Mean absolute error (MAE) of our prediction model by province and step forward (in biweeks).

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted–Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted – Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Average forecast skill by region, averaged over all seasons and targets (sm,r,.,.,.).

Dave Osthus (3216351)
Ashlynn R. Daughton (3155625)
Reid Priedhorsky (660106)

February 2019

Regions are ordered by increasing DBMperfect average forecast skill. For all regions, DBM has the lo...

Relative mean absolute error (MAE) comparing our prediction model vs. a model that predicts a seasonal median, by province and step forward (in biweeks).

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

Results to the left of the dotted line signify more accurate predictions from our models when com...

Comparison of province-level prediction accuracy between full-data and real-time predictions, by prediction horizon.

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

These calculations assume that both the full-data and real-time multi-step predictions began at t...

Summary of real-time prediction accuracy, by prediction horizon.

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

These results are aggregated across all provinces. The R2 and 95% PI coverage c...

Observed census counts plotted from the finer census administrative units versus the summed grid cell values from the population map estimated using coarser administrative units for a) Cambodia, b) Vietnam, and c) Kenya.

Forrest R. Stevens (281628)
Andrea E. Gaughan (281627)
Catherine Linard (40355)
Andrew J. Tatem (82578)

February 2015

Dotted lines in each figure represent the 1:1 line and prediction error is stated for each countr...

Forecasting performance comparison by RMSE, MAE and MAPE.

Yan-Ling Zheng (701006)
Li-Ping Zhang (1489732)
Xue-Liang Zhang (701007)
Kai Wang (21246)
Yu-Jian Zheng (701008)

March 2015

RMSE = root mean square error, MAE = mean absolute error and MAPE = mean absolute percentage erro...

Mean Absolute Error (MAE) values for various durations of meteorological data for the peak day prediction under the 2.5% and 5% start day criteria.

Ahmad Kakakhail (17896581)
Aimal Rextin (7534778)
Jeroen Buters (569767)
Chun Lin (680865)
José M. Maya-Manzano (17896584)
Mehwish Nasim (7534784)
Jose Oteros (17896587)
Antonio Picornell (17896590)
Hillary Pinnock (17896593)
Jurgen Schwarze (5653597)
Osman Yusuf (4996679)

February 2024

This was done only for the training years as the testing years were reserved to evaluate the perform...

Forecasting Results of the population structures for China, India, and Vietnam (Unit: %).

Yigang Wei (4836318)
Zhichao Wang (3570413)
Huiwen Wang (1731532)
Yan Li (23143)
Zhenyu Jiang (646556)

April 2019

Forecasting Results of the population structures for China, India, and Vietnam (Unit: %).</p

Comparison of the mean absolute error (MAE) and root mean square error (RMSE) of the proposed model with other state-of-art forecasting methods for all three offshore windfarms.

Mansoor Khan (1688455)
Essam A. Al-Ammar (11307715)
Muhammad Rashid Naeem (11307718)
Wonsuk Ko (11307721)
Hyeong-Jin Choi (11307724)
Hyun-Koo Kang (11307727)

August 2021

Comparison of the mean absolute error (MAE) and root mean square error (RMSE) of the proposed model ...

Fig 3 -

Ahmad Kakakhail (17896581)
Aimal Rextin (7534778)
Jeroen Buters (569767)
Chun Lin (680865)
José M. Maya-Manzano (17896584)
Mehwish Nasim (7534784)
Jose Oteros (17896587)
Antonio Picornell (17896590)
Hillary Pinnock (17896593)
Jurgen Schwarze (5653597)
Osman Yusuf (4996679)

February 2024

Mean Absolute Error (MAE) calculated over various time intervals using their corresponding meteorolo...

Analysis of absolute error score for world, Brazil, India, and Indonesia.

Michael S. Deiner (4370119)
Lee Worden (816205)
Alex Rittel (4370113)
Sarah F. Ackley (4370116)
Fengchen Liu (432859)
Laura Blum (4370122)
James C. Scott (116228)
Thomas M. Lietman (106610)
Travis C. Porco (116223)

August 2017

Columns refer to overall forecast error in predicted number of cases for the world, Brazil, India...

Prediction error percentages of PCA, Sparse LAP and LAP approaches of assigning individuals to their continental memberships.

Jun Zhang (48506)

February 2013

Prediction error percentages of PCA, Sparse LAP and LAP approaches of assigning individuals to th...

Comparison of the forecast error between metapopulation and homogeneous models.

Masaya M. Saito (460475)
Hiroshi Nishiura (65852)
Tomoyuki Higuchi (133868)

October 2018

The horizontal axis measures the date on which forecasting was made. The vertical axis measures the ...

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted–Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted – Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Average forecast skill by region, averaged over all seasons and targets (sm,r,.,.,.).

Dave Osthus (3216351)
Ashlynn R. Daughton (3155625)
Reid Priedhorsky (660106)

February 2019

Regions are ordered by increasing DBMperfect average forecast skill. For all regions, DBM has the lo...

Relative mean absolute error (MAE) comparing our prediction model vs. a model that predicts a seasonal median, by province and step forward (in biweeks).

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

Results to the left of the dotted line signify more accurate predictions from our models when com...

Comparison of province-level prediction accuracy between full-data and real-time predictions, by prediction horizon.

