Search results for "bayesian"
showing 10 items of 604 documents
Hierarchical structure of the Sicilian goats revealed by Bayesian analyses of microsatellite information
2011
Summary Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (AMOVA UST estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (AMOVA USC estimate). The analyses and methods applied in th…
Does social capital matter for European regional growth?
2015
Abstract This paper analyzes the role of different elements of social capital in economic growth for a sample of 85 European regions during the period 1995–2008. Despite the remarkable progress that social capital and European regional economic growth literatures have experienced over the last two decades, initiatives combining the two are few, and entirely yet to come for the post-1990s period. Recent improvements in data availability allow this gap in the literature to be closed, since they enable the researcher to consider the traditionally disregarded Eastern and Central European (ECE) regions. This is particularly interesting, as they are all transition economies that recently joined t…
WEIGHTED-AVERAGE LEAST SQUARES (WALS): A SURVEY
2014
Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted- average least squares (WALS) is a recent model-average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications.
Sampling properties of the Bayesian posterior mean with an application to WALS estimation
2022
Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these learning methods in repeated samples is assessed using the variance of the posterior distribution of the parameters of interest given the data. This may be permissible when the sample size is large because, under the conditions of the Bernstein--von Mises theorem, the posterior variance agrees asymptotically with the frequentist variance. In finite samples, however, things are less clear. In this pa…
Nonlinear impact estimation in spatial autoregressive models
2018
International audience; This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in…
Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging
2021
En este artículo analizamos los determinantes del stock de FDI saliente de Japón para el período 1996–2017. Este período es especialmente relevante ya que abarca un proceso de creciente globalización económica y dos crisis financieras. Para ello, consideramos un amplio conjunto de variables candidatas basadas en la teoría, así como en análisis empíricos previos. Nuestra muestra incluye un total de 27 países anfitriones. Seleccionamos las covariables utilizando una metodología basada en datos, el análisis Bayesian Model Averaging (BMA). Además, también analizamos si estos determinantes cambian según el grado de desarrollo (emergentes vs desarrollados) o las áreas geográficas (UE vs Asia Orie…
A Multisite Preregistered Paradigmatic Test of the Ego-Depletion Effect
2021
We conducted a preregistered multilaboratory project ( k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result ( d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Ex…
A Bayesian network model for evacuation time analysis during a ship fire
2013
We present an evacuation model for ships while a fire happens onboard. The model is designed by utilizing Bayesian networks (BN) and then simulated in GeNIe software. In our proposed model, the most important factors that have significant influence on a rescue process and evacuation time are identified and analyzed. By applying the probability distribution of the considered factors collected from the literature including IMO, real empirical data and practical experiences, the trend of the rescue process and evacuation time can be evaluated and predicted using the proposed model. The results of this paper help understanding about possible consequences of influential factors on the security o…
Adaptive Sequential Interpolator Using Active Learning for Efficient Emulation of Complex Systems
2020
Many fields of science and engineering require the use of complex and computationally expensive models to understand the involved processes in the system of interest. Nevertheless, due to the high cost involved, the required study becomes a cumbersome process. This paper introduces an interpolation procedure which belongs to the family of active learning algorithms, in order to construct cheap surrogate models of such costly complex systems. The proposed technique is sequential and adaptive, and is based on the optimization of a suitable acquisition function. We illustrate its efficiency in a toy example and for the construction of an emulator of an atmosphere modeling system.
Intrusion Detection and Ejection Framework Against Lethal Attacks in UAV-Aided Networks: A Bayesian Game-Theoretic Methodology
2017
International audience; Advances in wireless communications and microelectronics have spearheaded the development of unmanned aerial vehicles (UAVs), which can be used to augment a ground network composed of sensors and/or vehicles in order to increase coverage, enhance the end-to-end delay, and improve data processing. While UAV-aided networks can potentially find applications in many areas, a number of issues, particularly security, have not been readily addressed. The intrusion detection system is the most commonly used technique to detect attackers. In this paper, we focus on addressing two main issues within the context of intrusion detection and attacker ejection in UAV-aided networks…