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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 computationSat, 25 Dec 2010 19:37:25 +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/25/t12933057457dkr6hfwf1lbl66.htm/, Retrieved Mon, 29 Apr 2024 02:09:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115444, Retrieved Mon, 29 Apr 2024 02:09:25 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [ARIMA Forecasting] [ARIMA Forecast] [2010-12-25 19:37:25] [2e87ce7aa3eb3dfe16df617f31f74f3c] [Current]
- RMPD    [ARIMA Forecasting] [Olieprijs ARIMA f...] [2010-12-25 20:49:28] [ae68acb0755efbaaf8db92ef09a2ce40]
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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 time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115444&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115444&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 time2 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[96])
84115.348-------
85131.284-------
86134.701-------
87127.193-------
8887.077-------
8972.744-------
9077.542-------
9178.005-------
9285.329-------
9386.041-------
9496.384-------
95116.678-------
96160.672-------
97152.364157.7948139.6448175.94480.27880.3780.99790.378
98144.936140.0086120.3416159.67560.31170.10910.70160.0197
99122.974130.8729109.7978151.94790.23130.09550.63390.0028
10094.456101.76679.3713124.16080.26120.03170.90070
10182.49191.874168.2332115.5150.21830.41530.94360
10284.8989.423664.599114.24820.36020.70790.82590
10385.27791.759865.8055117.71420.31220.6980.85050
10481.20697.946570.9096124.98340.11250.82080.81980
10571.01294.973566.8957123.05130.04720.83170.73350
10687.302106.663777.5823135.74520.0960.99190.75581e-04
10797.427112.99882.9464143.04960.15490.95310.40529e-04
108133.242150.0518119.0604181.04310.14390.99960.25090.2509
109137.064156.1521123.5419188.76230.12560.91570.59010.3929
110119.042138.3659104.666172.06580.13050.53020.35120.0973
111116.47129.230294.4747163.98570.23590.71720.63790.0381
11296.028100.123464.3435135.90330.41120.18530.62195e-04
11379.28190.231453.4556127.00720.27970.37870.661e-04
11473.87287.78150.0355125.52640.23510.67050.55971e-04
11580.96490.117151.4264128.80790.32140.79470.59682e-04
11686.73996.303856.6903135.91730.3180.77610.77257e-04
11789.99793.330952.8156133.84620.43590.62510.85996e-04
11896.292105.021163.6236146.41850.33970.76160.79920.0042
119101.355111.355369.0942153.61650.32140.75760.74090.0111
120136.543148.4091105.3015191.51670.29480.98380.75480.2886

\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[96]) \tabularnewline
84 & 115.348 & - & - & - & - & - & - & - \tabularnewline
85 & 131.284 & - & - & - & - & - & - & - \tabularnewline
86 & 134.701 & - & - & - & - & - & - & - \tabularnewline
87 & 127.193 & - & - & - & - & - & - & - \tabularnewline
88 & 87.077 & - & - & - & - & - & - & - \tabularnewline
89 & 72.744 & - & - & - & - & - & - & - \tabularnewline
90 & 77.542 & - & - & - & - & - & - & - \tabularnewline
91 & 78.005 & - & - & - & - & - & - & - \tabularnewline
92 & 85.329 & - & - & - & - & - & - & - \tabularnewline
