What is he best known for?
The fields of study he is best known for:
- Statistics
- Normal distribution
- Regression analysis
Xuming He focuses on Statistics, Quantile, Linear model, Applied mathematics and Quantile regression.
In general Statistics, his work in Regression analysis, Nonparametric statistics, Nonparametric regression and Outlier is often linked to B-spline linking many areas of study.
His Quantile study frequently draws parallels with other fields, such as Estimator.
His work carried out in the field of Linear model brings together such families of science as Semiparametric model, M-estimator and Linear regression.
His Applied mathematics research includes themes of Posterior probability, Asymptotic distribution, Feature selection and Gibbs sampling.
His Quantile regression study is related to the wider topic of Econometrics.
His most cited work include:
- Quantile regression methods for reference growth charts. (232 citations)
- Quantile Curves without Crossing (213 citations)
- Estimation in a semiparametric model for longitudinal data with unspecified dependence structure (204 citations)
What are the main themes of his work throughout his whole career to date?
Xuming He mostly deals with Statistics, Estimator, Econometrics, Quantile regression and Quantile.
Xuming He combines topics linked to Applied mathematics with his work on Statistics.
His Estimator study incorporates themes from Poisson distribution, Robustness and Regression.
His Econometrics research focuses on Estimating equations and how it relates to Marginal model.
Xuming He has researched Quantile regression in several fields, including Nonparametric statistics, Bayesian probability, Markov chain Monte Carlo, Covariate and Conditional probability distribution.
Xuming He combines subjects such as Mathematical optimization, High dimensional and Heteroscedasticity with his study of Quantile.
He most often published in these fields:
- Statistics (53.72%)
- Estimator (34.71%)
- Econometrics (28.10%)
What were the highlights of his more recent work (between 2013-2021)?
- Quantile regression (27.27%)
- Econometrics (28.10%)
- Applied mathematics (23.97%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Quantile regression, Econometrics, Applied mathematics, Quantile and Statistics.
His Quantile regression study combines topics in areas such as Regression analysis, Estimator, Bayesian probability and Covariate.
His Regression analysis research is multidisciplinary, relying on both Mathematical statistics and Operations research.
His Estimator research incorporates themes from Smoothing, Inference and Regression.
His Applied mathematics research is multidisciplinary, incorporating perspectives in Statistical inference and Model selection.
His studies examine the connections between Statistical inference and genetics, as well as such issues in Outlier, with regards to Anomaly detection and Multivariate statistics.
Between 2013 and 2021, his most popular works were:
- Bayesian variable selection with shrinking and diffusing priors (114 citations)
- Handbook of quantile regression (55 citations)
- Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood (44 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Normal distribution
- Regression analysis
His scientific interests lie mostly in Quantile regression, Model selection, Econometrics, Bayesian probability and Covariate.
His Quantile regression study frequently draws connections to adjacent fields such as Estimator.
His Estimator research integrates issues from Range and Regression.
The various areas that Xuming He examines in his Model selection study include Prior probability, Feature selection, Applied mathematics and Gibbs sampling.
His work on Generalized linear model as part of general Applied mathematics study is frequently linked to Gaussian, bridging the gap between disciplines.
Xuming He specializes in Econometrics, namely Quantile.
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