In order to overcome the difficulty of optimizing molecular geometry using quantum Monte Carlo methods, we introduce various approximations to the exact force expectation value. We follow Pulay’s suggestion @Mol. Phys. 17, 153 ~1969!# to correct the Hellmann–Feynman estimator by introducing the contributions due to the changes in the wave function with respect to the nuclear positions. When use...

Monte Carlo methods are used extensively in computational finance to estimate the price of financial derivative options. In this paper we review the use of quasi-Monte Carlo methods to obtain the same accuracy at a much lower computational cost, and focus on these key ingredients: i) the generation of Sobol and lattice points; ii) reduction of effective dimension using the principal component a...

We consider the estimation of dynamic binary choice models in a semiparametric setting, which per-period utility functions are known up to finite number parameters, but distribution shocks is left unspecified. This setup differs from most existing identification and literature for discrete models. To show we derive exploit new recursive representation unknown quantile function shocks. Our estim...

By allowing the regression coefficients to change with certain covariates, the class of varying coefficient models offers a flexible approach to modeling nonlinearity and interactions between covariates. This paper proposes a novel estimation procedure for the varying coefficient models based on local ranks. The new procedure provides a highly efficient and robust alternative to the local linea...

We report a theoretical description and numerical tests of the extended-system adaptive biasing force method (eABF), together with an unbiased estimator of the free energy surface from eABF dynamics. Whereas the original ABF approach uses its running estimate of the free energy gradient as the adaptive biasing force, eABF is built on the idea that the exact free energy gradient is not necessary...