most citedA sieve M-theorem for bundled parameters in semiparametric models, with application to the efficient estimation in a linear model for censored data

68 citations · 70 across the 2 of their papers we have counts for

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2 papers

math.ST2012★ 68 cited

A sieve M-theorem for bundled parameters in semiparametric models, with application to the efficient estimation in a linear model for censored data

Ying Ding, Bin Nan

In many semiparametric models that are parameterized by two types of parameters---a Euclidean parameter of interest and an infinite-dimensional nuisance parameter---the two paramet…

physics.bio-ph2009★ 2 cited

Efficient equilibrium sampling of all-atom peptides using library-based Monte Carlo

Ying Ding, Artem B. Mamonov, Daniel M. Zuckerman

We applied our previously developed library-based Monte Carlo (LBMC) to equilibrium sampling of several implicitly solvated all-atom peptides. LBMC can perform equilibrium sampling…