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Per Mykland is the Maynard Hutchins Distinguished Service Professor in the Department of Statistics and the College at the University of Chicago. His research focuses on the analysis of longitudinal data, with particular expertise in survival analysis and inference for time series. He applies differential equations and stochastic simulation methods in his work. Mykland's research interests extend to the design of experiments and observational studies, particularly in the context of finance and economics, with an emphasis on financial econometrics. He studies topics such as pricing and hedging of derivative securities and high-frequency data, aiming to provide insights into risk management and statistical uncertainty related to prices. His work involves the application of likelihood theory, martingales, and nonparametric likelihood methods, focusing on analyzing and improving asymptotic approximations and sampling distributions, including likelihood methods, asymptotic expansions, resampling techniques, and more.
Department of Philosophy