Forster and Sober on the curve-fitting problem

Forster and Sober present a solution to the curve-fitting problem based on Akaike's Theorem. Their analysis shows that the curve with the best epistemic credentials need not always be the curve that most closely fits the data. However, their solution does not, without further argument, avoid the two difficulties that are traditionally associated with the curve-fitting problem: that there are infinitely many equally good candidate-curves relative to any given set of data, and that these best candidates include curves with indefinitely many bumps
Keywords No keywords specified (fix it)
Categories (categorize this paper)
DOI 10.1093/bjps/46.2.248
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index
Download options
PhilPapers Archive

Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 16,658
External links
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library
References found in this work BETA

No references found.

Add more references

Citations of this work BETA
Rhonda Martens (2009). Harmony and Simplicity: Aesthetic Virtues and the Rise of Testability. Studies in History and Philosophy of Science Part A 40 (3):258-266.
Wang-Yen Lee (2013). Akaike's Theorem and Weak Predictivism in Science. Studies in History and Philosophy of Science Part A 44 (4):594-599.

Add more citations

Similar books and articles

Monthly downloads

Added to index


Total downloads

175 ( #11,316 of 1,725,999 )

Recent downloads (6 months)

160 ( #4,020 of 1,725,999 )

How can I increase my downloads?

My notes
Sign in to use this feature

Start a new thread
There  are no threads in this forum
Nothing in this forum yet.