Results 151 to 160 of about 5,713 (196)
Regression for Left-Truncated and Right-Censored Data: A Semiparametric Sieve Likelihood Approach. [PDF]
Matthews S, Nan B.
europepmc +1 more source
Semiparametric outcome regression-based estimator of Mann-Whitney-type causal effect. [PDF]
Sani SS +11 more
europepmc +1 more source
Integrating preliminary test and Stein-type techniques to improve estimation in the time-dependent Cox model. [PDF]
Ramezani R, Rabiei MR, Arashi M.
europepmc +1 more source
Deep learning for the change-point Cox model with current status data. [PDF]
Huang Q, Feng A, Wu Q, Tong X.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Efficiency Bounds for Semiparametric Regression
Econometrica, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
SEMIPARAMETRIC TIME SERIES REGRESSION
Journal of Time Series Analysis, 1994Abstract.Let (Xi,Yi),i= 0, pL 1,… denote a bivariate stationary time series withXibeing Rd‐valued andYibeing real‐valued. We consider the regression modelYi=θ(Xi) +Zi, where θ(·) is an unknown function and Ziis an autoregressive process. Given a realization of lengthn, we examine the problem of estimating the nonparametric function θ(·) and the ...
Truong, Young K., Stone, Charles J.
openaire +1 more source
2003
Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the ...
David Ruppert, M. P. Wand, R. J. Carroll
openaire +1 more source
Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the ...
David Ruppert, M. P. Wand, R. J. Carroll
openaire +1 more source
Semiparametric regression model selections
Journal of Statistical Planning and Inference, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shi, Peide, Tsai, Chih-Ling
openaire +1 more source

