Results 31 to 40 of about 1,818,807 (197)

Estimation of the scale parameter of gamma model in presence of outlier observations

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 1990
This paper considers the Bayesian point estimation of the scale parameter for a two-parameter gamma life-testing model in presence of several outlier observations in the data.
M. E. Ghitany
doaj   +1 more source

Statin use and risk of remote seizure after first new onset status epilepticus

open access: yesEpilepsia, EarlyView.
Abstract Objective Preclinical evidence supports the role of statins as antiepileptogenic agents. In this study, we investigated the risk of remote unprovoked seizures (RS) according to the use of statin therapy in a cohort of first‐ever status epilepticus (SE) survivors. Methods Retrospective analysis was made of adult patients (age ≥ 14 years) with a
Niccolò Orlandi   +12 more
wiley   +1 more source

Rationale and Design of the Randomized Bayesian Multicenter COME-TAVI Trial in Patients With a New Onset Left Bundle Branch Block

open access: yesCJC Open, 2023
Patients with new-onset left bundle branch block (LBBB) after transcatheter aortic valve implantation (TAVI) are at risk of developing delayed high-degree atrioventricular block. Management of new-onset LBBB post-TAVI remains controversial.
Lena Rivard, MD, MSc   +36 more
doaj   +1 more source

Noninformative Priors for Multivariate Linear Calibration

open access: yesJournal of Multivariate Analysis, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Bayesian Multivariate Two‐Stage Volatility‐Return Models (MTS‐VR)

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper develops a class of models to capture the joint dynamics of asset returns and multivariate volatility. Owing to its two‐stage construction, this class is referred to as the multivariate two‐stage volatility‐return (MTS‐VR) model.
Zhenglyu Huang   +2 more
wiley   +1 more source

A Comparison of Methods for Synthesizing Results from Previous Research to Obtain Priors for Bayesian Structural Equation Modeling

open access: yesPsych
Bayesian estimation of latent variable models provides some unique advantages to researchers working with small samples and complex models when compared with the more commonly used maximum likelihood approach.
Holmes Finch
doaj   +1 more source

The spatial association between peritraumatic and chronic pain and its relation to posttraumatic stress disorder among trauma survivors

open access: yesJournal of Traumatic Stress, EarlyView.
Abstract Chronic pain frequently co‐occurs with posttraumatic stress disorder (PTSD). One theory proposes that some chronic pain may reflect pain reexperiencing (i.e., reactivation of somatosensory trauma memories). Although some research supports this theory, evidence from clinical survey studies is limited and methodologically constrained.
Sabrina E. Hettegger   +7 more
wiley   +1 more source

Estimation of Reliability in Multi-Component Stress-Strength Model Following Exponentiated Pareto Distribution [PDF]

open access: yesThe Egyptian Statistical Journal, 2012
This article deals with the Bayesian and non-Bayesian estimation of reliability of an s-out-of-k system with identical component strengths which are subjected to a common stress. Assuming that both stress and strength are assumed to have an exponentiated
Heba M.Basheikh, Amal S.Hassan
doaj   +1 more source

SAS_MoCa: software for small‐angle scattering data analysis of large unilamellar vesicles

open access: yesJournal of Applied Crystallography, EarlyView.
SAS_MoCa is an open‐source Python package for quantitative analysis of small‐angle scattering (SAS) data from large unilamellar vesicles, combining a compositional scattering density profile model of lipid bilayers with a separated form factor description of vesicle size and polydispersity in a Bayesian framework.
Enrico F. Semeraro, Georg Pabst
wiley   +1 more source

Graph‐Laplacian modeling of spatiotemporal effects for house price estimation

open access: yesReal Estate Economics, EarlyView.
Abstract Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input
Willem P Sijp, Marc K. Francke
wiley   +1 more source

Home - About - Disclaimer - Privacy