Search results for " Sampling"
showing 10 items of 375 documents
A new strategy for effective learning in population Monte Carlo sampling
2016
In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.
Cross-entropy-based adaptive optimization of simulation parameters for Markovian-driven service systems
2005
Abstract Markov fluid models represent a general description of the process of service request arrivals to service systems. The solution of performance analysis problems incorporating them often calls for a simulation approach, for which a reference methodology is Importance Sampling. However, in this case the appropriate choice of the biasing conditions is a problem in itself. In this paper an iterative method based on the cross-entropy is proposed for this choice. The equations are given that allow to derive the biasing conditions from the simulation itself. The application of the proposed method to three different sample cases, referring to one transient scenario (finite time horizon and…
A Quick Simulation Technique for a Fluid Information Storage Problem
2001
Summary In this paper we present an application of Importance Sampling (IS) for quick simulation of buffer overflow probability in a statistical multiplexer loaded with a number of independent Markov modulated fluid sources. Runtime improvement is deducible from NMCσ2(p) and NISσ2(p*) that characterize the trade-offs between sample size and variance of the estimators of buffer overflow probability experienced in Monte Carlo (MC) and Importance Sampling simulations. By assuming that the same precision is achieved for the two kinds of simulations if σ2(p)=σ2(p*), an approximate closed form expression for the ratio NIS/NMC is derived, and it is minimized with respect to the load of the multipl…
Anti-tempered Layered Adaptive Importance Sampling
2017
Monte Carlo (MC) methods are widely used for Bayesian inference in signal processing, machine learning and statistics. In this work, we introduce an adaptive importance sampler which mixes together the benefits of the Importance Sampling (IS) and Markov Chain Monte Carlo (MCMC) approaches. Different parallel MCMC chains provide the location parameters of the proposal probability density functions (pdfs) used in an IS method. The MCMC algorithms consider a tempered version of the posterior distribution as invariant density. We also provide an exhaustive theoretical support explaining why, in the presented technique, even an anti-tempering strategy (reducing the scaling of the posterior) can …
<p>Preoperative Anemia and Iron Deficiency Screening, Evaluation and Management: Barrier Identification and Implementation Strategy Mapping<…
2020
Introduction and aims: Patients undergoing major surgery risk significant blood loss and transfusion, which increases substantially if they have pre-existing anemia. Preoperative Anemia and Iron Deficiency Screening, Evaluation and Management Pathways (PAIDSEM-P) outline recommended blood tests and treatment to optimize patients before surgery. Documented success using PAIDSEM-P to reduce transfusions and improve patient outcomes exists, but the reporting quality of such studies is suboptimal. It remains unclear what implementation strategies best support the implementation of PAIDSEM-P. Method: Maximum variation, purposive sampling was used to recruit a total of 15 partici-pants, including…
Comparing cetacean abundance estimates derived from spatial models and design-based line transect methods
2007
Spatial modelling is increasingly being used as an alternative to conventional design- based line transect sampling to estimate cetacean abundance. This new method combines line transect sampling with spatial analysis to predict animal abundance based on the relationship of ani- mals observed to environmental factors. It presents several advantages including: (1) the ability to use data collected from 'platforms of opportunity', (2) the ability to estimate abundance for any defined subarea within the study area, and (3) the possibility for increased precision if covariates explain sufficient variability in the data. One study has been conducted to compare spatial modelling with conventional…
A Bayesian direction-of-arrival model for an undetermined number of sources using a two-microphone array.
2014
Sound source localization using a two-microphone array is an active area of research, with considerable potential for use with video conferencing, mobile devices, and robotics. Based on the observed time-differences of arrival between sound signals, a probability distribution of the location of the sources is considered to estimate the actual source positions. However, these algorithms assume a given number of sound sources. This paper describes an updated research account on the solution presented in Escolano et al. [J. Acoust. Am. Soc. 132(3), 1257-1260 (2012)], where nested sampling is used to explore a probability distribution of the source position using a Laplacian mixture model, whic…
Estimate the mean electricity consumption curve by survey and take auxiliary information into account
2012
In this thesis, we are interested in estimating the mean electricity consumption curve. Since the study variable is functional and storage capacities are limited or transmission cost are high survey sampling techniques are interesting alternatives to signal compression techniques. We extend, in this functional framework, estimation methods that take into account available auxiliary information and that can improve the accuracy of the Horvitz-Thompson estimator of the mean trajectory. The first approach uses the auxiliary information at the estimation stage, the mean curve is estimated using model-assisted estimators with functional linear regression models. The second method involves the au…
La hora de la evaluación ambulatoria [Recurso electrónico] = The time of ambulatory assessment /
2022
La evaluación ambulatoria aglutina un conjunto de métodos que permiten evaluar mediante dispositivos móviles, y en múltiples momentos temporales, el comportamiento de las personas en su entorno natural y contexto diario. Permite una evaluación más precisa, dinámica, contextual e ideográfica que los métodos clásicos, abriendo nuevos horizontes con claras implicaciones para el diagnóstico y la intervención psicológica. El objetivo de este trabajo es realizar una introducción a la evaluación ambulatoria. En primer lugar, se realiza una delimitación conceptual y se comentan las cuestiones que viene a solucionar y sus posibles beneficios. En segundo lugar, se exponen aspectos relacionados con la…
Health literacy of pregnant women and duration of breastfeeding maintenance: a feasibility study
2020
Research the association between health literacy (HL) and exclusive breastfeeding at 4-months postpartum.Despite the benefits of breastfeeding (BF), its rates are low worldwide. Among the reasons for abandonment is the level of maternal education. Maternal education has been associated with HL, but evidence between HL and BF maintenance is limited.A cross-sectional study.The sample compromised 229 nursing mothers recruited from January 2018 to the end of December 2018 at Spain by systematic sampling method. Women were interviewed postpartum on parameters associated with the start and continuation of BF up to 4 months postpartum. Multivariate logistic regression models to explain exposure va…