93 & 86.041 & - & - & - & - & - & - & - \tabularnewline
94 & 96.384 & - & - & - & - & - & - & - \tabularnewline
95 & 116.678 & - & - & - & - & - & - & - \tabularnewline
96 & 160.672 & - & - & - & - & - & - & - \tabularnewline
97 & 152.364 & 157.7948 & 139.6448 & 175.9448 & 0.2788 & 0.378 & 0.9979 & 0.378 \tabularnewline
98 & 144.936 & 140.0086 & 120.3416 & 159.6756 & 0.3117 & 0.1091 & 0.7016 & 0.0197 \tabularnewline
99 & 122.974 & 130.8729 & 109.7978 & 151.9479 & 0.2313 & 0.0955 & 0.6339 & 0.0028 \tabularnewline
100 & 94.456 & 101.766 & 79.3713 & 124.1608 & 0.2612 & 0.0317 & 0.9007 & 0 \tabularnewline
101 & 82.491 & 91.8741 & 68.2332 & 115.515 & 0.2183 & 0.4153 & 0.9436 & 0 \tabularnewline
102 & 84.89 & 89.4236 & 64.599 & 114.2482 & 0.3602 & 0.7079 & 0.8259 & 0 \tabularnewline
103 & 85.277 & 91.7598 & 65.8055 & 117.7142 & 0.3122 & 0.698 & 0.8505 & 0 \tabularnewline
104 & 81.206 & 97.9465 & 70.9096 & 124.9834 & 0.1125 & 0.8208 & 0.8198 & 0 \tabularnewline
105 & 71.012 & 94.9735 & 66.8957 & 123.0513 & 0.0472 & 0.8317 & 0.7335 & 0 \tabularnewline
106 & 87.302 & 106.6637 & 77.5823 & 135.7452 & 0.096 & 0.9919 & 0.7558 & 1e-04 \tabularnewline
107 & 97.427 & 112.998 & 82.9464 & 143.0496 & 0.1549 & 0.9531 & 0.4052 & 9e-04 \tabularnewline
108 & 133.242 & 150.0518 & 119.0604 & 181.0431 & 0.1439 & 0.9996 & 0.2509 & 0.2509 \tabularnewline
109 & 137.064 & 156.1521 & 123.5419 & 188.7623 & 0.1256 & 0.9157 & 0.5901 & 0.3929 \tabularnewline
110 & 119.042 & 138.3659 & 104.666 & 172.0658 & 0.1305 & 0.5302 & 0.3512 & 0.0973 \tabularnewline
111 & 116.47 & 129.2302 & 94.4747 & 163.9857 & 0.2359 & 0.7172 & 0.6379 & 0.0381 \tabularnewline
112 & 96.028 & 100.1234 & 64.3435 & 135.9033 & 0.4112 & 0.1853 & 0.6219 & 5e-04 \tabularnewline
113 & 79.281 & 90.2314 & 53.4556 & 127.0072 & 0.2797 & 0.3787 & 0.66 & 1e-04 \tabularnewline
114 & 73.872 & 87.781 & 50.0355 & 125.5264 & 0.2351 & 0.6705 & 0.5597 & 1e-04 \tabularnewline
115 & 80.964 & 90.1171 & 51.4264 & 128.8079 & 0.3214 & 0.7947 & 0.5968 & 2e-04 \tabularnewline
116 & 86.739 & 96.3038 & 56.6903 & 135.9173 & 0.318 & 0.7761 & 0.7725 & 7e-04 \tabularnewline
117 & 89.997 & 93.3309 & 52.8156 & 133.8462 & 0.4359 & 0.6251 & 0.8599 & 6e-04 \tabularnewline
118 & 96.292 & 105.0211 & 63.6236 & 146.4185 & 0.3397 & 0.7616 & 0.7992 & 0.0042 \tabularnewline
119 & 101.355 & 111.3553 & 69.0942 & 153.6165 & 0.3214 & 0.7576 & 0.7409 & 0.0111 \tabularnewline
120 & 136.543 & 148.4091 & 105.3015 & 191.5167 & 0.2948 & 0.9838 & 0.7548 & 0.2886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115444&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[96])[/C][/ROW]
[ROW][C]84[/C][C]115.348[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]85[/C][C]131.284[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]86[/C][C]134.701[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]87[/C][C]127.193[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]88[/C][C]87.077[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]89[/C][C]72.744[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]90[/C][C]77.542[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]91[/C][C]78.005[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]92[/C][C]85.329[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]93[/C][C]86.041[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]94[/C][C]96.384[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]95[/C][C]116.678[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]96[/C][C]160.672[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][C]-[/C][/ROW]
