/C][C]33290.1108[/C][C]28848.2583[/C][C]37731.9632[/C][C]2e-04[/C][C]0.9987[/C][C]0.9999[/C][C]0.3716[/C][/ROW]
[ROW][C]62[/C][C]23363.8[/C][C]30831.3994[/C][C]26146.8877[/C][C]35515.9112[/C][C]9e-04[/C][C]0.9909[/C][C]1[/C][C]0.0902[/C][/ROW]
[ROW][C]63[/C][C]24300.2[/C][C]30330.8781[/C][C]25450.0192[/C][C]35211.737[/C][C]0.0077[/C][C]0.9974[/C][C]0.9999[/C][C]0.0686[/C][/ROW]
[ROW][C]64[/C][C]25905.7[/C][C]32650.0697[/C][C]27575.7393[/C][C]37724.4[/C][C]0.0046[/C][C]0.9994[/C][C]1[/C][C]0.2967[/C][/ROW]
[ROW][C]65[/C][C]29036.8[/C][C]33966.355[/C][C]28697.804[/C][C]39234.906[/C][C]0.0333[/C][C]0.9986[/C][C]1[/C][C]0.4902[/C][/ROW]
[ROW][C]66[/C][C]32866.5[/C][C]35061.3005[/C][C]29611.7305[/C][C]40510.8705[/C][C]0.2149[/C][C]0.9849[/C][C]1[/C][C]0.6443[/C][/ROW]
[ROW][C]67[/C][C]33260[/C][C]37267.8058[/C][C]31641.7596[/C][C]42893.852[/C][C]0.0813[/C][C]0.9374[/C][C]1[/C][C]0.8702[/C][/ROW]
[ROW][C]68[/C][C]35288.5[/C][C]37754.7356[/C][C]31956.3396[/C][C]43553.1315[/C][C]0.2022[/C][C]0.9357[/C][C]1[/C][C]0.8958[/C][/ROW]
[ROW][C]69[/C][C]34999.2[/C][C]38846.835[/C][C]32882.2381[/C][C]44811.432[/C][C]0.1031[/C][C]0.8789[/C][C]0.9998[/C][C]0.9432[/C][/ROW]
[ROW][C]70[/C][C]34820.2[/C][C]40404.0714[/C][C]34277.4709[/C][C]46530.672[/C][C]0.037[/C][C]0.9581[/C][C]0.9997[/C][C]0.9792[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114962&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114962&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:

Univariate ARIMA Extrapolation Forecast
timeY[t]F[t]95% LB95% UBp-value(H0: Y[t] = F[t])P(F[t]>Y[t-1])P(F[t]>Y[t-s])P(F[t]>Y[46])
3431555.4-------
3529780.7-------
3625656.6-------
3726193-------
3824095.9-------
3922440.2-------
4025951.7-------
4127634.5-------
4227930.6-------
4331247.3-------
4431823.7-------
4533078.7-------
4634032.4-------
472826532625.768630759.017134492.520200.06990.99860.0699
4825079.529290.402527297.176931283.628200.84330.99980
4924743.530005.393327861.58132149.2055010.99981e-04
5018845.527466.149625041.246829891.052500.98610.99680
5121224.727393.163124811.139829975.1865010.99990
5221920.629655.166926913.099232397.2346010.99599e-04
5322734.130967.034928053.435333880.6345010.98750.0196
5423972.832006.60328947.005435066.2006010.99550.0972
5525671.134116.242530914.146737318.3383010.96050.5205
5625798.134978.651131637.062938320.2392010.96790.7106
5727893.936055.511932582.882339528.1414010.95350.8732
5829557.837532.323233932.675841131.9707010.97170.9717
5927541.735982.002831939.98840024.017600.99910.99990.8278
6026470.132370.59528130.679136610.51090.00320.98720.99960.2212
6125185.133290.110828848.258337731.96322e-040.99870.99990.3716
6223363.830831.399426146.887735515.91129e-040.990910.0902
6324300.230330.878125450.019235211.7370.00770.99740.99990.0686
6425905.732650.069727575.739337724.40.00460.999410.2967
6529036.833966.35528697.80439234.9060.03330.998610.4902
6632866.535061.300529611.730540510.87050.21490.984910.6443
