Results 171 to 180 of about 527,420 (298)

The comparison of the scores obtained by Bayesian nonparametric model and classical test theory methods. [PDF]

Sci Prog, 2021
Yurtcu M, Kelecioglu H, Boone EL.
europepmc   +1 more source

BAYESIAN CURVE ESTIMATION BY MODEL AVERAGING [PDF]

A bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the ...
M. Dolores Redondas, Daniel Peña
core  

Integrating Indigenous knowledge and modern statistical approaches to model wildlife density based on animal track counts

Conservation Biology, EarlyView.
Abstract In multiuse areas outside formal protection, sustaining both wildlife and people is critical to wildlife conservation and coexistence efforts. Botswana's Kalahari hosts one of sub‐Saharan Africa’s largest unprotected areas supporting free‐ranging wildlife.
Marie‐Charlotte Gielen, Xiko Johannes, Njoxlau Kashe, Glam Khumo, Horekwe (Karoha) Langwane, Zoro Zoronxhogo, Viktoriia Radchuk, Nicolas Schtickzelle   +7 more
wiley   +1 more source

Contributions to the understanding of Bayesian consistency. [PDF]

Consistency of Bayesian nonparametric procedures has been the focus of a considerable amount of research. Here we deal with strong consistency for Bayesian density estimation. An awkward consequence of inconsistency is pointed out. We investigate reasons
Antonio Lijoi, Stephen G. Walker, Igor Prünster   +2 more
core  

Development of a machine learning (ML) model to predict 3‐month response to CGRP monoclonal antibodies in migraine: A pilot evaluation of physician‐ML model interaction

Headache: The Journal of Head and Face Pain, EarlyView.
Plain Language Summary Monoclonal antibodies that target calcitonin gene‐related peptide (CGRP‐mAbs) are effective treatments for preventing migraine in many patients but are expensive, and physicians cannot easily predict which patients will benefit from them.
Masahito Katsuki, Muneto Tatsumoto, Tomokazu Shimazu, Yasuhiko Matsumori, Marina Romozzi, Omid Kohandel Gargari, Alicia Gonzalez‐Martinez, Woo‐Seok Ha, Yutaro Fuse, Shiho Suzuki, Saro Kobayashi, Tomohiko Shiina, Mukuto Shioda, Hiroaki Fujita, Koichi Hirata, Yuya Kano, Ryosuke Fukazawa, Jackson T. S. Cheung, Siobhán O'Connor, Tomás Ward, Kieran Moran, Keisuke Suzuki   +21 more
wiley   +1 more source

Methodology for using a Bayesian nonparametric model to uncover universal patterns in color naming. [PDF]

MethodsX, 2021
Joe K, Gooyabadi M.
europepmc   +1 more source

The Distributional Effects of Economic Uncertainty*

International Economic Review, EarlyView.
ABSTRACT We study the distributional implications of uncertainty shocks by developing a model that links macroeconomic aggregates to the US distribution of earnings and consumption. Our findings suggest that the fraction of low‐earning workers decreases initially, while the share of households reporting low consumption increases.
Florian Huber, Massimiliano Marcellino, Tommaso Tornese   +2 more
wiley   +1 more source

Bayesian nonparametric multiway regression for clustered binomial data. [PDF]

Stat (Int Stat Inst), 2021
Lock EF, Bandyopadhyay D.
europepmc   +1 more source

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

International Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula Moraga   +2 more
wiley   +1 more source

A Bayesian nonparametric approach to dynamic item-response modeling: An application to the GUSTO cohort study. [PDF]

Stat Med, 2021
Cremaschi A, De Iorio M, Seng Chong Y, Broekman B, Meaney MJ, Kee MZL.   +5 more
europepmc   +1 more source