[ROW][C]97[/C][C]152.364[/C][C]157.7948[/C][C]139.6448[/C][C]175.9448[/C][C]0.2788[/C][C]0.378[/C][C]0.9979[/C][C]0.378[/C][/ROW]
[ROW][C]98[/C][C]144.936[/C][C]140.0086[/C][C]120.3416[/C][C]159.6756[/C][C]0.3117[/C][C]0.1091[/C][C]0.7016[/C][C]0.0197[/C][/ROW]
[ROW][C]99[/C][C]122.974[/C][C]130.8729[/C][C]109.7978[/C][C]151.9479[/C][C]0.2313[/C][C]0.0955[/C][C]0.6339[/C][C]0.0028[/C][/ROW]
[ROW][C]100[/C][C]94.456[/C][C]101.766[/C][C]79.3713[/C][C]124.1608[/C][C]0.2612[/C][C]0.0317[/C][C]0.9007[/C][C]0[/C][/ROW]
[ROW][C]101[/C][C]82.491[/C][C]91.8741[/C][C]68.2332[/C][C]115.515[/C][C]0.2183[/C][C]0.4153[/C][C]0.9436[/C][C]0[/C][/ROW]
[ROW][C]102[/C][C]84.89[/C][C]89.4236[/C][C]64.599[/C][C]114.2482[/C][C]0.3602[/C][C]0.7079[/C][C]0.8259[/C][C]0[/C][/ROW]
[ROW][C]103[/C][C]85.277[/C][C]91.7598[/C][C]65.8055[/C][C]117.7142[/C][C]0.3122[/C][C]0.698[/C][C]0.8505[/C][C]0[/C][/ROW]
[ROW][C]104[/C][C]81.206[/C][C]97.9465[/C][C]70.9096[/C][C]124.9834[/C][C]0.1125[/C][C]0.8208[/C][C]0.8198[/C][C]0[/C][/ROW]
[ROW][C]105[/C][C]71.012[/C][C]94.9735[/C][C]66.8957[/C][C]123.0513[/C][C]0.0472[/C][C]0.8317[/C][C]0.7335[/C][C]0[/C][/ROW]
[ROW][C]106[/C][C]87.302[/C][C]106.6637[/C][C]77.5823[/C][C]135.7452[/C][C]0.096[/C][C]0.9919[/C][C]0.7558[/C][C]1e-04[/C][/ROW]
[ROW][C]107[/C][C]97.427[/C][C]112.998[/C][C]82.9464[/C][C]143.0496[/C][C]0.1549[/C][C]0.9531[/C][C]0.4052[/C][C]9e-04[/C][/ROW]
[ROW][C]108[/C][C]133.242[/C][C]150.0518[/C][C]119.0604[/C][C]181.0431[/C][C]0.1439[/C][C]0.9996[/C][C]0.2509[/C][C]0.2509[/C][/ROW]
[ROW][C]109[/C][C]137.064[/C][C]156.1521[/C][C]123.5419[/C][C]188.7623[/C][C]0.1256[/C][C]0.9157[/C][C]0.5901[/C][C]0.3929[/C][/ROW]
[ROW][C]110[/C][C]119.042[/C][C]138.3659[/C][C]104.666[/C][C]172.0658[/C][C]0.1305[/C][C]0.5302[/C][C]0.3512[/C][C]0.0973[/C][/ROW]
[ROW][C]111[/C][C]116.47[/C][C]129.2302[/C][C]94.4747[/C][C]163.9857[/C][C]0.2359[/C][C]0.7172[/C][C]0.6379[/C][C]0.0381[/C][/ROW]
[ROW][C]112[/C][C]96.028[/C][C]100.1234[/C][C]64.3435[/C][C]135.9033[/C][C]0.4112[/C][C]0.1853[/C][C]0.6219[/C][C]5e-04[/C][/ROW]
[ROW][C]113[/C][C]79.281[/C][C]90.2314[/C][C]53.4556[/C][C]127.0072[/C][C]0.2797[/C][C]0.3787[/C][C]0.66[/C][C]1e-04[/C][/ROW]
[ROW][C]114[/C][C]73.872[/C][C]87.781[/C][C]50.0355[/C][C]125.5264[/C][C]0.2351[/C][C]0.6705[/C][C]0.5597[/C][C]1e-04[/C][/ROW]
[ROW][C]115[/C][C]80.964[/C][C]90.1171[/C][C]51.4264[/C][C]128.8079[/C][C]0.3214[/C][C]0.7947[/C][C]0.5968[/C][C]2e-04[/C][/ROW]
[ROW][C]116[/C][C]86.739[/C][C]96.3038[/C][C]56.6903[/C][C]135.9173[/C][C]0.318[/C][C]0.7761[/C][C]0.7725[/C][C]7e-04[/C][/ROW]
[ROW][C]117[/C][C]89.997[/C][C]93.3309[/C][C]52.8156[/C][C]133.8462[/C][C]0.4359[/C][C]0.6251[/C][C]0.8599[/C][C]6e-04[/C][/ROW]
