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Article
A new bandwidth selection method for nonparametric modal regression based on generalized hyperbolic distributions
As a complement to standard mean and quantile regression, nonparametric modal regression has been broadly applied in various fields. By focusing on the most likely conditional value of Y given x, the nonparame...
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Article
Machine learning embedded EM algorithms for semiparametric mixture regression models
In this article, we propose two machine learning embedded algorithms for a class of semiparametric mixture models, where the mixing proportions and mean functions are unknown but smooth functions of covariates...
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Article
Statistical inference for the nonparametric and semiparametric hidden Markov model via the composite likelihood approach
In this paper, we propose a new estimation method for a nonparametric hidden Markov model (HMM), in which both the emission model and the transition matrix are nonparametric, and a semiparametric HMM, in which...
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Article
Regularized Factor Portfolio for Cross-sectional Multifactor Models
Factor portfolio is an important concept in the field of active portfolio management. However, the traditional factor portfolio lacks of theoretical results and is not investable since it is over-diversified. ...
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Article
Special issue on “Models and learning for clustering and Classification”
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Article
Editorial for ADAC issue 1 of volume 16 (2022)
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Chapter
Modal Regression for Skewed, Truncated, or Contaminated Data with Outliers
Built on the ideas of mean and quantile, mean regression and quantile regression are extensively investigated and popularly used to model the relationship between a dependent variable Y and covariates x. However...
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Article
Semiparametric mixture regression with unspecified error distributions
In fitting a mixture of linear regression models, normal assumption is traditionally used to model the error and then regression parameters are estimated by the maximum likelihood estimators (MLE). This proced...
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Article
Modal regression for fixed effects panel data
Most research on panel data focuses on mean or quantile regression, while there is not much research about regression methods based on the mode. In this paper, we propose a new model named fixed effects modal reg...
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Article
Open AccessBayesian Hyper-LASSO Classification for Feature Selection with Application to Endometrial Cancer RNA-seq Data
Feature selection is demanded in many modern scientific research problems that use high-dimensional data. A typical example is to identify gene signatures that are related to a certain disease from high-dimens...
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Article
Semiparametric mixtures of regressions with single-index for model based clustering
In this article, we propose two classes of semiparametric mixture regression models with single-index for model based clustering. Unlike many semiparametric/nonparametric mixture regression models that can onl...
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Article
Base-Calling Using a Random Effects Mixture Model on Next-Generation Sequencing Data
The emergence of next-generation sequencing technology has greatly influenced research in biology and clinical applications. This new technology allows millions of DNA fragments to be sequenced in parallel, re...
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Article
Semiparametric mixtures of nonparametric regressions
In this article, we propose and study a new class of semiparametric mixture of regression models, where the mixing proportions and variances are constants, but the component regression functions are smooth fun...
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Chapter
A Selective Overview of Semiparametric Mixture of Regression Models
Finite mixture of regression models have been popularly used in many applications. In this article, we did a systematic review of newly developed semiparametric mixture of regression models. Recent development...
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Article
Robust estimation of the number of components for mixtures of linear regression models
In this paper, we investigate a robust estimation of the number of components in the mixture of regression models using trimmed information criteria. Compared to the traditional information criteria, the trimm...
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Article
Model based labeling for mixture models
Label switching is one of the fundamental problems for Bayesian mixture model analysis. Due to the permutation invariance of the mixture posterior, we can consider that the posterior of a m-component mixture mode...
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Chapter and Conference Paper
Study on the Control of Line Balancing for Infant’s Costume Production
This paper introduces the basic theory of sewing process layout of infant costume production line. It discusses process optimization and the load balancing process design in the production. For knitted T-shirt...
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Chapter and Conference Paper
A Study on the Difference of IT Skill between Retrained Professionals and Recent Graduates
In order to go back to the active workforce, many unemployed IT professionals choose to upgrade their skills by accepting retraining. Being older and often far from their college education, these workers often...
