32 Result(s)
within
**-Lin Wang
Statistics
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Article
Bayesian multivariate nonlinear mixed models for censored longitudinal trajectories with non-monotone missing values
The analysis of multivariate longitudinal data may often encounter a difficult task, particularly in the presence of censored measurements induced by detection limits and intermittently missing values arising ...
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Article
Extending finite mixtures of nonlinear mixed-effects models with covariate-dependent mixing weights
Finite mixtures of nonlinear mixed-effects models have emerged as a prominent tool for modeling and clustering longitudinal data following nonlinear growth patterns with heterogeneous behavior. This paper prop...
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Article
The computing of the Poisson multinomial distribution and applications in ecological inference and machine learning
The Poisson multinomial distribution (PMD) describes the distribution of the sum of n independent but non-identically distributed random vectors, in which each random vector is of length m with 0/1 valued element...
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Article
Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data
Mixtures of factor analyzers (MFA) based on the restricted skew normal distribution (rMSN) have emerged as a flexible tool to handle asymmetrical high-dimensional data with heterogeneity. However, the rMSN dis...
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Article
A robust factor analysis model based on the canonical fundamental skew-t distribution
The traditional factor analysis rested on the assumption of multivariate normality has been extended by considering the restricted multivariate skew-t (rMST) distribution for the unobserved factors and errors joi...
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Article
Analytical Computation of Pseudo-Gibbs Distributions for Dependency Networks
Dependency network (DN) aims at using a collection of conditional distributions to identify a joint pdf. When the DN is compatible (self-consistent), the Gibbs sampler (GS) has been the algorithm to approximat...
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Article
Semiparametric single-index models for optimal treatment regimens with censored outcomes
There is a growing interest in precision medicine, where a potentially censored survival time is often the most important outcome of interest. To discover optimal treatment regimens for such an outcome, we pro...
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Article
Robust clustering via mixtures of t factor analyzers with incomplete data
Mixtures of t factor analyzers (MtFA) are powerful and widely used tools for robust clustering of high-dimensional data in the presence of outliers. However, the occurrence of missing values may cause analytical ...
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Article
Semiparametric inference on general functionals of two semicontinuous populations
In this paper, we propose new semiparametric procedures for inference on linear functionals in the context of two semicontinuous populations. The distribution of each semicontinuous population is characterized...
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Article
Robust clustering of multiply censored data via mixtures of t factor analyzers
Mixtures of t factor analyzers (MtFA) have been well recognized as a prominent tool in modeling and clustering multivariate data contaminated with heterogeneity and outliers. In certain practical situations, howe...
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Bayesian Inferences for Panel Count Data and Interval-Censored Data with Nonparametric Modeling of the Baseline Functions
Both panel count data and interval-censored data arise commonly in real-life studies when subjects are examined at periodic follow-ups. Interval-censored data are studied when the exact times of the events are...
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Article
Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables
Censored data arise frequently in diverse applications in which observations to be measured may be subject to some upper and lower detection limits due to the restriction of experimental apparatus such that th...
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Article
On moments of folded and truncated multivariate Student-t distributions based on recurrence relations
The use of the first two moments of the truncated multivariate Student-t distribution has attracted increasing attention from a wide range of applications. This paper develops recurrence relations for integral...
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Article
Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions
Finite mixtures of multivariate skew distributions have become increasingly popular in recent years due to their flexibility and robustness in modeling heterogeneity, asymmetry and leptokurticness of the data....
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Article
Automated learning of mixtures of factor analysis models with missing information
The mixture of factor analyzers (MFA) model has emerged as a useful tool to perform dimensionality reduction and model-based clustering for heterogeneous data. In seeking the most appropriate number of factors (q
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Article
A Bayesian approach for semiparametric regression analysis of panel count data
Panel count data commonly arise in epidemiological, social science, and medical studies, in which subjects have repeated measurements on the recurrent events of interest at different observation times. Since t...
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Chapter
Evaluating Risk Measures Using the Normal Mean-Variance Birnbaum-Saunders Distribution
Despite the widespread use and attractive properties of the normal and Student’s t distributions for modeling financial risks, it is widely believed that the normal-inverse Gaussian, skew-normal and skew-t distri...
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Article
Robust and efficient estimator for simultaneous model structure identification and variable selection in generalized partial linear varying coefficient models with longitudinal data
This paper proposes a new robust and efficient estimator for the generalized partial linear varying coefficient models with longitudinal data, which can construct variable selection and partial linear structur...
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Article
Limiting distributions of likelihood ratio test for independence of components for high-dimensional normal vectors
Consider a p-variate normal random vector. We are interested in the limiting distributions of likelihood ratio test (LRT) statistics for testing the independence of its grouped components based on a random sample...
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Article
Mixtures of restricted skew-t factor analyzers with common factor loadings
Mixtures of common t factor analyzers (MCtFA) have been shown its effectiveness in robustifying mixtures of common factor analyzers (MCFA) when handling model-based clustering of the high-dimensional data with he...
