Dimension reduction based on constrained canonical correlation and variable filtering (2008)
The ``curse of dimensionality'' has remained a challenge for high-dimensional data analysis in statistics. The sliced inverse regression (SIR) and canonical correlation (CANCOR) methods aim to reduce...
Robust estimates in generalized partially linear models (2007)
Boente, Graciela, He, Xuming, Zhou, Jianhui
In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by...
A depth-based rank sum statistic for multivariate data introduced by Liu and Singh [J. Amer. Statist. Assoc. 88 (1993) 252--260] as an extension of the Wilcoxon rank sum statistic for univariate data...
Discussion paper. Conditional growth charts (2007)
Growth charts are often more informative when they are customized per subject, taking into account prior measurements and possibly other covariates of the subject. We study a global semiparametric...
Rejoinder: Conditional Growth Charts (2007)
Rejoinder: Conditional Growth Charts [math.ST/0702634]
Conditional growth charts (2006)
Growth charts are often more informative when they are customized per subject, taking into account prior measurements and possibly other covariates of the subject. We study a global semiparametric...
Discussion of "Breakdown and groups" by P. L. Davies and U. Gather (2005)
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
A study of inter-lab and inter-platform agreement of DNA microarray data (2005)
Wang, Huixia, He, Xuming, Band, Mark, Wilson, Carole, Liu, Lei
Abstract As gene expression profile data from DNA microarrays accumulate rapidly, there is a natural need to compare data across labs and platforms. Comparisons of microarray data can be quite...
On the Stahel-Donoho estimator and depth-weighted means of multivariate data (2004)
Zuo, Yijun, Cui, Hengjian, He, Xuming
The depth of multivariate data can be used to construct weighted means as robust estimators of location. The use of projection depth leads to the Stahel-Donoho estimator as a special case. In...
We derive the asymptotic distribution ofthe maximal depth regression estimator recently proposed in Rousseeuw and Hubert. The estimator is obtained by maximizing a projection-based depth and the...
Some Asymptotic Results on Bivariate Quantile Splines (1999)
Nonparametric estimation of conditional quantiles is of fundamental importance in analyzing general regression problems, especially when heteroscedasticity is suspected. Koenker, Ng, and Portnoy...
We consider the problem of estimating quantile regression coefficients in errorsin -variables models. When the error variables for both the response and the manifest variables have a joint...
COBS: Qualitatively Constrained Smoothing via Linear Programming (1998)
this paper, we attempt to bring the problem of constrained spline smoothing to the foreground and describe the details of a constrained B-spline smoothing (COBS) algorithm that is being made...
High Breakdown Estimation for Multiple Populations With Applications to Discriminant Analysis (1998)
This paper considers the S-estimators for multivariate location and dispersion parameters in multiple populations with a common covariance matrix. We use multivariate normal as our central model but...
Monotone B-spline Smoothing (1997)
Estimation of growth curves or item response curves often involves monotone data smoothing. Methods that have been studied in the literature tend to be either less flexible or more difficult to...
Bivariate Tensor-product B-Splines in a Partly Linear Model (1997)
: In some applications, the mean or median response is linearly related to some variables but the relation to additional variables are not easily parameterized. Partly linear models arise naturally...
Bivariate Quantile Smoothing Splines (1997)
Xuming He, Pin Ng, Stephen Portnoy
It has long been recognized that the mean provides an inadequate summary while the set of quantiles can supply a more complete description of a sample. We introduce bivariate quantile smoothing...
Monotone B-spline Smoothing (1997)
Estimation of growth curves or item response curves often involves monotone data smoothing. Methods that have been studied in the literature tend to be either less flexible or more difficult to...
Bailey, David M., Simpson, Douglas G., He, Xuming, Geling, Olga, Lau, Shun
The ROOFER Engineered Management System (EMS), developed by the U.S. Army Construction Engineering Research Laboratories (USACERL), enables Army installations to capture roofing inspection data in a...
