NONPARAMETRIC ESTIMATION OF CONDITIONAL CUMULATIVE HAZARDS FOR MISSING POPULATION MARKS
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Publication:2810414
DOI10.1111/j.1467-842X.2009.00567.xzbMath1337.62048WikidataQ34066914 ScholiaQ34066914MaRDI QIDQ2810414
Amalia Jácome Pumar, Dipankar Bandyopadhyay
Publication date: 1 June 2016
Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)
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- Data. A collection of problems from many fields for the student and research worker
- Density and hazard rate estimation for censored data via strong representation of the Kaplan-Meier estimator
- Strong embedding of the estimator of the distribution function under random censorship
- Nonparametric inference for a family of counting processes
- Nonparametric estimation for nonhomogeneous Markov processes in the problem of competing risks
- A strong representation of the product-limit estimator for left truncated and right censored data
- Estimating future stage entry and occupation probabilities in a multistage model based on randomly right-censored data
- Kaplan-Meier representation of competing risk estimates
- Testing equality of survival distributions when the population marks are missing
- Restricted tests for testing independence of time to failure and cause of failure in a competing-risks model
- The Presmoothed Nelson–Aalen Estimator in the Competing Risk Model
- Prediction of Cumulative Incidence Function under the Proportional Hazards Model
- On Testing Dependence between Time to Failure and Cause of Failure via Conditional Probabilities
- Fitting competing risks with an assumed copula
- Statistical models based on counting processes
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