Results 51 to 60 of about 44,986 (305)
Industry Portfolio Volatility Connections and Industry Portfolio Returns
International Journal of Finance &Economics, EarlyView.ABSTRACT This paper tracks dynamic connections that form among daily US industry portfolio return volatilities using a Bayesian time‐varying parameter VAR model. Market participants often focus on sectors to filter vast amounts of information, and this focus results in cross‐industry return predictability. We characterise connections that form over the
Michael Ellington +2 more
wiley +1 more source
Computing the Cramer-Rao bound of Markov random field parameters: Application to the Ising and the Potts models [PDF]
, 2013 This letter considers the problem of computing the Cramer–Rao bound for the parameters of a Markov random field. Computation of the exact bound is not feasible for most fields of interest because their likelihoods are intractable and have intractable ...
Batatia, Hadj +8 more
core +1 more source
International Journal of Gynecology &Obstetrics, EarlyView.Abstract Objective This study identifies factors associated with not proceeding to clitoral reconstructive surgery among women with female genital mutilation (FGM) enrolled in a specialized surgical pathway. Methods A retrospective cohort study was conducted at a multidisciplinary referral center in Montreuil, France, between January 2021 and December ...
Félicia Joinau‐Zoulovits +3 more
wiley +1 more source
Applying diffusion-based Markov chain Monte Carlo. [PDF]
PLoS ONE, 2017 We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC.
Radu Herbei, Rajib Paul, L Mark Berliner
doaj +1 more source
Parallel hierarchical sampling : a general-purpose class of multiple-chains MCMC algorithms [PDF]
, 2009 This paper introduces the Parallel Hierarchical Sampler (PHS), a class of Markov chain Monte Carlo algorithms using several interacting chains having the same target distribution but different mixing properties. Unlike any single-chain MCMC algorithm,
Mira, Antonietta +3 more
core
Alternatives to the MCMC method [PDF]
, 2003 The Markov Chain Monte Carlo method (MCMC) is often used to generate independent (pseudo) random numbers from a distribution with a density that is known only up to a normalising constant.
Knüsel, L., Knüsel, Leo
core +1 more source
Rare vasculitis types and obstetric and neonatal outcomes – A population‐based study
International Journal of Gynecology &Obstetrics, EarlyView.Abstract Objective Vasculitis is an infrequent pathology among reproductive‐aged women. While data exists regarding pregnancy outcomes in the more common vasculitis subtypes, data is limited regarding these outcomes in rare vasculitis subtypes. We aimed to compare pregnancy and perinatal outcomes between women who suffered from rare types of vasculitis
Uri Amikam +4 more
wiley +1 more source
Revista Colombiana de Estadística, 2011 In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different "frailties" or latent variables are considered to capture the correlation among the survival times ...
JORGE ALBERTO ACHCAR +1 more
doaj
Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo
Journal of Synchrotron Radiation, 2022 Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis.
Zhang Jiang +4 more
doaj +1 more source
Journal of Adolescence, EarlyView.ABSTRACT Introduction There is a growing interest in positive risk‐taking (PRT) during adolescence and young adulthood. Emerging evidence has documented positive associations of PRT with multiple positive adolescent socioemotional developmental outcomes, including prosocial behavior.
Weiyu Edith Chen, Hao Zheng, Yao Zheng
wiley +1 more source