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Stat 548, H. Joe

The list of papers was updated in August 2024; the themes in the list are modern multivariate and time series analysis.

Geenens, Charpentier and Paindaveine (2017). Probit transformation for nonparametric kernel estimation of the copula density. Bernoulli 23(3), 1848-1873.
(download paper as pdf) https://doi.org/10.3150/15-BEJ798

Palacios-Rodrı́guez, Toulemonde, Carreau and Opitz (2020). Generalized Pareto processes for simulating space-time extreme events: an application to precipitation reanalyses. Stochastic Environmental Research and Risk Assessment 34:2033-2052.
(download paper as pdf) https://doi.org/10.1007/s00477-020-01895-w

  • Nikoloulopoulos (2016). Efficient estimation of high-dimensional multivariate normal copula models with discrete spatial responses. Stochastic Environmental Research and Risk Assessment, 30(2):493-505, 2016.
    (download paper as pdf) https://doi.org/10.1007/s00477-015-1060-2

  • Scotto, Weiss, Silva, Pereira (2014). Bivariate binomial autoregressive models. Journal of Multivariate Analysis 125, 233-251.
    (download paper as pdf) https://doi.org/10.1016/j.jmva.2013.12.014

  • Rootzen, Segers, Wadsworth (2018). Multivariate generalized Pareto distributions: Parametrizations, representations, and properties. Journal of Multivariate Analysis 165, 117-131.
    (download paper as pdf) https://doi.org/10.1016/j.jmva.2017.12.003

  • Otneim and Tjostheim (2017). The locally Gaussian density estimator for multivariate data. Stat Comput 27:1595-1616.
    (download paper as pdf) https://doi.org/10.1007/s11222-016-9706-6

  • Trapin (2018). Can Volatility Models Explain Extreme Events? Journal of Financial Econometrics, Vol. 16, No. 2, 297-315.
    (download paper as pdf) https://doi.org/10.1093/jjfinec/nbx031

  • Xia and Li (2021). Copula-based partial correlation screening: a joint and robust approach Statistica Sinica 31, 421-447.
    (download paper as pdf) https://doi.org/10.5705/ss.202018.0219


    Motivational note

    Note that it is to your advantage to learn to critically read research papers early in a PhD program, and then proceed to doing research and writing/submitting/publishing research manuscripts. Chances of getting a fellowship/scholarship and getting an academic position after a PhD program, increase a lot if you have submitted papers during your PhD studies.

    See also Statistical Research: Some Advice for Beginners, an article by Hamada and Sitter, American Statistician, May 2004, v 58, 93-101.

    Manage your time well and develop professional skills (e.g., communication, research, computer, teaching/presentation) to enhance your job opportunities. See the IMS new researchers guide

    How to read the statistical methods literature: a guide for students , an article by James Murphy, American Statistician, May 1997, v 51, 155-157.

    Another useful article if you are looking ahead: How to Get a Job in Academics, by EA Stasny, American Statistician, Feb 2001, v 55, 35-40.