• Publications
  • Influence
Highly Robust Estimation of the Autocovariance Function
In this paper, the problem of the robustness of the sample autocovariance function is addressed. We propose a new autocovariance estimator, based on a highly robust estimator of scale. Its robustnessExpand
  • 104
  • 20
  • Open Access
A Semiparametric Approach to Dimension Reduction
  • Y. Ma, L. Zhu
  • Medicine, Mathematics
  • Journal of the American Statistical Association
  • 31 January 2012
We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimension-reduction problem in a semiparametric estimation framework andExpand
  • 112
  • 13
  • Open Access
Flexible Class of Skew‐Symmetric Distributions
Abstract. We propose a flexible class of skew‐symmetric distributions for which the probability density function has the form of a product of a symmetric density and a skewing function. ByExpand
  • 137
  • 11
On the likelihood function of Gaussian max-stable processes
We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by R-super-d at p≤dp1 sites, d≥1. We demonstrate the gain in efficiency in the maximumExpand
  • 99
  • 8
  • Open Access
Multiple imputation in quantile regression.
We propose a multiple imputation estimator for parameter estimation in a quantile regression model when some covariates are missing at random. The estimation procedure fully utilizes the entireExpand
  • 55
  • 7
  • Open Access
EFFICIENT ESTIMATION IN SUFFICIENT DIMENSION REDUCTION.
  • Y. Ma, L. Zhu
  • Medicine, Mathematics
  • Annals of statistics
  • 2 April 2013
We develop an efficient estimation procedure for identifying and estimating the central subspace. Using a new way of parameterization, we convert the problem of identifying the central subspace toExpand
  • 43
  • 5
  • Open Access
Efficient semiparametric estimator for heteroscedastic partially linear models
We study the heteroscedastic partially linear model with an unspecified partial baseline component and a nonparametric variance function. An interesting finding is that the performance of a naiveExpand
  • 54
  • 5
  • Open Access
Locally Efficient Estimators for Semiparametric Models With Measurement Error
We derive constructive locally efficient estimators in semiparametric measurement error models. The setting is one in which the likelihood function depends on variables measured with and withoutExpand
  • 42
  • 4
  • Open Access
Cure Rate Model With Mismeasured Covariates Under Transformation
Cure rate models explicitly account for the survival fraction in failure time data. When the covariates are measured with errors, naively treating mismeasured covariates as error-free would causeExpand
  • 23
  • 4
  • Open Access
Non-parametric statistics and robust methods
  • Y. Ma
  • Computer Science
  • 2008
Objectives Master classical and modern nonparametric modeling, estimation and inference methods.
  • 33
  • 4
  • Open Access