[ROW][C]118[/C][C]96.292[/C][C]105.0211[/C][C]63.6236[/C][C]146.4185[/C][C]0.3397[/C][C]0.7616[/C][C]0.7992[/C][C]0.0042[/C][/ROW]
[ROW][C]119[/C][C]101.355[/C][C]111.3553[/C][C]69.0942[/C][C]153.6165[/C][C]0.3214[/C][C]0.7576[/C][C]0.7409[/C][C]0.0111[/C][/ROW]
[ROW][C]120[/C][C]136.543[/C][C]148.4091[/C][C]105.3015[/C][C]191.5167[/C][C]0.2948[/C][C]0.9838[/C][C]0.7548[/C][C]0.2886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115444&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[96])
84115.348-------
85131.284-------
86134.701-------
87127.193-------
8887.077-------
8972.744-------
9077.542-------
9178.005-------
9285.329-------
9386.041-------
9496.384-------
95116.678-------
96160.672-------
97152.364157.7948139.6448175.94480.27880.3780.99790.378
98144.936140.0086120.3416159.67560.31170.10910.70160.0197
99122.974130.8729109.7978151.94790.23130.09550.63390.0028
10094.456101.76679.3713124.16080.26120.03170.90070
10182.49191.874168.2332115.5150.21830.41530.94360
10284.8989.423664.599114.24820.36020.70790.82590
10385.27791.759865.8055117.71420.31220.6980.85050
10481.20697.946570.9096124.98340.11250.82080.81980
10571.01294.973566.8957123.05130.04720.83170.73350
10687.302106.663777.5823135.74520.0960.99190.75581e-04
10797.427112.99882.9464143.04960.15490.95310.40529e-04
108133.242150.0518119.0604181.04310.14390.99960.25090.2509
109137.064156.1521123.5419188.76230.12560.91570.59010.3929
110119.042138.3659104.666172.06580.13050.53020.35120.0973
111116.47129.230294.4747163.98570.23590.71720.63790.0381
11296.028100.123464.3435135.90330.41120.18530.62195e-04
11379.28190.231453.4556127.00720.27970.37870.661e-04
11473.87287.78150.0355125.52640.23510.67050.55971e-04
11580.96490.117151.4264128.80790.32140.79470.59682e-04
11686.73996.303856.6903135.91730.3180.77610.77257e-04
11789.99793.330952.8156133.84620.43590.62510.85996e-04
11896.292105.021163.6236146.41850.33970.76160.79920.0042
119101.355111.355369.0942153.61650.32140.75760.74090.0111
120136.543148.4091105.3015191.51670.29480.98380.75480.2886






Univariate ARIMA Extrapolation Forecast Performance
time% S.E.PEMAPESq.EMSERMSE
970.0587-0.0344029.493400
980.07170.03520.034824.279226.88635.1852
990.0822-0.06040.043362.39238.72156.2227
1000.1123-0.07180.050453.436742.40036.5116
1010.1313-0.10210.060888.042651.52887.1784
1020.1416-0.05070.059120.553746.36636.8093
1030.1443-0.07060.060842.02745.74646.7636
1040.1408-0.17090.0745280.243875.05858.6636
1050.1508-0.25230.0943574.1553130.513711.4243
1060.1391-0.18150.103374.8764154.9512.4479
1070.1357-0.13780.1062242.4563162.905112.7634
1080.1054-0.1120.1067282.5681172.87713.1483
1090.1065-0.12220.1079364.3561187.606213.6969
1100.1243-0.13970.1101373.4144200.878214.1732
1110.1372-0.09870.1094162.8224198.341214.0834
1120.1823-0.04090.105116.772186.993113.6745
1130.2079-0.12140.106119.9119183.047113.5295
1140.2194-0.15850.109193.459183.625613.5509
1150.2191-0.10160.108683.7801178.370513.3555
1160.2099-0.09930.108191.4856174.026313.1919
1170.2215-0.03570.104711.1147166.268612.8945
1180.2011-0.08310.103776.1964162.174412.7348
