subjective forecast【气象】 - PMC

Nikos I. Bosse, Sam Abbott, Johannes Bracher, Habakuk Hain, Billy J. Quilty, Mark Jit, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Edwin van Leeuwen, Anne Cori, Sebastian Funk

PLoS Comput Biol. 2022 Sep; 18(9): e1010405. Published online 2022 Sep 19. doi: 10.1371/journal.pcbi.1010405

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Mortality and life expectancy forecast for (comparatively) high mortality countries

Ahbab Mohammad Fazle Rabbi, Stefano Mazzuco

Genus. 2018; 74(1): 18. Published online 2018 Nov 1. doi: 10.1186/s41118-018-0042-x

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Forecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey

Fatma Carman Cevik, Basak Gever, Nihat Tak, Tahir Khaniyev

Soft comput. 2023; 27(5): 2509–2535. Published online 2023 Jan 5. doi: 10.1007/s00500-022-07800-7

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Chimeric forecasting: combining probabilistic predictions from computational models and human judgment

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A survey of human judgement and quantitative forecasting methods

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R Soc Open Sci. 2021 Feb; 8(2): 201187. Published online February 24, 2021. doi: 10.1098/rsos.201187

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Global forecasting of thermal health hazards: the skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI)

F. Pappenberger, G. Jendritzky, H. Staiger, E. Dutra, F. Di Giuseppe, D. S. Richardson, H. L. Cloke

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Testing the reliability of forecasting systems

J. Bröcker

J Appl Stat. 2023; 50(1): 106–130. Published online 2021 Sep 30. doi: 10.1080/02664763.2021.1981833

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Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions

Devon A. Gaydos, Chris M. Jones, Shannon K. Jones, Garrett C. Millar, Vaclav Petras, Anna Petrasova, Helena Mitasova, Ross K. Meentemeyer

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Forecasting national and regional influenza-like illness for the USA

Michal Ben-Nun, Pete Riley, James Turtle, David P. Bacon, Steven Riley

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Firdos Khan, Shaukat Ali, Alia Saeed, Ramesh Kumar, Abdul Wali Khan

PLoS One. 2021; 16(6): e0253367. Published online 2021 Jun 17. doi: 10.1371/journal.pone.0253367

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A Human Resource Demand Forecasting Method Based on Improved BP Algorithm

Xingguang Lu

Comput Intell Neurosci. 2022; 2022: 3534840. Published online 2022 Mar 29. doi: 10.1155/2022/3534840

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Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods

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PLoS One. 2022; 17(3): e0266096. Published online 2022 Mar 29. doi: 10.1371/journal.pone.0266096

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Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries

Andreas Graefe, Kesten C. Green, J. Scott Armstrong

PLoS One. 2019; 14(1): e0209850. Published online 2019 Jan 10. doi: 10.1371/journal.pone.0209850

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Methods for Small Area Population Forecasts: State-of-the-Art and Research Needs

Tom Wilson, Irina Grossman, Monica Alexander, Phil Rees, Jeromey Temple

Popul Res Policy Rev. 2022; 41(3): 865–898. Published online 2021 Aug 16. doi: 10.1007/s11113-021-09671-6

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Tourism Demand Interval Forecasting Amid COVID-19: A Hybrid Model With a Modified Multi-Objective Optimization Algorithm

Jianzhou Wang, Lifang Zhang, Zhenkun Liu, Xiaojia Huang

Journal of Hospitality & Tourism Research. 2023 Jan 13 : 10963480221142873. Published online 2023 Jan 13. doi: 10.1177/10963480221142873

PMCID:: PMC9841211

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Fig 3The Bayesian forecast and true probabilities.

(A) The median Bayesian estimate closely tracks the true underlying probability in each bin. (B) The median Bayesian responses corresponding to the sessions completed by each individual generate very small dispersion around the diagonal. (C) and (D) Much of the deviation in the subjective probability forecasts from the true probabilities reflect deviations from the Bayesian forecast.

Individual differences in the perception of probability

PLoS Comput Biol. 2021 Apr;17(4):e1008871.
Figure 1.

Subjective Survivor Functions for Men Aged 52

Using Subjective Expectations to Forecast Longevity: Do Survey Respondents Know Something We Don’t Know?

Demography. 2008 Feb;45(1):95-113.
Figure 4.

Subjective Survivor Function Versus Actual Mortality Experience for Men Aged 51–61

Using Subjective Expectations to Forecast Longevity: Do Survey Respondents Know Something We Don’t Know?

Demography. 2008 Feb;45(1):95-113.
Figure 5.

Subjective Survivor Functions Versus Actual Mortality Experience for Women Aged 51–61

Using Subjective Expectations to Forecast Longevity: Do Survey Respondents Know Something We Don’t Know?

Demography. 2008 Feb;45(1):95-113.