Modeling gap times between recurrent events by marginal rate function
From MaRDI portal
Publication:425394
DOI10.1016/J.CSDA.2011.07.015zbMath1239.62101OpenAlexW2011359741MaRDI QIDQ425394
Publication date: 8 June 2012
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2011.07.015
Asymptotic properties of parametric estimators (62F12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Non-Markovian processes: estimation (62M09) Markov processes: estimation; hidden Markov models (62M05)
Related Items (7)
A semi-parametric approach to analysis of event duration and prevalence ⋮ An extended poisson family of life distribution: a unified approach in competitive and complementary risks ⋮ The semiparametric accelerated trend-renewal process for recurrent event data ⋮ Marginal regression of recurrent gap times based on semiparametric transformation cure model ⋮ The Poisson-exponential model for recurrent event data: an application to bowel motility data ⋮ The exponential‐Poisson model for recurrent event data: An application to a set of data on malaria in Brazil ⋮ The Exponential-Poisson Regression Model for Recurrent Events: A Bayesian Approach
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A semiparametric additive rates model for recurrent event data
- Credibility premiums for the zero-inflated Poisson model and new hunger for bonus interpretation
- Mixture modelling of recurrent event times with long-term survivors: Analysis of Hutterite birth intervals
- Profile likelihood and conditionally parametric models
- Marginal regression of gaps between recurrent events
- The statistical analysis of recurrent events.
- On modeling claim frequency data in general insurance with extra zeros
- Proportional hazards models for survival data with long-term survivors
- Local Likelihood Estimation
- Regression methods for gap time hazard functions of sequentially ordered multivariate failure time data
- Partially Linear Hazard Regression with Varying Coefficients for Multivariate Survival Data
- Local Maximum Likelihood Estimation and Inference
- Nonparametric estimation of the gap time distribution for serial events with censored data
- Local Polynomial Estimation in Multiparameter Likelihood Models
- Analyzing Recurrent Event Data With Informative Censoring
- Frequency of Recurrent Events at Failure Time
- Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
- Nonparametric Estimation of a Recurrent Survival Function
- Functional-Coefficient Regression Models for Nonlinear Time Series
- Nonparametric and Semiparametric Trend Analysis for Stratified Recurrence Times
- One-step Local Quasi-likelihood Estimation
- Risk Classification for Claim Counts
- Analysis of repeated events
- Semiparametric Analysis of Correlated Recurrent and Terminal Events
- Kernel Estimation of Rate Function for Recurrent Event Data
- Understanding Relationships Using Copulas
- A kernel smoothed semiparametric survival model
This page was built for publication: Modeling gap times between recurrent events by marginal rate function
