Penalty and shrinkage strategies based on local polynomials for right-censored partially linear regression

HIGHLIGHTS

• who: Syed Ejaz Ahmed and colleagues from the Department of Mathematics and Statistics, Brock University, StCatharines, ON L S , Canada have published the research work: Penalty and Shrinkage Strategies Based on Local Polynomials for Right-Censored Partially Linear Regression, in the Journal: Entropy 2022, 1833 of /2022/
• what: For instance, in clinical trials, some of the observed patients may withdraw from the study before it ends, or they may die from another reason, which makes the corresponding observation right-censored. The simulation design and data generation are described as follows: Simulation Design: Two main scenarios . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.