Uncertainty Quantification In Forecasting

Uncertainty Quantification in Forecasting is a methodological framework within procurement forecasting that characterizes and measures the uncertainty associated with predicted demand, supply, or cost estimates by specifying probabilistic bounds, confidence intervals, or predictive distributions to distinguish it from deterministic point forecasts.

109

Publications

7.6K

Citations

283

Authors

182

Institutions

Publications per year

2017–2026

48

Authors

283

  1. JT
    Joseph Tracy

    National Bureau of Economic Research, United States

    3 publications · 178 citations

    3

    h-index

  2. CS
    Chi‐Wei Su

    Qingdao University, China

    3 publications · 133 citations

    3

    h-index

  3. AG
    Anil Gaba

    INSEAD, Singapore

    3 publications · 288 citations

    3

    h-index

  4. KF
    Kenneth F. Wallis

    University of Warwick, United Kingdom

    3 publications · 312 citations

    3

    h-index

  5. RW
    Robert W. Rich

    Federal Reserve Bank of Cleveland, United States

    3 publications · 178 citations

    3

    h-index

1–5 of 283

Venues

  1. SSRN Electronic Journal

    Repository · 8 publications · 263 citations

    8

    h-index

  2. International Journal of Forecasting

    4 publications · 330 citations

    4

    h-index

  3. RePEc: Research Papers in Economics

    Repository · 2 publications · 40 citations

    2

    h-index

  4. International Petroleum Technology Conference

    Conference · 2 publications · 36 citations

    2

    h-index

  5. SPE Annual Technical Conference and Exhibition

    Conference · 2 publications · 39 citations

    2

    h-index

1–5