Statistical modelling via partitioned counting processes
type: Item
instance of: scholarly article
title: Statistical modelling via partitioned counting processes
zbMATH Open document ID: 0572.62078
DOI: 10.1016/0378-3758(85)90066-7
author: B. George
published in: Journal of Statistical Planning and Inference
publication date: 1985-01-01T00:00:00Z
review text: Partitioned counting processes arise from observation of the jumps of a counting process in disjoint stochastic time intervals. The multiplicative intensity model for a counting process is a statistical model for nonparametric inference about, e.g., the hazard function of a survival time distribution. In non-standard situations when the data are recorded only between two stopping times which vary from one individual to another, partitioned counting processes provide a simple approach to statistical modelling. Some recent extensions of Cox's regression model can be justified.
Mathematics Subject Classification ID: 62M99
Mathematics Subject Classification ID: 60K99
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 3913502
zbMATH Keywords: point process
zbMATH Keywords: Partitioned counting processes
zbMATH Keywords: multiplicative intensity model
zbMATH Keywords: hazard function
zbMATH Keywords: survival time distribution
zbMATH Keywords: extensions of Cox's regression model
MaRDI profile type: Publication
full work available at URL: 0378-3758(85)90066-7
OpenAlex ID: W1982676112
cites work: Nonparametric inference for a family of counting processes
cites work: Q3899365
cites work: Q4164219
cites work: Linear Nonparametric Tests for Comparison of Counting Processes, with Applications to Censored Survival Data, Correspondent Paper
cites work: Cox's regression model for counting processes: A large sample study
cites work: Point processes and queues. Martingale dynamics
cites work: Q3862765
cites work: Q5654899
cites work: Partial likelihood
cites work: Q3957682
cites work: Q3957683
cites work: Q3906237
cites work: Statistical analysis of counting processes
cites work: An Extension of Cox's Regression Model
cites work: The analysis of transition times in multistate stochastic processes using proportional hazard regression models
cites work: On the regression analysis of multivariate failure time data
cites work: A semi-Markov model for survival data with covariates
description: scientific article; zbMATH DE number 3913502