673326037267.805831641.759642893.8520.08130.937410.8702
6835288.537754.735631956.339643553.13150.20220.935710.8958
6934999.238846.83532882.238144811.4320.10310.87890.99980.9432
7034820.240404.071434277.470946530.6720.0370.95810.99970.9792






Univariate ARIMA Extrapolation Forecast Performance
time% S.E.PEMAPESq.EMSERMSE
470.0292-0.1337019016303.073200
480.0347-0.14380.138717731700.220418374001.64684286.4906
490.0365-0.17540.150927687520.604221478507.96594634.4911
500.045-0.31390.191774315600.229434687781.03185889.6334
510.0481-0.22520.198438049937.447535360212.31495946.4454
520.0472-0.26080.208859823524.970239437431.09086279.9229
530.048-0.26590.216967781217.246143486543.39876594.4328
540.0488-0.2510.221264541990.159846118474.24386791.0584
550.0479-0.24750.224171320432.042248918691.7776994.1899
560.0487-0.26250.22884282518.3952455074.43837242.5876
570.0491-0.22640.227866611908.200953742059.32587330.8976
580.0489-0.21250.226563593020.841554562972.78557386.6754
590.0573-0.23460.227171238711.512855845721.91837472.9995
600.0668-0.18230.223934815840.824354343587.55457371.8103
610.0681-0.24350.225265691199.329355100095.00617422.9438
620.0775-0.24220.226355765041.086955141654.13627425.7427
630.0821-0.19880.224736369077.844954037384.94267351.0125
640.0793-0.20660.223745486522.011953562337.0027318.6294
650.0791-0.14510.219524300512.041752022240.95147212.6445
660.0793-0.06260.21174817149.17449661986.36267047.1261
670.077-0.10750.206716062507.47448062011.17746932.6771
680.0784-0.06530.20036082318.004946153843.30596793.662
690.0783-0.0990.195914804295.229744790819.47656692.5944
700.0774-0.13820.193531179620.086144223686.16866650.0892

\begin{tabular}{lllllllll}
\hline
Univariate ARIMA Extrapolation Forecast Performance \tabularnewline
time & % S.E. & PE & MAPE & Sq.E & MSE & RMSE \tabularnewline
47 & 0.0292 & -0.1337 & 0 & 19016303.0732 & 0 & 0 \tabularnewline
48 & 0.0347 & -0.1438 & 0.1387 & 17731700.2204 & 18374001.6468 & 4286.4906 \tabularnewline
49 & 0.0365 & -0.1754 & 0.1509 & 27687520.6042 & 21478507.9659 & 4634.4911 \tabularnewline
50 & 0.045 & -0.3139 & 0.1917 & 74315600.2294 & 34687781.0318 & 5889.6334 \tabularnewline
51 & 0.0481 & -0.2252 & 0.1984 & 38049937.4475 & 35360212.3149 & 5946.4454 \tabularnewline
52 & 0.0472 & -0.2608 & 0.2088 & 59823524.9702 & 39437431.0908 & 6279.9229 \tabularnewline
53 & 0.048 & -0.2659 & 0.2169 & 67781217.2461 & 43486543.3987 & 6594.4328 \tabularnewline
54 & 0.0488 & -0.251 & 0.2212 & 64541990.1598 & 46118474.2438 & 6791.0584 \tabularnewline
55 & 0.0479 & -0.2475 & 0.2241 & 71320432.0422 & 48918691.777 & 6994.1899 \tabularnewline
56 & 0.0487 & -0.2625 & 0.228 & 84282518.39 & 52455074.4383 & 7242.5876 \tabularnewline
57 & 0.0491 & -0.2264 & 0.2278 & 66611908.2009 & 53742059.3258 & 7330.8976 \tabularnewline
58 & 0.0489 & -0.2125 & 0.2265 & 63593020.8415 & 54562972.7855 & 7386.6754 \tabularnewline
