Results 61 to 70 of about 3,106 (192)

Using Integrated Nested Laplace Approximations for Modelling Spatial Healthcare Utilization

, 2012
In recent years, spatial and spatio-temporal modeling have become an important area of research in many fields (epidemiology, environmental studies, disease mapping). In this work we propose different spatial models to study hospital recruitment, including some potentially explicative variables.
MUSIO, MONICA, Sauleau E. A, MAMELI, VALENTINA   +2 more
openaire   +4 more sources

Integrated nested Laplace approximations for threshold stochastic volatility models [PDF]

Econometrics and Statistics
Abstract The aim is to implement the integrated nested Laplace approximations (INLA), known to be very fast and efficient, for estimating the parameters of the threshold stochastic volatility (TSV) model. INLA replaces Markov chain Monte Carlo (MCMC) simulations with accurate deterministic approximations. Weakly informative proper priors are used, as
P. de Zea Bermudez, J. Miguel Marín, Håvard Rue, Helena Veiga   +3 more
openaire   +2 more sources

Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach

BMC Women's Health
Background Despite the significant weight of difficulty, Ethiopia's survival rate and mortality predictors have not yet been identified. Finding out what influences outpatient breast cancer patients' survival time was the major goal of this study ...
Chalachew Gashu, Aragaw Eshetie Aguade
doaj   +1 more source

Functional Brain Response to Emotional Muical Stimuli in Depression, Using INLA Approach for Approximate Bayesian Inference

Basic and Clinical Neuroscience, 2021
Introduction: One of the vital skills which has an impact on emotional health and well-being is the regulation of emotions. In recent years, the neural basis of this process has been considered widely.
Parisa Naseri, Hamid Alavi Majd, Seyyed Mohammad Tabatabaei, Naghmeh Khadembashi, Seyed Morteza Najibi, Atiye Nazari   +5 more
doaj  

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

International Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula Moraga   +2 more
wiley   +1 more source

Bayesian Mortality Modeling with Linearized Integrated Nested Laplace Approximations

, 2022
Prediksjon av dødelighet er et viktig verktøy innen for eksempel aktuarviten- skap og demografi. Mange populære dødelighetsmodeller inneholder multiplikative ledd som gjør at de ikke inkluderes i gruppen av modeller der man kan bruke den populære metoden INLA (Rue et al. 2009) for å gjøre bayesiansk inferens.
openaire   +2 more sources

Breakpoint detection on latent autoregressive time series of counts using integrated nested Laplace approximation. [PDF]

, 2020
Abrupt changes in a data source can weaken models that fail at addressing these. Structural change detection has traditionally been done with a frequentist approach, but recently approaches based on Bayesian models and Markov Chain Monte Carlo (MCMC ...
Ahmed, Amir
core   +2 more sources

Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation

International Statistical Review, EarlyView.
Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo, Domingo Morales, Nicola Salvati, Francesco Schirripa Spagnolo   +3 more
wiley   +1 more source

Traffic prediction at signalised intersections using Integrated Nested Laplace Approximation

, 2021
A Bayesian approach to predicting traffic flows at signalised intersections is considered using the the INLA framework. INLA is a deterministic, computationally efficient alternative to MCMC for estimating a posterior distribution. It is designed for latent Gaussian models where the parameters follow a joint Gaussian distribution.
Townsend, D., Nel, C.
openaire   +2 more sources

Robust CDF‐Filtering of a Location Parameter

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania, Andrew C. Harvey, Alessandra Luati   +2 more
wiley   +1 more source