Results 91 to 100 of about 149 (141)

Sufficient dimension reduction for the conditional mean with a categorical predictor in multivariate regression

Recent sufficient dimension reduction methodologies in multivariate regression do not have direct application to a categorical predictor. For this, we define the multivariate central partial mean subspace and propose two methodologies to estimate it. The
Yoo, Jae Keun
core  

TSSS: A Novel Triangulated Spherical Spline Smoothing for Surface-Based Data. [PDF]

J Nonparametr Stat
Gu Z, Yu S, Wang G, Lai MJ, Wang L.
europepmc   +1 more source

A refined Jensen's inequality in Hilbert spaces and empirical approximations

Let be a convex mapping and a Hilbert space. In this paper we prove the following refinement of Jensen's inequality: for every A,B such that and B[subset of]A.
Leorato, S.
core  

Linear Wavelet-Based Estimators of Partial Derivatives of Multivariate Density Function for Stationary and Ergodic Continuous Time Processes. [PDF]

Entropy (Basel)
Didi S, Bouzebda S.
europepmc   +1 more source

Sparse canonical correlation analysis between an alcohol biomarker and self-reported alcohol consumption. [PDF]

Commun Stat Simul Comput, 2017
Helian S, Brumback BA, Cook RL.
europepmc   +1 more source

Analysis of correlated binary data under partially linear single-index logistic models

Clustered data arise commonly in practice and it is often of interest to estimate the mean response parameters as well as the association parameters. However, most research has been directed to address the mean response parameters with the association ...
Liang, Hua, Yi, Grace Y., He, Wenqing
core  

Inverse-Probability-Weighted Wavelet Estimation of Regression Derivatives Under Missing-at-Random Responses for Stationary Ergodic Processes. [PDF]

Entropy (Basel)
Bouzebda S, Didi S.
europepmc   +1 more source

Automatic Structure Discovery for Varying-coefficient Partially Linear Models. [PDF]

Commun Stat Theory Methods, 2017
Yang G, Sun Y, Cui X.
europepmc   +1 more source

Flexible modeling based on copulas in nonparametric median regression

Consider the model Y=m(X)+[epsilon], where m([dot operator])=med(Y[dot operator]) is unknown but smooth. It is often assumed that [epsilon] and X are independent. However, in practice this assumption is violated in many cases.
Braekers, Roel, Van Keilegom, Ingrid
core  

ESTIMATION OF A MONOTONE DENSITY IN S-SAMPLE BIASED SAMPLING MODELS. [PDF]

Ann Stat, 2018
Chan KCG, Ling HK, Sit T, Yam SCP.
europepmc   +1 more source