Buscar
Mostrando ítems 61-70 de 2033
Bayesian heavy-tailed models and conflict resolution: A review
(Brazilian Statistical Association, 2012)
Partially linear censored regression models using heavy-tailed distributions: A Bayesian approach
(ELSEVIER SCIENCE BV, 2014)
Linear regression models where the response variable is censored are often considered in statistical analysis. A parametric relationship between the response variable and covariates and normality of random errors are ...
Bayesian inference for longitudinal data with non-parametric treatment effects
(2014)
We consider inference for longitudinal data based on mixed-effects models with a non-parametric Bayesian prior on the treatment effect.
The proposed non-parametric Bayesian prior is a random partition model with a regression ...
Enhanced Sparse Bayesian Learning via Statistical Thresholding for Signals in Structured Noise
(Institute of Electrical and Electronics Engineers, 2013-11)
In this paper we address the problem of sparse signal reconstruction. We propose a new algorithm that determines the signal support applying statistical thresholding to accept the active components of the model. This ...
Statistical post-processing of ensemble forecasts of temperature in Santiago de Chile
(John Wiley and Sons Ltd, 2020)
Modelling forecast uncertainty is a difficult task in any forecasting problem. In weather forecasting a possible solution is the use of forecast ensembles, which are obtained from multiple runs of numerical weather prediction ...
Uncertainty in the estimation of the postmortem interval based on rectal temperature measurements: A Bayesian approach
(Elsevier Ireland, 2020-12)
In this work, the postmortem interval is estimated by means of Bayesian inference using rectal temperature data from a published database. First, a systematic analysis of the uncertainties in each of the model parameters ...
A Bayesian space varying parameter model applied to estimating fertility schedules
(John Wiley & Sons LtdW SussexInglaterra, 2002)
Bayesian estimation of regression parameters in elliptical measurement error models
(ELSEVIER SCIENCE BV, PO BOX 211, 2012)
Partial least squares enhances genomic prediction of new environments
(Frontiers, 2022)