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

These calculations assume that both the full-data and real-time multi-step predictions began at t...

Summary of real-time prediction accuracy, by prediction horizon.

Nicholas G. Reich (167708)
Stephen A. Lauer (716220)
Krzysztof Sakrejda (2837681)
Sopon Iamsirithaworn (260152)
Soawapak Hinjoy (332639)
Paphanij Suangtho (2837678)
Suthanun Suthachana (2837675)
Hannah E. Clapham (2157634)
Henrik Salje (589157)
Derek A. T. Cummings (116201)
Justin Lessler (116180)

June 2016

These results are aggregated across all provinces. The R2 and 95% PI coverage c...

Observed census counts plotted from the finer census administrative units versus the summed grid cell values from the population map estimated using coarser administrative units for a) Cambodia, b) Vietnam, and c) Kenya.

Forrest R. Stevens (281628)
Andrea E. Gaughan (281627)
Catherine Linard (40355)
Andrew J. Tatem (82578)

February 2015

Dotted lines in each figure represent the 1:1 line and prediction error is stated for each countr...

Forecasting performance comparison by RMSE, MAE and MAPE.

Yan-Ling Zheng (701006)
Li-Ping Zhang (1489732)
Xue-Liang Zhang (701007)
Kai Wang (21246)
Yu-Jian Zheng (701008)

March 2015

RMSE = root mean square error, MAE = mean absolute error and MAPE = mean absolute percentage erro...

Mean Absolute Error (MAE) values for various durations of meteorological data for the peak day prediction under the 2.5% and 5% start day criteria.

Ahmad Kakakhail (17896581)
Aimal Rextin (7534778)
Jeroen Buters (569767)
Chun Lin (680865)
José M. Maya-Manzano (17896584)
Mehwish Nasim (7534784)
Jose Oteros (17896587)
Antonio Picornell (17896590)
Hillary Pinnock (17896593)
Jurgen Schwarze (5653597)
Osman Yusuf (4996679)

February 2024

This was done only for the training years as the testing years were reserved to evaluate the perform...

Forecasting Results of the population structures for China, India, and Vietnam (Unit: %).

Yigang Wei (4836318)
Zhichao Wang (3570413)
Huiwen Wang (1731532)
Yan Li (23143)
Zhenyu Jiang (646556)

April 2019

Forecasting Results of the population structures for China, India, and Vietnam (Unit: %).</p

Comparison of the mean absolute error (MAE) and root mean square error (RMSE) of the proposed model with other state-of-art forecasting methods for all three offshore windfarms.

Mansoor Khan (1688455)
Essam A. Al-Ammar (11307715)
Muhammad Rashid Naeem (11307718)
Wonsuk Ko (11307721)
Hyeong-Jin Choi (11307724)
Hyun-Koo Kang (11307727)

August 2021

Comparison of the mean absolute error (MAE) and root mean square error (RMSE) of the proposed model ...

Fig 3 -

Ahmad Kakakhail (17896581)
Aimal Rextin (7534778)
Jeroen Buters (569767)
Chun Lin (680865)
José M. Maya-Manzano (17896584)
Mehwish Nasim (7534784)
Jose Oteros (17896587)
Antonio Picornell (17896590)
Hillary Pinnock (17896593)
Jurgen Schwarze (5653597)
Osman Yusuf (4996679)

February 2024

Mean Absolute Error (MAE) calculated over various time intervals using their corresponding meteorolo...

Analysis of absolute error score for world, Brazil, India, and Indonesia.

Michael S. Deiner (4370119)
Lee Worden (816205)
Alex Rittel (4370113)
Sarah F. Ackley (4370116)
Fengchen Liu (432859)
Laura Blum (4370122)
James C. Scott (116228)
Thomas M. Lietman (106610)
Travis C. Porco (116223)

August 2017

Columns refer to overall forecast error in predicted number of cases for the world, Brazil, India...

Prediction error percentages of PCA, Sparse LAP and LAP approaches of assigning individuals to their continental memberships.

Jun Zhang (48506)

February 2013

Prediction error percentages of PCA, Sparse LAP and LAP approaches of assigning individuals to th...

Comparison of the forecast error between metapopulation and homogeneous models.

Masaya M. Saito (460475)
Hiroshi Nishiura (65852)
Tomoyuki Higuchi (133868)

October 2018

The horizontal axis measures the date on which forecasting was made. The vertical axis measures the ...

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted–Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Model errors and p-values assessed using population count error as a proportion of actual district population: |Predicted – Actual|/Actual.

Weston Anderson (1654783)
Seth Guikema (2225395)
Ben Zaitchik (2225392)
William Pan (69006)

July 2014

Model errors and p-values assessed using population count error as a proportion of actual distric...

Average forecast skill by region, averaged over all seasons and targets (sm,r,.,.,.).

Dave Osthus (3216351)
Ashlynn R. Daughton (3155625)
Reid Priedhorsky (660106)

February 2019

Regions are ordered by increasing DBMperfect average forecast skill. For all regions, DBM has the lo...

Mean absolute error (MAE) of our prediction model by province and step forward (in biweeks).

Abstract

Extracted data

Mean absolute error (MAE) of our prediction model by province and step forward (in biweeks).

Abstract

Extracted data

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