‎Recently a first-order Spatial Integer-valued Autoregressive‎ ‎SINAR(1,1) model was introduced to model spatial data that comes‎ ‎in counts citep{ghodsi2012}‎. ‎Some properties of this model‎ ‎have been established and the Yule-Walker estimator has been‎ ‎proposed for this model‎. ‎In this paper‎, ‎we introduce the...

Given uncertainty in the input model and parameters of a simulation study, the goal of the simulation study often becomes the estimation of a conditional expectation. The conditional expectation is expected performance conditional on the selected model and parameters. The distribution of this conditional expectation describes precisely, and concisely, the impact of input uncertainty on performa...

This paperreviews the three Conditional techniques for high performance flip-flops namely Conditional Precharge, Conditional Capture and Conditional Discharge. The classification of these techniques is based on how to prevent or reduce the unnecessary internal switching activities and reviewed in terms of Power and Delay.Comparison summary of flip-flops characteristics based on these techniques...

An iterative co-conditional Monte Carlo simulation (IMCS) approach is developed. This approach derives co-conditional means and variances of transmissivity (T), head (f), and Darcy’s velocity (q), based on sparse measurements of T and f in heterogeneous, confined aquifers under steady-state conditions. It employs the classical co-conditional Monte Carlo simulation technique (MCS) and a successi...

In this paper, we discuss dierent predictors of times to failure of units censored in multiple stages in a progressively censored  sample from proportional hazard rate models. The maximum likelihood predictors, best unbiased predictors and conditional median predictors are considered. We also consider Bayesian point predictors for the times to failure of units. A numerical example and a Monte C...

A "realistic" interpolation or extrapolation of bathymetry, i.e., one that honors both the statistical character and the deterministic constraints of the data, is referred to as a "conditional simulation." The first step in generating a conditional simulation is derivation of a statistical model for bathymetry. We typically employ the anisotropic von Kármán model (Goff and Jordan, 1988), which ...

A new simulation approach, called`subset simulation', is proposed to compute small failure probabilities encountered in reliability analysis of engineering systems. The basic idea is to express the failure probability as a product of larger conditional failure probabilities by introducing intermediate failure events. With a proper choice of the conditional events, the conditional failure probab...

We consider inference procedures, conditional on an observed ancillary statistic, for regression coefficients under a linear regression setup where the unknown error distribution is specified nonparametrically. We establish conditional asymptotic normality of the regression coefficient estimators under regularity conditions, and formally justify the approach of plugging in kernel-type density e...