1190.1936-0.08980.1031100.0067159.471512.6282
1200.1482-0.080.1021140.8041158.693712.5974

\begin{tabular}{lllllllll}
\hline
Univariate ARIMA Extrapolation Forecast Performance \tabularnewline
time & % S.E. & PE & MAPE & Sq.E & MSE & RMSE \tabularnewline
97 & 0.0587 & -0.0344 & 0 & 29.4934 & 0 & 0 \tabularnewline
98 & 0.0717 & 0.0352 & 0.0348 & 24.2792 & 26.8863 & 5.1852 \tabularnewline
99 & 0.0822 & -0.0604 & 0.0433 & 62.392 & 38.7215 & 6.2227 \tabularnewline
100 & 0.1123 & -0.0718 & 0.0504 & 53.4367 & 42.4003 & 6.5116 \tabularnewline
101 & 0.1313 & -0.1021 & 0.0608 & 88.0426 & 51.5288 & 7.1784 \tabularnewline
102 & 0.1416 & -0.0507 & 0.0591 & 20.5537 & 46.3663 & 6.8093 \tabularnewline
103 & 0.1443 & -0.0706 & 0.0608 & 42.027 & 45.7464 & 6.7636 \tabularnewline
104 & 0.1408 & -0.1709 & 0.0745 & 280.2438 & 75.0585 & 8.6636 \tabularnewline
105 & 0.1508 & -0.2523 & 0.0943 & 574.1553 & 130.5137 & 11.4243 \tabularnewline
106 & 0.1391 & -0.1815 & 0.103 & 374.8764 & 154.95 & 12.4479 \tabularnewline
107 & 0.1357 & -0.1378 & 0.1062 & 242.4563 & 162.9051 & 12.7634 \tabularnewline
108 & 0.1054 & -0.112 & 0.1067 & 282.5681 & 172.877 & 13.1483 \tabularnewline
109 & 0.1065 & -0.1222 & 0.1079 & 364.3561 & 187.6062 & 13.6969 \tabularnewline
110 & 0.1243 & -0.1397 & 0.1101 & 373.4144 & 200.8782 & 14.1732 \tabularnewline
111 & 0.1372 & -0.0987 & 0.1094 & 162.8224 & 198.3412 & 14.0834 \tabularnewline
112 & 0.1823 & -0.0409 & 0.1051 & 16.772 & 186.9931 & 13.6745 \tabularnewline
113 & 0.2079 & -0.1214 & 0.106 & 119.9119 & 183.0471 & 13.5295 \tabularnewline
114 & 0.2194 & -0.1585 & 0.109 & 193.459 & 183.6256 & 13.5509 \tabularnewline
115 & 0.2191 & -0.1016 & 0.1086 & 83.7801 & 178.3705 & 13.3555 \tabularnewline
116 & 0.2099 & -0.0993 & 0.1081 & 91.4856 & 174.0263 & 13.1919 \tabularnewline
117 & 0.2215 & -0.0357 & 0.1047 & 11.1147 & 166.2686 & 12.8945 \tabularnewline
118 & 0.2011 & -0.0831 & 0.1037 & 76.1964 & 162.1744 & 12.7348 \tabularnewline
119 & 0.1936 & -0.0898 & 0.1031 & 100.0067 & 159.4715 & 12.6282 \tabularnewline
120 & 0.1482 & -0.08 & 0.1021 & 140.8041 & 158.6937 & 12.5974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115444&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]97[/C][C]0.0587[/C][C]-0.0344[/C][C]0[/C][C]29.4934[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]98[/C][C]0.0717[/C][C]0.0352[/C][C]0.0348[/C][C]24.2792[/C][C]26.8863[/C][C]5.1852[/C][/ROW]
[ROW][C]99[/C][C]0.0822[/C][C]-0.0604[/C][C]0.0433[/C][C]62.392[/C][C]38.7215[/C][C]6.2227[/C][/ROW]
[ROW][C]100[/C][C]0.1123[/C][C]-0.0718[/C][C]0.0504[/C][C]53.4367[/C][C]42.4003[/C][C]6.5116[/C][/ROW]
[ROW][C]101[/C][C]0.1313[/C][C]-0.1021[/C][C]0.0608[/C][C]88.0426[/C][C]51.5288[/C][C]7.1784[/C][/ROW]
[ROW][C]102[/C][C]0.1416[/C][C]-0.0507[/C][C]0.0591[/C][C]20.5537[/C][C]46.3663[/C][C]6.8093[/C][/ROW]
[ROW][C]103[/C][C]0.1443[/C][C]-0.0706[/C][C]0.0608[/C][C]42.027[/C][C]45.7464[/C][C]6.7636[/C][/ROW]
[ROW][C]104[/C][C]0.1408[/C][C]-0.1709[/C][C]0.0745[/C][C]280.2438[/C][C]75.0585[/C][C]8.6636[/C][/ROW]
[ROW][C]105[/C][C]0.1508[/C][C]-0.2523[/C][C]0.0943[/C][C]574.1553[/C][C]130.5137[/C][C]11.4243[/C][/ROW]
