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Mathematics

D-Index
39
Citations
6133
World Ranking
2213
National Ranking
933

Overview

Jianguo Sun is affiliated with the University of Missouri in the United States. Their research primarily focuses on mathematical and statistical methods, with a particular emphasis on statistics and probability. Their work extends into subfields such as economics and econometrics, artificial intelligence, genetics, and pulmonary and respiratory medicine.

The main areas of investigation in Jianguo Sun's scholarly contributions include:

  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Statistical Distribution Estimation and Applications
  • Advanced Causal Inference Techniques
  • Bayesian Methods and Mixture Models
  • Advanced Statistical Methods and Models
  • Spatial and Panel Data Analysis

Jianguo Sun has published extensively in various academic journals. Key publication venues where their research appears with notable frequency include:

  • Statistics in Medicine
  • Computational Statistics & Data Analysis
  • Communication in Statistics- Theory and Methods
  • Lifetime Data Analysis
  • Journal of Applied Statistics

Among the recent papers attributed to Jianguo Sun are the following:

  • Variable selection for high-dimensional partly linear additive Cox model with application to Alzheimer's disease, 2020, Statistics in Medicine
  • A pairwise pseudo-likelihood approach for left-truncated and interval-censored data under the Cox model, 2020, Biometrics
  • Regression analysis of case-cohort studies in the presence of dependent interval censoring, 2020, Journal of Applied Statistics
  • Simultaneous variable selection and estimation for joint models of longitudinal and failure time data with interval censoring, 2020, Biometrics
  • A unified approach to variable selection for Cox's proportional hazards model with interval-censored failure time data, 2021, Statistical Methods in Medical Research

Jianguo Sun collaborates frequently with several researchers. Common coauthors include:

  • Shishun Zhao
  • Mingyue Du
  • Yichen Lou
  • Tao Hu
  • Liang Zhu

In addition to journal articles, Jianguo Sun has contributed to academic literature through book publications. Notably, a title published by Springer Nature is:

  • Emerging Topics in Modeling Interval-Censored Survival Data, 2022

Jianguo Sun's body of work revolves around the development and application of advanced statistical models, particularly in survival analysis and interval censoring. Their research integrates methodologies relevant to medical research and various applied statistical domains.

Best Publications

  • The Statistical Analysis of Interval-censored Failure Time Data

    Jianguo Sun

  • A non-parametric test for interval-censored failure time data with application to AIDS studies.

    Jianguo Sun

  • Introducing Ti3+ defects based on lattice distortion for enhanced visible light photoreactivity in TiO2 microspheres

    Yunfan Xu;Yunfan Xu;Sujuan Wu;Piaopiao Wan;Jianguo Sun

  • Interval-Censored Time-to-Event Data : Methods and Applications

    Ding-Geng (Din) Chen;Jianguo Sun;Karl E. Peace

  • A correlation principal component regression analysis of NIR data

    Jianguo Sun

  • Statistical Analysis of Panel Count Data

    Jianguo Sun;Xingqiu Zhao

  • Semiparametric regression analysis of longitudinal data with informative observation times

    Jianguo Sun;Do Hwan Park;Liuquan Sun;Xingqiu Zhao

  • A Sieve Semiparametric Maximum Likelihood Approach for Regression Analysis of Bivariate Interval-Censored Failure Time Data

    Qingning Zhou;Tao Hu;Jianguo Sun

  • The Analysis of Current Status Data on Point Processes

    Jianguo Sun;John D. Kalbfleisch

  • Maximum Likelihood Estimation in a Semiparametric Logistic/Proportional‐Hazards Mixture Model

    Hong-Bin Fang;Gang Li;Jianguo Sun

  • Failure Mechanism and Interface Engineering for NASICON-Structured All-Solid-State Lithium Metal Batteries.

    Linchun He;Qiaomei Sun;Chao Chen;Jin An Sam Oh;Jin An Sam Oh

  • Regression Analysis of Longitudinal Data in the Presence of Informative Observation and Censoring Times

    Jianguo Sun;Liuquan Sun;Dandan Liu

  • Generalized log‐rank test for mixed interval‐censored failure time data

    Qiang Zhao;Jianguo Sun

  • Regression analysis of interval-censored failure time data with linear transformation models

    Zhigang Zhang;Liuquan Sun;Xingqiu Zhao;Jianguo Sun

  • A 2D multistage median filter to reduce random seismic noise

    Cai Liu;Yang Liu;Baojun Yang;Dian Wang

  • Sieve maximum likelihood regression analysis of dependent current status data

    Ling Ma;Tao Hu;Jianguo Sun

  • Statistical analysis of current status data with informative observation times.

    Zhigang Zhang;Jianguo Sun;Liuquan Sun

  • Generalized Log-Rank Tests for Interval-Censored Failure Time Data

    Jianguo Sun;Qiang Zhao;Xingqiu Zhao

  • Regression Parameter Estimation from Panel Counts

    X. Joan Hu;Jianguo Sun;Lee-Jen Wei

  • Empirical estimation of a distribution function with truncated and doubly interval-censored data and its application to AIDS studies.

    Jianguo Sun

  • Regression analysis of panel count data with dependent observation times.

    Jianguo Sun;Xingwei Tong;Xin He

  • Statistical analysis of NIR data : Data pretreatment

    Jianguo Sun

Frequent Co-Authors

Leslie L. Robison
Leslie L. Robison St. Jude Children's Research Hospital
Wendy Leisenring
Wendy Leisenring Fred Hutchinson Cancer Research Center
John D. Kalbfleisch
John D. Kalbfleisch University of Michigan–Ann Arbor
Narayanaswamy Balakrishnan
Narayanaswamy Balakrishnan McMaster University
Stanley Pounds
Stanley Pounds St. Jude Children's Research Hospital
Melissa M. Hudson
Melissa M. Hudson St. Jude Children's Research Hospital
Peter B. Gilbert
Peter B. Gilbert Fred Hutchinson Cancer Research Center
Gary Stacey
Gary Stacey University of Missouri
Dong Xu
Dong Xu University of Missouri
Henry T. Nguyen
Henry T. Nguyen University of Missouri

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