Results 131 to 140 of about 527,420 (298)

Nonparametric Bayesian Aggregation for Massive Data

J. Mach. Learn. Res., 2015
We develop a set of scalable Bayesian inference procedures for a general class of nonparametric regression models. Specifically, nonparametric Bayesian inferences are separately performed on each subset randomly split from a massive dataset, and then the obtained local results are aggregated into global counterparts.
Zuofeng Shang, Botao Hao, Guang Cheng 0003   +2 more
openaire   +4 more sources

A Bayesian nonparametric approach to modeling market share dynamics [PDF]

We propose a flexible stochastic framework for modeling the market share dynamics over time in a multiple markets setting, where firms interact within and between markets.
Igor Prünster, Matteo Ruggiero
core  

Nonparametric Regression for Cost‐Effectiveness Analyses With Observational Data—A Tutorial

Health Economics, EarlyView.
ABSTRACT Healthcare decision‐making often requires selecting among multiple treatment options under budget constraints, particularly when one option is more effective but also more costly. Cost‐effectiveness analysis (CEA) provides a framework for evaluating whether the health benefits of a treatment justify its additional costs.
Jonas Esser, Mateus Maia, Judith E. Bosmans, Johanna Maria van Dongen   +3 more
wiley   +1 more source

Sleep disturbance as a transdiagnostic marker of children's mental health difficulties: A network analysis of item‐level associations between different types of sleep problems and different behavioural and emotional symptoms

JCPP Advances, EarlyView.
Abstract Background Sleep disturbances are widely considered to be a transdiagnostic feature of common behavioural and emotional difficulties in childhood, yet most studies treat sleep as a single construct. Where studies have explored specific sleep problems to psychopathology in children, these tend to only include behavioural or emotional ...
Alina A. Marinca, Julia E. Michalek, Alice M. Gregory, Afia Ali, Jennifer Y. F. Lau   +4 more
wiley   +1 more source

DPpackage: Bayesian Semi- and Nonparametric Modeling in R

Journal of Statistical Software, 2011
Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model.
Alejandro Jara, Timothy Hanson, Fernando A. Quintana, Peter Müller, Gary L. Rosner   +4 more
doaj  

Discrete components of stress impact trajectories of childhood irritability but not adolescent mental health outcomes

JCPP Advances, EarlyView.
Thick red line indicates positive mixture effect of stressors predicting high irritability class. Maternal demoralization, material hardship, maternal perceived stress, and intimate partner violence contributed to the mixture effect (thick borders on boxes).
Mariah DeSerisy, Huiyu Yang, Jacob W. Cohen, David Pagliaccio, Julie B. Herbstman, Bradley S. Peterson, Frederica P. Perera, Virginia Rauh, Amy E. Margolis   +8 more
wiley   +1 more source

Nonparametric Learning Rules from Bandit Experiments: The Eyes have it! [PDF]

How do people learn? We assess, in a distribution-free manner, subjects?learning and choice rules in dynamic two-armed bandit (probabilistic reversal learning) experiments.
Yingyao Hu, Yutaka Kayaba, Matt Shum
core  

Navigating Parallel Careers: Profiles and Career Sustainability

Journal of Employment Counseling, EarlyView.
ABSTRACT This study explores protean and boundaryless career profiles among parallel career track (PCT) holders, who are professionals who voluntarily maintain more than one career role simultaneously, and examines their relationship with sustainable career outcomes.
Maria Candida Baumer de Azevedo, Ellen Peeters, Judith Semeijn, Tinka van Vuuren   +3 more
wiley   +1 more source

Local Search and the Evolution of World Models

Topics in Cognitive Science, EarlyView., 2023
Abstract An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily ...
Neil R. Bramley, Bonan Zhao, Tadeg Quillien, Christopher G. Lucas   +3 more
wiley   +1 more source

Models beyond the Dirichlet process [PDF]

Bayesian nonparametric inference is a relatively young area of research and it has recently undergone a strong development. Most of its success can be explained by the considerable degree of exibility it ensures in statistical modelling, if compared to ...
Antonio Lijoi, Igor Pruenster
core   +2 more sources