Qi-Man Shao mostly deals with Random variable, Combinatorics, Applied mathematics, Mathematical analysis and Law of the iterated logarithm. His research integrates issues of Iterated logarithm and Distribution in his study of Random variable. His work carried out in the field of Combinatorics brings together such families of science as Gaussian process, Central limit theorem, Bounded function, Convergence of random variables and Independent and identically distributed random variables.
The study incorporates disciplines such as Estimator, Linear model, Statistics and Markov chain Monte Carlo in addition to Applied mathematics. His studies in Mathematical analysis integrate themes in fields like Martingale, Rate of convergence, Mathematical proof and Weak convergence. Qi-Man Shao works mostly in the field of Law of the iterated logarithm, limiting it down to concerns involving Zero and, occasionally, Upper and lower bounds, Generating function and Law of large numbers.
Qi-Man Shao mainly focuses on Combinatorics, Applied mathematics, Random variable, Mathematical analysis and Statistics. His Combinatorics study combines topics in areas such as Self normalized, Distribution and Independent and identically distributed random variables. His study explores the link between Applied mathematics and topics such as Markov chain Monte Carlo that cross with problems in Gibbs sampling.
His work in Random variable tackles topics such as Central limit theorem which are related to areas like Pure mathematics. His Mathematical analysis research is multidisciplinary, incorporating elements of Fractional Brownian motion, Brownian motion and Gaussian process. His study looks at the relationship between Law of the iterated logarithm and topics such as Iterated logarithm, which overlap with Large deviations theory.
His scientific interests lie mostly in Applied mathematics, Moderate deviations, Combinatorics, Self normalized and Random variable. In his works, Qi-Man Shao undertakes multidisciplinary study on Applied mathematics and Stein's method. His Combinatorics research includes themes of Distribution and Stationary sequence.
The various areas that he examines in his Self normalized study include Martingale, Independent and identically distributed random variables, Autoregressive model, Aperiodic graph and Random walk. The Random variable study combines topics in areas such as Sequence and Asymptotic distribution. His Concentration inequality research includes elements of Mathematical analysis and Moment.
Qi-Man Shao focuses on Applied mathematics, Stein's method, Moderate deviations, Random variable and Combinatorics. His Applied mathematics research incorporates elements of Covariate, Model selection, Spurious relationship, Covariance matrix and Statistics. His Statistics study which covers Linear combination that intersects with Spurious correlation and Empirical process.
The study of Random variable is intertwined with the study of Asymptotic distribution in a number of ways. In his study, which falls under the umbrella issue of Combinatorics, Dimension is strongly linked to Distribution. In his research on the topic of Self normalized, Concentration inequality and Moment is strongly related with Studentized range.
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Monte Carlo Methods in Bayesian Computation
Ming-Hui Chen;Qi-Man Shao;Joseph George Ibrahim.
Monte Carlo Estimation of Bayesian Credible and HPD Intervals
Ming-Hui Chen;Qi-Man Shao.
Journal of Computational and Graphical Statistics (1999)
Normal Approximation by Stein's Method
Louis H. Y. Chen;Larry Joel Goldstein;Qi-Man Shao.
Gaussian processes: Inequalities, small ball probabilities and applications
W.V. Li;Q.-M. Shao.
Handbook of Statistics (2001)
A Comparison Theorem on Moment Inequalities Between Negatively Associated and Independent Random Variables
Journal of Theoretical Probability (2000)
Self-Normalized Processes: Limit Theory and Statistical Applications
Víctor De la Peña;Tze Leung Lai;Qi-Man Shao.
Weak convergence for weighted empirical processes of dependent sequences
Qi-Man Shao;Hao Yu.
Annals of Probability (1996)
A general bahadur representation of M-estimators and its application to linear regression with nonstochastic designs
Xuming He;Qi-Man Shao.
Annals of Statistics (1996)
A New Skewed Link Model for Dichotomous Quantal Response Data
Ming-Hui Chen;Dipak K. Dey;Qi-Man Shao.
Journal of the American Statistical Association (1999)
Self-normalized large deviations
Annals of Probability (1997)
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