Semiparametric Transformation Models for Point Processes

By Danyu Lin, Lee-Jen Wei, Zhiliang Ying. 2001

116 citations recorded by the source corpus.

Subfields: Applied Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c37aa4c5ab053b3274a79f970a56fbd32fec0a79

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Xinyuan Song
2. Hulin Wu
3. Yanqing Sun

In Statistics and Probability

1. Liuquan Sun
2. Xinyuan Song
3. Hulin Wu
4. Jie Zhou
5. Yanqing Sun
6. Lei Liu
7. Yixin Fang

Citations in the corpus

• Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event (2012, background): “However, it does not appear possible to derive optimal weights without specification of the covariance function of the longitudinal process and the observation process, and the selection of weight functions is usually a complicated problem (e.g., Lin, Wei, and Ying 2001).”
• Semiparametric Time‐Varying Coefficients Regression Model for Longitudinal Data (2005, methodology): “S) of Lin et al. (2000),”
• Semiparametric Transformation Models With Random Effects for Recurrent Events (2007, unknown): “For timeindependent covariates, Lin, Wei, and Ying (2001) proposed a class of transformation models for the mean function”
• Efficient estimation of semiparametric transformation models for counting processes (2006, unknown): “LIN For recurrent events with time-invariate covariates, Lin et al. (2001) studied the following class of transformation models for the mean frequency functions:”