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Results for Quantile regression

Publications & Outputs

  1. Alcohol quantity and quality price elasticities: quantile regression estimates

    Pryce, R., Hollingsworth, B. P. & Walker, I., 30/04/2019, In: European Journal of Health Economics. 20, 3, p. 439-454 16 p.

    Research output: Contribution to journalJournal articlepeer-review

  2. Short term electricity demand forecasting using partially linear additive quantile regression with an application to the unit commitment problem

    Lebotsa, M. E., Sigauke, C., Bere, A., Fildes, R. & Boylan, J. E., 15/07/2018, In: Applied Energy. 222, p. 104-118 15 p.

    Research output: Contribution to journalJournal articlepeer-review

  3. Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets

    Haerdle, W., Lee Kuo Chuen, D., Nasekin, S. & Petukhina, A., 1/01/2018, In: Journal of Asset Management. 19, 1, p. 49-63 15 p.

    Research output: Contribution to journalJournal articlepeer-review

  4. Subcontracting and the survival of plants in the road construction industry: a panel quantile regression analysis

    De Silva, D. G., Kosmopoulou, G. & Lamarche, C., 05/2017, In: Journal of Economic Behavior and Organization. 137, p. 113-131 19 p.

    Research output: Contribution to journalJournal articlepeer-review

  5. Consistent design criteria for south China sea with a large-scale extreme value model

    Raghupathi, L., Randell, D., Jonathan, P. & Ewans, K. C., 2016, p. 844-863. 20 p.

    Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

  6. Threshold modeling of nonstationary extremes

    Northrop, P. J., Jonathan, P. & Randell, D., 2016, Extreme Value Modeling and Risk Analysis: Methods and Applications. CRC Press, p. 87-108 22 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

  7. Distributions of return values for ocean wave characteristics in the South China Sea using directional-seasonal extreme value analysis

    Randell, D., Feld, G., Ewans, K. & Jonathan, P., 2015, In: Environmetrics. 26, 6, p. 442-450 9 p.

    Research output: Contribution to journalJournal articlepeer-review

  8. Self-consistent estimation of conditional multivariate extreme distributions

    Liu, Y. & Tawn, J., 05/2014, In: Journal of Multivariate Analysis. 127, p. 19-35 17 p.

    Research output: Contribution to journalJournal articlepeer-review

  9. Omnidirectional return values for storm severity from directional extreme value models: The effect of physical environment and sample size

    Randell, D., Zanini, E., Vogel, M., Ewans, K. & Jonathan, P., 2014, ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering: Volume 4A: Structures, Safety and Reliability. ASME, 10 p. V04AT02A013

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

  10. Modelling covariate effects in extremes of storm severity on the Australian North West Shelf

    Randell, D., Wu, Y., Jonathan, P. & Ewans, K., 2013, ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering: Volume 2A: Structures, Safety and Reliability. ASME, 9 p. V02AT02A019

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

  11. Threshold modelling of spatially dependent non-stationary extremes with application to hurricane-induced wave heights

    Northrop, P. J. & Jonathan, P., 2011, In: Environmetrics. 22, 7, p. 799-809 11 p.

    Research output: Contribution to journalJournal articlepeer-review

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