Results 91 to 100 of about 44,356 (305)
On Order Restricted Inference in Multi‐Step Stage Life Testing for a General Family of Distributions
Naval Research Logistics (NRL), EarlyView.ABSTRACT Recently, k$$ k $$‐step stage life testing (SLT) has been proposed by Laumen and Cramer (2021) as a natural extension of progressive censoring with fixed censoring times (PC‐FCT) as well as of simple step‐stress accelerated life testing (SSALT).
Erhard Cramer +2 more
wiley +1 more source
Variational Bayesian Quantile Regression with Non-Ignorable Missing Response Data
AxiomsFor non-ignorable missing response variables, the mechanism of whether the response variable is missing can be modeled through logistic regression. In Bayesian computation, the lack of a conjugate prior for the logistic function poses a significant ...
Juanjuan Zhang +2 more
doaj +1 more source
Retirement Consumption Puzzle in Malaysia: Evidence from Bayesian Quantile Regression Model
Journal of Probability and Statistics, 2019 The objective of this study is to use the Bayesian quantile regression for studying the retirement consumption puzzle, which is defined as the drop in consumption upon retirement, using the cross-sectional data of the Malaysian Household Expenditure ...
Ros Idayuwati Alaudin +2 more
doaj +1 more source
Ensemble Kalman filter in latent space using a variational autoencoder pair
Quarterly Journal of the Royal Meteorological Society, EarlyView.The use of the ensemble Kalman filter (EnKF) in strongly nonlinear or constrained atmospheric, oceanographic, or sea‐ice models can be challenging. Applying the EnKF in the latent space of a variational autoencoder (VAE) ensures that the ensemble members satisfy the balances and constraints present in the model.
Ivo Pasmans +4 more
wiley +1 more source
Bayesian Quantile Regression for Partial Functional Linear Spatial Autoregressive Model
AxiomsWhen performing Bayesian modeling on functional data, the assumption of normality is often made on the model error and thus the results may be sensitive to outliers and/or heavy tailed data.
Dengke Xu +3 more
doaj +1 more source
An Extension of Generalized Linear Models to Finite Mixture Outcome Distributions
, 2016 Finite mixture distributions arise in sampling a heterogeneous population. Data drawn from such a population will exhibit extra variability relative to any single subpopulation.
Morel, Jorge G. +2 more
core +1 more source
Data assimilation with extremum Monte Carlo methods
Quarterly Journal of the Royal Meteorological Society, EarlyView.This study presents the extremum Monte Carlo filter as a data assimilation method and, in particular, a variant of the variational approach (three‐ and four‐dimensional variational), where the state estimates are obtained by solving an optimization problem numerically over a space of prediction functions, instead of the state space itself.
Karim Moussa, Siem Jan Koopman
wiley +1 more source
Regional Science Policy &Practice, EarlyView., 2021 Abstract Knowledge and innovation have become a significant source of modern regional development. The paper aims to study the spatial association of innovation and model innovation, besides critiquing regional innovation policy, using the regional knowledge production function approach.
Mohamed Abouelhassan Ali
wiley +1 more source
Bayesian composite $$L^p$$-quantile regression
MetrikaAbstract $$L^p$$ L p -quantiles are a class of generalized quantiles defined as minimizers of an asymmetric power function. They include both quantiles,
openaire +2 more sources
Optimal designs for quantile regression models [PDF]
, 2011 Despite of their importance optimal designs for quantile regression models have not been developed so far. In this paper we investigate the D-optimal design problem for the location scale nonlinear quantile regression model.
Dette, Holger, Trampisch, Matthias
core