نتایج جستجو برای: Truncated Gaussian Simulation

تعداد نتایج: 654783  

Journal: :international journal of mining and geo-engineering 0
omid asghari ut fatemeh amirpoursaeid simulation and data processing laboratory, school of mine engineering, college of engineering, university of tehran

truncated gaussian simulation (tgs) is a well-known method to generate realizations of the ore domains located in a spatial sequence. in geostatistical framework geological domains are normally utilized for stationary assumption. the ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. as a simple a...

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple a...

Journal: :journal of research in health sciences 0
shahrbanoo goli hossein mahjub abbas moghimbeigi jalal poorolajal ahmad heidari pahlavian

background : so far, several studies were conducted to estimate the prevalence of cigarette smoking in iran, but none of them used a statistical model to deal with unobserved smokers. the present study planned to estimate the accurate prevalence of cigarette smoking using mixture of truncated poisson distribution. methods : a cross-sectional study was conducted in hamadan, west of iran in 2009,...

2010
Alejandro Cáceres

Truncated Gaussian simulation (TGS) and plurigaussian simulation (PGS) are widely accepted methods for generating realisations of geological domains (lithofacies) that reproduce contact relationships. The realisations can be used to evaluate transfer functions related to the lithofacies occurrence, the simplest ones of which are the probability of occurrence of each lithofacies and the most pro...

Journal: :Comptes Rendus Geoscience 2016

1998
Hanfeng CHEN Jiahua CHEN

The authors study the asymptotic behaviour of the likelihood ratio statistic for testing homogeneity in the finite mixture models of a general parametric distribution family. They prove that the limiting distribution of this statistic is the squared supremum of a truncated standard Gaussian process. The autocorrelation function of the Gaussian process is explicitly presented. A re-sampling proc...

Journal: :journal of sciences, islamic republic of iran 2012
m. bolbolian ghalibaf

the purpose of this paper is to provide some asymptotic results for nonparametric estimator of the lorenz curve and lorenz process for the case in which data are assumed to be strong mixing subject to random left truncation. first, we show that nonparametric estimator of the lorenz curve is uniformly strongly consistent for the associated lorenz curve. also, a strong gaussian approximation for ...

Journal: :Information Fusion 2016
Andrew W. Palmer Andrew John Hill Steve Scheding

This paper develops an analytical method of truncating inequality constrained Gaussian distributed variables where the constraints are themselves described by Gaussian distributions. Existing truncation methods either assume hard constraints, or use numerical methods to handle uncertain constraints. The proposed approach introduces moment-based Gaussian approximations of the truncated distribut...

 Minimax estimation problems with restricted parameter space reached increasing interest within the last two decades Some authors derived minimax and admissible estimators of bounded parameters under squared error loss and scale invariant squared error loss In some truncated estimation problems the most natural estimator to be considered is the truncated version of a classic...

2017
Hassan Maatouk Xavier Bay

Statistical researchers have shown increasing interest in generating truncated multivariate normal distributions. In this paper, we only assume that the acceptance region is convex and we focus on rejection sampling. We propose a new algorithm that outperforms crude rejection method for the simulation of truncated multivariate Gaussian random variables. The proposed algorithm is based on a gene...

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