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Bases for alternative nonparametric Mincer function
(Universidad de Cuenca, 2017)
Bayesian inference for longitudinal data with nonparametrics random effects
(2014)
We consider inference for longitudinal data based on mixed-effects models with a non-parametric Bayesian prior on the treatment effect.
The proposed non-parametric Bayesian prior is a random partition model with a regression ...
Bayesian inference for longitudinal data with non-parametric treatment effects
(2014)
We consider inference for longitudinal data based on mixed-effects models with a non-parametric Bayesian prior on the treatment effect.
The proposed non-parametric Bayesian prior is a random partition model with a regression ...
Semiparametric Bayesian inference for multilevel repeated measurement data
(WILEY, 2007)
We discuss inference for data with repeated measurements at multiple levels. The motivating example is data with blood counts from cancer patients undergoing multiple cycles of chemotherapy, with days nested within cycles. ...
Nonparametric bayesian inference in applications
(2018)
Nonparametric Bayesian (BNP) inference is concerned with inference for infinite dimensional parameters, including unknown distributions, families of distributions, random mean functions and more. Better computational ...
Random partition models with regression on covariates
(ELSEVIER SCIENCE BV, 2010)
Many recent applications of nonparametric Bayesian inference use random partition models, i.e. probability models for clustering a set of experimental units. We review the popular basic constructions. We then focus on an ...
Nonparametric Bayesian Modeling and Estimation of Spatial Correlation Functions for Global Data
(INT SOC BAYESIAN ANALYSIS, 2021)
We provide a nonparametric spectral approach to the modeling of correlation functions on spheres. The sequence of Schoenberg coefficients and their associated covariance functions are treated as random rather than assuming ...
Bayesian nonparametric approaches for roc curve inference
(Mitra, R.; Mueller, P., 2015)
The development of medical diagnostic tests is of great importance in clinical practice, public health, and medical research. The receiver operating characteristic (ROC) curve is a popular tool for evaluating the accuracy ...
Bayesian inference for longitudinal data with non-parametric treatment effects
(OXFORD UNIVERSITY PRESS, 2014)