Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Geophysical Research"
DOI: 10.1002/2017jd026648
Abstract: Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed a general framework for blending multiple satellite precipitation data using the dynamic… read more here.
Keywords: plateau; precipitation; multisatellite precipitation; model averaging ... See more keywords
Model averaging for robust assessment of QT prolongation by concentration-response analysis.
Sign Up to like & getrecommendations! Published in 2017 at "Statistics in medicine"
DOI: 10.1002/sim.7395
Abstract: Assessing the QT prolongation potential of a drug is typically done based on pivotal safety studies called thorough QT studies. Model-based estimation of the drug-induced QT prolongation at the estimated mean maximum drug concentration could… read more here.
Keywords: concentration response; model averaging; method; model ... See more keywords
Collaborative deep learning across multiple data centers
Sign Up to like & getrecommendations! Published in 2020 at "Science China Information Sciences"
DOI: 10.1007/s11432-019-2705-2
Abstract: Valuable training data is often owned by independent organizations and located in multiple data centers. Most deep learning approaches require to centralize the multi-datacenter data for performance purpose. In practice, however, it is often infeasible… read more here.
Keywords: collaborative deep; multiple data; model averaging; deep learning ... See more keywords
One size does not fit all… panel data: Bayesian model averaging and data poolability
Sign Up to like & getrecommendations! Published in 2018 at "Economic Modelling"
DOI: 10.1016/j.econmod.2018.07.009
Abstract: Abstract We show in this paper why researchers ought to pay particular attention to the issues of model uncertainty and data poolability in their panel data applications. We focus on the identification of robust determinants… read more here.
Keywords: panel data; bayesian model; model averaging; model ... See more keywords
A multiple crop model ensemble for improving broad-scale yield prediction using Bayesian model averaging
Sign Up to like & getrecommendations! Published in 2017 at "Field Crops Research"
DOI: 10.1016/j.fcr.2017.06.011
Abstract: Abstract Process-based crop models are popular tools to evaluate the impact of climate change and agricultural management on crop growth. Accurate simulation of crop production over large geographic regions using an individual crop model remains… read more here.
Keywords: bayesian model; crop model; model averaging; model ... See more keywords
Optimal model averaging forecasting in high-dimensional survival analysis
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Forecasting"
DOI: 10.1016/j.ijforecast.2020.12.004
Abstract: Abstract This article considers ultrahigh-dimensional forecasting problems with survival response variables. We propose a two-step model averaging procedure for improving the forecasting accuracy of the true conditional mean of a survival response variable. The first… read more here.
Keywords: survival response; model; optimal model; model averaging ... See more keywords
Semiparametric model averaging prediction for dichotomous response
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Econometrics"
DOI: 10.1016/j.jeconom.2020.09.008
Abstract: Abstract Model averaging has attracted abundant attentions in the past decades as it emerges as an impressive forecasting device in econometrics, social sciences and medicine. So far most developed model averaging methods focus only on… read more here.
Keywords: dichotomous response; model averaging; semiparametric model; model ... See more keywords
Optimal model averaging estimator for expectile regressions
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Statistical Planning and Inference"
DOI: 10.1016/j.jspi.2021.08.003
Abstract: Abstract In this paper, we consider model averaging for expectile regressions, which are common in many fields. The J -fold cross-validation criterion is developed to determine averaging weights. Under some regularity conditions, we prove that… read more here.
Keywords: averaging estimator; expectile regressions; model averaging; model ... See more keywords
Bayesian model averaging for Kriging regression structure selection
Sign Up to like & getrecommendations! Published in 2019 at "Probabilistic Engineering Mechanics"
DOI: 10.1016/j.probengmech.2019.02.002
Abstract: Abstract Kriging metamodels are widely used to approximate the response of computationally-intensive engineering models for a variety of applications, ranging from system design to uncertainty quantification. Their predictions are formulated by combining a regression that… read more here.
Keywords: regression; basis functions; averaging kriging; model ... See more keywords
Bayesian Model Averaging With Fixed and Flexible Priors: Theory, Concepts, and Calibration Experiments for Rainfall‐Runoff Modeling
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Advances in Modeling Earth Systems"
DOI: 10.1029/2019ms001924
Abstract: This paper introduces for the first time the concept of Bayesian model averaging (BMA) with multiple prior structures, for rainfall‐runoff modeling applications. The original BMA model proposed by Raftery et al. (2005, https://doi.org.10.1175/MWR2906.1) assumes that… read more here.
Keywords: rainfall runoff; model; bayesian model; fixed flexible ... See more keywords
Parsimonious Model Averaging With a Diverging Number of Parameters
Sign Up to like & getrecommendations! Published in 2020 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2019.1604363
Abstract: Abstract Model averaging generally provides better predictions than model selection, but the existing model averaging methods cannot lead to parsimonious models. Parsimony is an especially important property when the number of parameters is large. To… read more here.
Keywords: parsimonious model; model averaging; averaging diverging; model ... See more keywords