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Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring
We consider a novel class of semiparametric joint models for multivariate longitudinal and survival data with dependent censoring. In these models,...
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The expectation–maximization approach for Bayesian additive Cox regression with current status data
In this paper, we propose a Bayesian additive Cox model for analyzing current status data based on the expectation–maximization variable selection...
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Polynomial spline estimation of panel count data model with an unknown link function
Panel count data are frequently encountered in follow-up studies such as clinical trials, reliability researches, and insurance studies. Models about...
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Fusion Learning of Functional Linear Regression with Application to Genotype-by-Environment Interaction Studies
We propose a sparse multi-group functional linear regression model to simultaneously estimate multiple coefficient functions and identify groups,...
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Penalized spline estimation for panel count data model with time-varying coefficients
We consider a panel count data model with both time-varying and time-invariant coefficients. We estimate the baseline function and the time-varying...
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Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods
In this work, we propose an efficient implementation of mixtures of experts distributional regression models which exploits robust estimation by...
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Bayesian P-Splines Applied to Semiparametric Models with Errors Following a Scale Mixture of Normals
This work is about semiparametric models assuming that the error follows a scale mixture of gaussian distributions and such that the functional...
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Tree-based boosting with functional data
In this article we propose a boosting algorithm for regression with functional explanatory variables and scalar responses. The algorithm uses...
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Robust variable selection for additive coefficient models
Additive coefficient models generalize linear regression models by assuming that the relationship between the response and some covariates is linear,...
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Feature selection algorithms in generalized additive models under concurvity
In this paper, the properties of 10 different feature selection algorithms for generalized additive models (GAMs) are compared on one simulated and...
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Penalized polygram regression
We consider a study on regression function estimation over a bounded domain of arbitrary shapes based on triangulation and penalization techniques. A...
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Bayesian Analysis of First-Order Markov Models for Autocorrelated Binary Responses
In many clinical trials, patient outcomes are often binary-valued which are measured asynchronously over time across various dose levels. To account...
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Variable Selection for Nonlinear Covariate Effects with Interval-Censored Failure Time Data
This paper discusses variable selection when one faces general, high-dimensional interval-censored failure time data, which commonly occur in many...
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Personalized Medicine with Advanced Analytics
Practice of modern medicine demands personalized medicine (PM) to improve both quality of care and efficiency of the healthcare system. This is...
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Extensions of the Classical Linear Model
This chapter discusses several extensions of the classical linear model. We first describe the general linear model and its applications in Sect. 4.1.
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Variable selection and structure identification for additive models with longitudinal data
This paper proposes a polynomial structure identification (PSI) method for variable selection and model structure identification of additive models...
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Regularization and Predictor Selection for Ordinal and Categorical Data
Categorical data are quite common in applied statistics, and various regularized fitting procedures have been proposed for appropriate handling of...
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VC: a method for estimating time-varying coefficients in linear models
This paper describes a moments estimator for a standard state-space model with coefficients generated by a random walk. The method calculates the...
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Shape Detection Using Semi-Parametric Shape-Restricted Mixed Effects Regression Spline with Applications
Linear models are widely used in the field of epidemiology to model the relationship between placental-fetal hormone and fetal/infant outcome. When a...
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Variable selection for multivariate functional data via conditional correlation learning
Variable selection involves selecting truly important predictors from p -dimensional multivariate functional predictors in functional predictive...