[ROW][C]106[/C][C]0.1391[/C][C]-0.1815[/C][C]0.103[/C][C]374.8764[/C][C]154.95[/C][C]12.4479[/C][/ROW]
[ROW][C]107[/C][C]0.1357[/C][C]-0.1378[/C][C]0.1062[/C][C]242.4563[/C][C]162.9051[/C][C]12.7634[/C][/ROW]
[ROW][C]108[/C][C]0.1054[/C][C]-0.112[/C][C]0.1067[/C][C]282.5681[/C][C]172.877[/C][C]13.1483[/C][/ROW]
[ROW][C]109[/C][C]0.1065[/C][C]-0.1222[/C][C]0.1079[/C][C]364.3561[/C][C]187.6062[/C][C]13.6969[/C][/ROW]
[ROW][C]110[/C][C]0.1243[/C][C]-0.1397[/C][C]0.1101[/C][C]373.4144[/C][C]200.8782[/C][C]14.1732[/C][/ROW]
[ROW][C]111[/C][C]0.1372[/C][C]-0.0987[/C][C]0.1094[/C][C]162.8224[/C][C]198.3412[/C][C]14.0834[/C][/ROW]
[ROW][C]112[/C][C]0.1823[/C][C]-0.0409[/C][C]0.1051[/C][C]16.772[/C][C]186.9931[/C][C]13.6745[/C][/ROW]
[ROW][C]113[/C][C]0.2079[/C][C]-0.1214[/C][C]0.106[/C][C]119.9119[/C][C]183.0471[/C][C]13.5295[/C][/ROW]
[ROW][C]114[/C][C]0.2194[/C][C]-0.1585[/C][C]0.109[/C][C]193.459[/C][C]183.6256[/C][C]13.5509[/C][/ROW]
[ROW][C]115[/C][C]0.2191[/C][C]-0.1016[/C][C]0.1086[/C][C]83.7801[/C][C]178.3705[/C][C]13.3555[/C][/ROW]
[ROW][C]116[/C][C]0.2099[/C][C]-0.0993[/C][C]0.1081[/C][C]91.4856[/C][C]174.0263[/C][C]13.1919[/C][/ROW]
[ROW][C]117[/C][C]0.2215[/C][C]-0.0357[/C][C]0.1047[/C][C]11.1147[/C][C]166.2686[/C][C]12.8945[/C][/ROW]
[ROW][C]118[/C][C]0.2011[/C][C]-0.0831[/C][C]0.1037[/C][C]76.1964[/C][C]162.1744[/C][C]12.7348[/C][/ROW]
[ROW][C]119[/C][C]0.1936[/C][C]-0.0898[/C][C]0.1031[/C][C]100.0067[/C][C]159.4715[/C][C]12.6282[/C][/ROW]
[ROW][C]120[/C][C]0.1482[/C][C]-0.08[/C][C]0.1021[/C][C]140.8041[/C][C]158.6937[/C][C]12.5974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115444&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115444&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
970.0587-0.0344029.493400
980.07170.03520.034824.279226.88635.1852
990.0822-0.06040.043362.39238.72156.2227
1000.1123-0.07180.050453.436742.40036.5116
1010.1313-0.10210.060888.042651.52887.1784
1020.1416-0.05070.059120.553746.36636.8093
1030.1443-0.07060.060842.02745.74646.7636
1040.1408-0.17090.0745280.243875.05858.6636
1050.1508-0.25230.0943574.1553130.513711.4243
1060.1391-0.18150.103374.8764154.9512.4479
1070.1357-0.13780.1062242.4563162.905112.7634
1080.1054-0.1120.1067282.5681172.87713.1483
1090.1065-0.12220.1079364.3561187.606213.6969
1100.1243-0.13970.1101373.4144200.878214.1732
1110.1372-0.09870.1094162.8224198.341214.0834
1120.1823-0.04090.105116.772186.993113.6745
1130.2079-0.12140.106119.9119183.047113.5295
1140.2194-0.15850.109193.459183.625613.5509
1150.2191-0.10160.108683.7801178.370513.3555
1160.2099-0.09930.108191.4856174.026313.1919
1170.2215-0.03570.104711.1147166.268612.8945
1180.2011-0.08310.103776.1964162.174412.7348
1190.1936-0.08980.1031100.0067159.471512.6282
1200.1482-0.080.1021140.8041158.693712.5974


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = FALSE ; par2 = 0.5 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 1 ;
Parameters (R input):
par1 = 24 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = 0 ; par7 = 1 ; par8 = 0 ; par9 = 1 ; par10 = FALSE ;
R code (references can be found in the software module):