Abstract
We use the statistical framework known as algorithmic inference explained in Chapter 1 of this book to provide confidence intervals for the cumulative distribution and hazard function of a set of survival data [Boracchi and Biganzoli, 2001].
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media New York
About this chapter
Cite this chapter
Apolloni, B., Gaito, S., Malchiodi, D. (2002). Learning and Checking Confidence Regions for the Hazard Function of Biomedical Data. In: Apolloni, B., Kurfess, F. (eds) From Synapses to Rules. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0705-5_13
Download citation
DOI: https://doi.org/10.1007/978-1-4615-0705-5_13
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5204-4
Online ISBN: 978-1-4615-0705-5
eBook Packages: Springer Book Archive