59 & 0.0573 & -0.2346 & 0.2271 & 71238711.5128 & 55845721.9183 & 7472.9995 \tabularnewline
60 & 0.0668 & -0.1823 & 0.2239 & 34815840.8243 & 54343587.5545 & 7371.8103 \tabularnewline
61 & 0.0681 & -0.2435 & 0.2252 & 65691199.3293 & 55100095.0061 & 7422.9438 \tabularnewline
62 & 0.0775 & -0.2422 & 0.2263 & 55765041.0869 & 55141654.1362 & 7425.7427 \tabularnewline
63 & 0.0821 & -0.1988 & 0.2247 & 36369077.8449 & 54037384.9426 & 7351.0125 \tabularnewline
64 & 0.0793 & -0.2066 & 0.2237 & 45486522.0119 & 53562337.002 & 7318.6294 \tabularnewline
65 & 0.0791 & -0.1451 & 0.2195 & 24300512.0417 & 52022240.9514 & 7212.6445 \tabularnewline
66 & 0.0793 & -0.0626 & 0.2117 & 4817149.174 & 49661986.3626 & 7047.1261 \tabularnewline
67 & 0.077 & -0.1075 & 0.2067 & 16062507.474 & 48062011.1774 & 6932.6771 \tabularnewline
68 & 0.0784 & -0.0653 & 0.2003 & 6082318.0049 & 46153843.3059 & 6793.662 \tabularnewline
69 & 0.0783 & -0.099 & 0.1959 & 14804295.2297 & 44790819.4765 & 6692.5944 \tabularnewline
70 & 0.0774 & -0.1382 & 0.1935 & 31179620.0861 & 44223686.1686 & 6650.0892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114962&T=2

[TABLE]
[ROW][C]Univariate ARIMA Extrapolation Forecast Performance[/C][/ROW]
[ROW][C]time[/C][C]% S.E.[/C][C]PE[/C][C]MAPE[/C][C]Sq.E[/C][C]MSE[/C][C]RMSE[/C][/ROW]
[ROW][C]47[/C][C]0.0292[/C][C]-0.1337[/C][C]0[/C][C]19016303.0732[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]48[/C][C]0.0347[/C][C]-0.1438[/C][C]0.1387[/C][C]17731700.2204[/C][C]18374001.6468[/C][C]4286.4906[/C][/ROW]
[ROW][C]49[/C][C]0.0365[/C][C]-0.1754[/C][C]0.1509[/C][C]27687520.6042[/C][C]21478507.9659[/C][C]4634.4911[/C][/ROW]
[ROW][C]50[/C][C]0.045[/C][C]-0.3139[/C][C]0.1917[/C][C]74315600.2294[/C][C]34687781.0318[/C][C]5889.6334[/C][/ROW]
[ROW][C]51[/C][C]0.0481[/C][C]-0.2252[/C][C]0.1984[/C][C]38049937.4475[/C][C]35360212.3149[/C][C]5946.4454[/C][/ROW]
[ROW][C]52[/C][C]0.0472[/C][C]-0.2608[/C][C]0.2088[/C][C]59823524.9702[/C][C]39437431.0908[/C][C]6279.9229[/C][/ROW]
[ROW][C]53[/C][C]0.048[/C][C]-0.2659[/C][C]0.2169[/C][C]67781217.2461[/C][C]43486543.3987[/C][C]6594.4328[/C][/ROW]
[ROW][C]54[/C][C]0.0488[/C][C]-0.251[/C][C]0.2212[/C][C]64541990.1598[/C][C]46118474.2438[/C][C]6791.0584[/C][/ROW]
[ROW][C]55[/C][C]0.0479[/C][C]-0.2475[/C][C]0.2241[/C][C]71320432.0422[/C][C]48918691.777[/C][C]6994.1899[/C][/ROW]
[ROW][C]56[/C][C]0.0487[/C][C]-0.2625[/C][C]0.228[/C][C]84282518.39[/C][C]52455074.4383[/C][C]7242.5876[/C][/ROW]
[ROW][C]57[/C][C]0.0491[/C][C]-0.2264[/C][C]0.2278[/C][C]66611908.2009[/C][C]53742059.3258[/C][C]7330.8976[/C][/ROW]
[ROW][C]58[/C][C]0.0489[/C][C]-0.2125[/C][C]0.2265[/C][C]63593020.8415[/C][C]54562972.7855[/C][C]7386.6754[/C][/ROW]
[ROW][C]59[/C][C]0.0573[/C][C]-0.2346[/C][C]0.2271[/C][C]71238711.5128[/C][C]55845721.9183[/C][C]7472.9995[/C][/ROW]
[ROW][C]60[/C][C]0.0668[/C][C]-0.1823[/C][C]0.2239[/C][C]34815840.8243[/C][C]54343587.5545[/C][C]7371.8103[/C][/ROW]
