The relative free energias of hydration of dimethyl phosphate anion in gauchegauche, gauchetrans, and trans-trans conformations of phosphodiester torsion angles, computed with Monte Carlo method in the (T, V, N) ensemble at 25 OC, are reported. The free energy differences are determined by the probability ratio method using both umbrella sampling with harmonic weighting functions and adaptive u...

This paper presents an extension to our work on estimating the probability distribution by using a Markov Random Field (MRF) model in an Estimation of Distribution Algorithm (EDA) [1]. We propose a method that directly samples a MRF model to generate new population. We also present a new EDA, called the Distribution Estimation Using MRF with direct sampling (DEUMd), that uses this method, and i...

When conducting simulation for evaluating complex system reliability or availability, method of random sampling is applied to simulate fault occasion of complex system. Current research of fault sampling generally assumes maintenance activity restores systems to “good-as-new” and “bad-as-old” without considering “partly good” situation. However, system usually keeps its function through imperfe...

Monte Carlo simulation provides the benchmark for computational methods in reliability assessment in terms of both accuracy and robustness. However, Monte Carlo methods are well-known to be computationally expensive and, in many cases, intractable. Several improvements have been proposed to increase their computational efficiency for reliability analysis including Latin hypercube sampling; see ...

Particle filtering is a sequential Monte Carlo method [3] that uses importance sampling to draw samples from probability distributions. In a particle filter the target state is represented by a point mass particle set that is propagated and updated using conditional probability representations of the motion model and measurement model. Methods that improve the sampling efficiency include [3] re...

Because of high costs or complex logistics, scientific populations cannot be measured entirely and must be sampled. Accepted scientific practice holds that sample selection be based on statistical principles to assure objectivity when estimating totals and variances. Probability sampling--obtaining samples with known probabilities--is the only method that assures these results. However, probabi...

The Ziggurat Algorithm is a very fast rejection sampling method for generating PseudoRandom Numbers (PRNs) from statistical distributions. In the algorithm, rectangular sampling domains are layered on top of each other (resembling a ziggurat) to encapsulate the desired probability density function. Random values within these layers are sampled and then returned if they lie beneath the graph of ...

the aim of this study was to evaluate suicide probability in iranian males with substance abuse or dependence disorder and to investigate the predictors of suicide probability based on trait mindfulness, reasons for living and severity of general psychiatric symptoms.participants were 324 individuals with substance abuse or dependence in an outpatient setting and prison. reasons for living ques...

The Cross Entropy method is a well-known adaptive importance sampling method for rare-event probability estimation, which requires estimating an optimal importance sampling density within a parametric class. In this article we estimate an optimal importance sampling density within a wider semiparametric class of distributions. We show that this semiparametric version of the Cross Entropy method...

A method of window exchange umbrella sampling molecular dynamics simulation is employed for transmembrane helix assembly. An analytical expression for the average acceptance probability between neighboring windows is derived and combined with the first passage time optimization method to predetermine a parameter set in an optimal range. With the parameter set, the method provides a substantiall...