World's Best Scientists 2026 revealed!

Overview

Xin-Yuan Song is affiliated with the Chinese University of Hong Kong in China. Their research work primarily focuses on the field of Mathematics, with a particular emphasis on Statistics and Probability. They have contributed substantially to the subfields of Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, and Management Science and Operations Research.

The scientist's work spans several key topics within statistics and inference, including Statistical Methods and Inference, Statistical Methods and Bayesian Inference, Bayesian Methods and Mixture Models, Advanced Causal Inference Techniques, Statistical Distribution Estimation and Applications, Advanced Statistical Methods and Models, and areas related to Health Systems, Economic Evaluations, and Quality of Life.

Xin-Yuan Song has published recent papers that reflect a range of research interests:

  • Wnt/β-catenin signalling, epithelial-mesenchymal transition and crosslink signalling in colorectal cancer cells, 2024, Biomedicine & Pharmacotherapy
  • Simultaneous variable selection in regression analysis of multivariate interval-censored data, 2021, Biometrics
  • A joint model for multivariate longitudinal and survival data to discover the conversion to Alzheimer's disease, 2021, Statistics in Medicine
  • Bayesian analysis of hidden Markov structural equation models with an unknown number of hidden states, 2020, Econometrics and Statistics
  • The complex relationship between gut microbiota and Alzheimer's disease: A systematic review, 2024, Ageing Research Reviews

Their frequent co-authors include Liuquan Sun, Silin Chen, Jinlang Wang, Ziqian Bi, and Chia Xin Liang.

Xin-Yuan Song's research has appeared in a variety of publication venues. Among the most frequent are:

  • arXiv (Cornell University)
  • Statistics in Medicine
  • Statistical Methods in Medical Research
  • SSRN Electronic Journal
  • Biometrics

Best Publications

  • Evaluation of the Bayesian and Maximum Likelihood Approaches in Analyzing Structural Equation Models with Small Sample Sizes.

    Sik-Yum Lee;Xin-Yuan Song

  • Local Polynomial Fitting in Semivarying Coefficient Model

    Wenyang Zhang;Sik-Yum Lee;Xinyuan Song

  • Basic and Advanced Bayesian Structural Equation Modeling: With Applications in the Medical and Behavioral Sciences

    Xin-Yuan Song;Sik-Yum Lee

  • Longitudinal Analysis of Quality of Life for Stroke Survivors Using Latent Curve Models

    Jun Hao Pan;Xin Yuan Song;Sik Yum Lee;Timothy Kwok

  • Bayesian analysis of structural equation models with dichotomous variables

    Sik-Yum Lee;Xin-Yuan Song

  • Comparison of Approaches in Estimating Interaction and Quadratic Effects of Latent Variables.

    Sik-Yum Lee;Xin Yuan Song;Wai-Yin Poon

  • Bayesian Methods for Analyzing Structural Equation Models With Covariates, Interaction, and Quadratic Latent Variables

    Sik-Yum Lee;Xin-Yuan Song;Nian-Sheng Tang

  • Bayesian estimation and test for factor analysis model with continuous and polytomous data in several populations.

    Xin-Yuan Song;Sik-Yum Lee

  • Model comparison of nonlinear structural equation models with fixed covariates

    Sik-Yum Lee;Xin-Yuan Song

  • ORACLE MODEL SELECTION FOR NONLINEAR MODELS BASED ON WEIGHTED COMPOSITE QUANTILE REGRESSION

    Xuejun Jiang;Jiancheng Jiang;Xinyuan Song

  • Bayesian analysis of two-level nonlinear structural equation models with continuous and polytomous data.

    Xin-Yuan Song;Xin-Yuan Song;Sik-Yum Lee

  • A tutorial on the Bayesian approach for analyzing structural equation models

    Xin-Yuan Song;Sik-Yum Lee

  • Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event

    Liuquan Sun;Xinyuan Song;Jie Zhou;Lei Liu

  • Maximum likelihood analysis of a general latent variable model with hierarchically mixed data

    Sik-Yum Lee;Xin-Yuan Song;Xin-Yuan Song

  • Analysis of structural equation model with ignorable missing continuous and polytomous data

    Xin-Yuan Song;Sik-Yum Lee

  • A UNIFIED VARIABLE SELECTION APPROACH FOR VARYING COEFFICIENT MODELS

    Yanlin Tang;Huixia Judy Wang;Zhongyi Zhu;Xinyuan Song

  • Financial literacy and household finances: A Bayesian two-part latent variable modeling approach

    Xiangnan Feng;Bin Lu;Xinyuan Song;Shuang Ma

  • Bayesian model selection for mixtures of structural equation models with an unknown number of components.

    Sik-Yum Lee;Xin-Yuan Song;Xin-Yuan Song

  • Semiparametric Bayesian analysis of structural equation models with fixed covariates

    Sik-Yum Lee;Bin Lu;Xin-Yuan Song

  • Oracle model selection for nonlinear models based on weighted composite quantile regression accelerated failure time model

    Xuejun Jiang;Jiancheng Jiang;Xinyuan Song

Frequent Co-Authors

Sik-Yum Lee
Sik-Yum Lee Chinese University of Hong Kong
Yih-Ing Hser
Yih-Ing Hser University of California, Los Angeles
Wing-Yee So
Wing-Yee So Chinese University of Hong Kong
Edward H. Ip
Edward H. Ip Wake Forest University
Juliana C.N. Chan
Juliana C.N. Chan Chinese University of Hong Kong
Claes Ohlsson
Claes Ohlsson University of Gothenburg
Suzanne M. Skevington
Suzanne M. Skevington University of Manchester
Ping-Chung Leung
Ping-Chung Leung Chinese University of Hong Kong
Yi Li
Yi Li University of Michigan–Ann Arbor
Ronald C.W. Ma
Ronald C.W. Ma Chinese University of Hong Kong

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