[ROW][C]61[/C][C]0.0681[/C][C]-0.2435[/C][C]0.2252[/C][C]65691199.3293[/C][C]55100095.0061[/C][C]7422.9438[/C][/ROW]
[ROW][C]62[/C][C]0.0775[/C][C]-0.2422[/C][C]0.2263[/C][C]55765041.0869[/C][C]55141654.1362[/C][C]7425.7427[/C][/ROW]
[ROW][C]63[/C][C]0.0821[/C][C]-0.1988[/C][C]0.2247[/C][C]36369077.8449[/C][C]54037384.9426[/C][C]7351.0125[/C][/ROW]
[ROW][C]64[/C][C]0.0793[/C][C]-0.2066[/C][C]0.2237[/C][C]45486522.0119[/C][C]53562337.002[/C][C]7318.6294[/C][/ROW]
[ROW][C]65[/C][C]0.0791[/C][C]-0.1451[/C][C]0.2195[/C][C]24300512.0417[/C][C]52022240.9514[/C][C]7212.6445[/C][/ROW]
[ROW][C]66[/C][C]0.0793[/C][C]-0.0626[/C][C]0.2117[/C][C]4817149.174[/C][C]49661986.3626[/C][C]7047.1261[/C][/ROW]
[ROW][C]67[/C][C]0.077[/C][C]-0.1075[/C][C]0.2067[/C][C]16062507.474[/C][C]48062011.1774[/C][C]6932.6771[/C][/ROW]
[ROW][C]68[/C][C]0.0784[/C][C]-0.0653[/C][C]0.2003[/C][C]6082318.0049[/C][C]46153843.3059[/C][C]6793.662[/C][/ROW]
[ROW][C]69[/C][C]0.0783[/C][C]-0.099[/C][C]0.1959[/C][C]14804295.2297[/C][C]44790819.4765[/C][C]6692.5944[/C][/ROW]
[ROW][C]70[/C][C]0.0774[/C][C]-0.1382[/C][C]0.1935[/C][C]31179620.0861[/C][C]44223686.1686[/C][C]6650.0892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114962&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114962&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:

Univariate ARIMA Extrapolation Forecast Performance
time% S.E.PEMAPESq.EMSERMSE
470.0292-0.1337019016303.073200
480.0347-0.14380.138717731700.220418374001.64684286.4906
490.0365-0.17540.150927687520.604221478507.96594634.4911
500.045-0.31390.191774315600.229434687781.03185889.6334
510.0481-0.22520.198438049937.447535360212.31495946.4454
520.0472-0.26080.208859823524.970239437431.09086279.9229
530.048-0.26590.216967781217.246143486543.39876594.4328
540.0488-0.2510.221264541990.159846118474.24386791.0584
550.0479-0.24750.224171320432.042248918691.7776994.1899
560.0487-0.26250.22884282518.3952455074.43837242.5876
570.0491-0.22640.227866611908.200953742059.32587330.8976
580.0489-0.21250.226563593020.841554562972.78557386.6754
590.0573-0.23460.227171238711.512855845721.91837472.9995
600.0668-0.18230.223934815840.824354343587.55457371.8103
610.0681-0.24350.225265691199.329355100095.00617422.9438
620.0775-0.24220.226355765041.086955141654.13627425.7427
630.0821-0.19880.224736369077.844954037384.94267351.0125
640.0793-0.20660.223745486522.011953562337.0027318.6294
650.0791-0.14510.219524300512.041752022240.95147212.6445
660.0793-0.06260.21174817149.17449661986.36267047.1261
670.077-0.10750.206716062507.47448062011.17746932.6771
680.0784-0.06530.20036082318.004946153843.30596793.662
690.0783-0.0990.195914804295.229744790819.47656692.5944
700.0774-0.13820.193531179620.086144223686.16866650.0892


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 24 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 2 ; par7 = 0 ; par8 = 2 ; par9 = 0 ; par10 = FALSE ;
R code (references can be found in the software module):