The change-plane Cox model

Penalized Estimators in Cox Regression Model

The proportional hazard Cox regression models play a key role in analyzing censored survival data. We use penalized methods in high dimensional scenarios to achieve more efficient models. This article reviews the penalized Cox regression for some frequently used penalty functions. Analysis of medical data namely ”mgus2” confirms the penalized Cox regression performs better than the cox regressi...

Low-Thrust Optimal Orbit Raising with Plane Change

A new guidance scheme for the problem of Low-thrust transfer between inclined orbits is developed within the framework of optimal control theory. The objective of the guidance scheme is to provide the appropriate thrust steering program that will transfer the vehicle from an inclined low earth orbits to the high earth orbits. The presented guidance scheme is determined using Pontryagin’s princi...

Model assisted Cox regression

Semiparametric random censorship (SRC) models (Dikta, 1998), derive their rationale from their ability to gainfully utilize parametric ideas within the random censorship environment. An extension of this approach is developed for Cox regression, producing new estimators of the regression parameter and baseline cumulative hazard function. Under correct parametric specification, the proposed esti...

Understanding the Cox Regression Models with Time-Change Covariates

The Cox regression model is a cornerstone of modern survival analysis and is widely used in many other fields as well. But the Cox models with time-change covariates are not easy to understand or visualize. We therefore offer a simple and easy-to-understand interpretation of the (arbitrary) baseline hazard and time-change covariate. This interpretation also provides a way to simulate variables ...

Estimation for the Cox Model withInterval