Conditional simulation of ergodic and stationary Gaussian random fields using successive residuals is a new approach used to overcome the size limitations of the LU decomposition algorithm as well as provide fast updating of existing simulated realizations with new data. This paper discusses two different implementations of this approach. The implementations differ in the use of the new informa...

We introduce fast millimeter-wave base station (BS) and its antenna sector selection for user equipment based on its location. Using a conditional random field inference model with specially designed parameters, which are robust to change of environment, InferBeam allows the use of measurement samples on best beam selection at a small number of locations to infer the rest dynamically. Compared ...

A diffusion-influenced pseudo-first order reversible reaction A + B ↔C + B is investigated by the molecular dynamics (MD) simulation method. Theoretical finding that the temporal evolution of reactants [conditional probabilities] in the reversible system can be expressed by the irreversible survival probability with an effective rate parameter is confirmed even in the presence of solvent partic...

In this paper, the problem of predicting times to failure of units censored in multiple stages of progressively hybrid censoring for the proportional hazards family is considered. We discuss different classical predictors. The best unbiased predictor ($BUP$), the maximum likelihood predictor ($MLP$) and conditional median predictor ($CMP$) are all derived. As an example, the obtained results ar...

In a two-level nested simulation, an outer level of simulation samples scenarios, while the inner level uses simulation to estimate a conditional expectation given the scenario. Applications include financial risk management, assessing the effects of simulation input uncertainty, and computing the expected value of gathering more information in decision theory. We show that an ANOVA-like estima...

We suggest a discrete-time approximation for decoupled forward-backward stochastic differential equations. The L norm of the error is shown to be of the order of the time step. Given a simulation-based estimator of the conditional expectation operator, we then suggest a backward simulation scheme, and we study the induced L error. This estimate is more investigated in the context of the Malliav...