Robust inference for bivariate point processes

DOI10.2307/3316108zbMath1060.62551OpenAlexW1966504168MaRDI QIDQ4944641

Edmund T. M. Ng, Richard J. Cook

Publication date: 1999

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3316108

zbMATH Keywords

Cumulative mean functions, estimating functions, mixed Poisson processes, random effects, recurrent events.

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Non-Markovian processes: estimation (62M09) Robustness and adaptive procedures (parametric inference) (62F35) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (5)

The analysis of multivariate recurrent events with partially missing event types ⋮ Robust Tests for Treatment Effects Based on Censored Recurrent Event Data Observed over Multiple Periods ⋮ Analysis of repeated events ⋮ Semiparametric additive marginal regression models for multiple type recurrent events ⋮ A Bayesian Time-Varying Coefficient Model for Multitype Recurrent Events

Cites Work

• Unnamed Item
• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Modeling of two-state disease processes with random effects
• An extension of quasi-likelihood estimation
• A Point-Process Model Incorporating Renewals and Time Trends, with Application to Repairable Systems
• On linear and quadratic estimating functions
• Regression Methods for Poisson Process Data
• Quasi-Likelihood and Optimal Estimation, Correspondent Paper
• Inference for means and covariances of point processes through estimating functions
• Some Simple Robust Methods for the Analysis of Recurrent Events
• Informative Drop-Out in Longitudinal Data Analysis
• Maximum Likelihood Estimation of Misspecified Models

This page was built for publication: Robust inference for bivariate point processes