Asymptotics Of The Deepest Line (1997)
. We consider the asymptotic behavior of the regression line based on a new notion of maximumdepth proposed in Rousseeuw and Hubert (1996). We prove consistency at the usual n Gamma1=2 rate, and...
Convergence of depth contours for multivariate datasets (1997)
Contours of depth often provide a good geometrical understanding of the structure of a multivariate dataset. They are also useful in robust statistics in connection with generalized medians and data...
COBS: Qualitatively Constrained Smoothing via Linear Programming (1996)
this paper we bring the problem of constrained spline smoothing to the foreground and describe the details of a constrained B-spline smoothing (COBS) algorithm that is being made available to Splus...
We obtain strong Bahadur representations for a general class of M-estimators that satisfies $\Sigma_i \psi (x_i, \theta) = o(\delta_n)$, where the $x_i$'s are independent but not necessarily...
We consider the problem of estimating quantile regression coefficients in errorsin -variables models. When the error variables for both the response and the manifest variables have a joint...
Remarks on M-Type Smoothers with Edge Preserving Properties (1970)
Douglas G. Simpson, Xuming He, Yao-tsorng Liu
this paper to stimulate more research in the area. It raises many issues and provides many practical insights.
A Data-Adaptive Knot Selection Scheme for Fitting Splines (1970)
Xuming He, Lixin Shen, Zuowei Shen
A critical component of spline smoothing is the choice of knots, especially for curves with varying shapes and frequencies in its domain. We consider a two-stage knot selection scheme for adaptively...
A study of inter-lab and inter-platform agreement of DNA microarray data
Wang, Huixia, He, Xuming, Band, Mark, Wilson, Carole, Liu, Lei
As gene expression profile data from DNA microarrays accumulate rapidly, there is a natural need to compare data across labs and platforms. Comparisons of microarray data can be quite challenging due...
Quantile Regression Estimates for a Class of Linear and Partially Linear Errors-in-Variables Models
We consider the problem of estimating quantile regression coefficients in errors-in-variables models. When the error variables for both the response and the manifest variables have a joint...
Quantile Regression Estimates for a Class of Linear and Partially Linear Errors-in-Variables Models
We consider the problem of estimating quantile regression coefficients in errors-in-variables models. When the error variables for both the response and the manifest variables have a joint...
A study of inter-lab and inter-platform agreement of DNA microarray data
Wang, Huixia, He, Xuming, Band, Mark, Wilson, Carole, Liu, Lei
As gene expression profile data from DNA microarrays accumulate rapidly, there is a natural need to compare data across labs and platforms. Comparisons of microarray data can be quite challenging due...
Local Influence Analysis for Penalized Gaussian Likelihood Estimators in Partially Linear Models
Zhong-Yi Zhu, Xuming He, Wing-Kam Fung
Partially linear models are extensions of linear models to include a non-parametric function of some covariate. They have been found to be useful in both cross-sectional and longitudinal studies....
Ricardo Fraiman, Jean Meloche, Luis García-Escudero, Alfonso Gordaliza, Xuming He, Ricardo Maronna, ...
Approximate likelihood depth, asymptotic normality, equivariance, multivariate order statistics, Primary 62G05, secondary 62G20,
Estimation in a semiparametric model for longitudinal data with unspecified dependence structure
This paper considers an extension of M-estimators in semiparametric models for independent observations to the case of longitudinal data. We approximate the nonparametric function by a regression...
Robust and efficient estimation under data grouping
The minimum Hellinger distance estimator is known to have desirable properties in terms of robustness and efficiency. We propose an approximate minimum Hellinger distance estimator by adapting the...
Bahadur efficiency and robustness of studentized score tests
Bahadur slope, efficiency, influence function, score test,
On the asymptotics of marginal regression splines with longitudinal data
There have been studies on how the asymptotic efficiency of a nonparametric function estimator depends on the handling of the within-cluster correlation when nonparametric regression models are used...