Results 101 to 110 of about 44,356 (305)
An objective Bayesian method for including parameter uncertainty in ensemble model output statistics
Quarterly Journal of the Royal Meteorological Society, EarlyView.Conventional model output statistics and ensemble model output statistics methods for calibrating ensemble forecasts lead to severe underestimation of the probabilities of ensemble extremes (in blue). This is because they ignore statistical parameter uncertainty.
Stephen Jewson +4 more
wiley +1 more source
A Discrete Density Approach to Bayesian Quantile and Expectile Regression with Discrete Responses [PDF]
, 2021 Xi Liu, Xueping Hu, Keming Yu
openalex +1 more source
Bayesian Spatial Quantile Regression
, 2013 In this paper we present a Bayesian spatial model quantile regression. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. W
Grażyna Trzpiot
openalex +3 more sources
, 2012 Predictions of the uncertainty associated with extreme events are a vital component of any prediction system for such events. Consequently, the prediction system ought to be probabilistic in nature, with the predictions taking the form of probability ...
Friederichs, Petra +1 more
core +1 more source
Quarterly Journal of the Royal Meteorological Society, EarlyView.The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley +1 more source
Corrigendum: Modified quantile regression for modeling the low birth weight
Frontiers in Applied Mathematics and Statistics, 2023 Ferra Yanuar +2 more
doaj +1 more source
Non-linear regression models for Approximate Bayesian Computation
, 2009 Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable.
A. Butler +43 more
core +1 more source
Optimal Accelerated Life Testing Design Under Constrained Resources Using Double Deep Q‐Learning
Quality and Reliability Engineering International, EarlyView.ABSTRACT Accelerated life tests (ALTs) are essential tools for estimating product reliability under high‐stress conditions, allowing failure data to be collected in reduced timeframes. However, planning effective ALT configurations is a complex task that requires selecting stress levels, test durations, and unit allocations while accounting for limited
Allan Jonathan da Silva +3 more
wiley +1 more source
Hydrological Model Diversity Enhances Streamflow Forecast Skill at Short‐ to Medium‐Range Timescales
Water Resources Research, 2019 We investigate the ability of hydrological multimodel ensemble predictions to enhance the skill of streamflow forecasts at short‐ to medium‐range timescales.
Sanjib Sharma +4 more
doaj +1 more source