Vassend, Olav B. (2017) Nonstandard Bayesianism: How Verisimilitude and Counterfactual Degrees of Belief Solve the Interpretive Problem in Bayesian Inference. In: UNSPECIFIED.
This is the latest version of this item.
|
Text
philsciarchive2016.pdf Download (511kB) | Preview |
Abstract
Scientists and Bayesian statisticians often study hypotheses that they know to be false. This creates an interpretive problem because the Bayesian probability of a hypothesis is typically interpreted as a degree of belief that the hypothesis is true. In this paper, I present and contrast two solutions to the interpretive problem, both of which involve reinterpreting the Bayesian framework in such a way that pragmatic factors directly determine in part how probability assignments are interpreted and whether a given probability assignment is rational. I argue that there is an important sense in which the two solutions are equivalent, and I suggest that the two reinterpretations can help us do Bayesian inference better. I also explore various features of the two reinterprations, including their relations to the standard Bayesian interpretation of probability and to the Law of Likelihood.
| Export/Citation: | EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL |
| Social Networking: |
| Item Type: | Conference or Workshop Item (UNSPECIFIED) | ||||||
|---|---|---|---|---|---|---|---|
| Creators: |
|
||||||
| Keywords: | Bayesian statistics, verisimilitude, closeness to the truth, interpretation of probability, Bayesian inference, counterfactual degrees of belief | ||||||
| Subjects: | General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
||||||
| Depositing User: | Olav Vassend | ||||||
| Date Deposited: | 04 Aug 2017 15:17 | ||||||
| Last Modified: | 04 Aug 2017 15:17 | ||||||
| Item ID: | 13301 | ||||||
| Subjects: | General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
||||||
| Date: | 4 August 2017 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/13301 |
Available Versions of this Item
-
Bayesian Statistical Inference and Approximate Truth. (deposited 29 Oct 2016 16:56)
- Nonstandard Bayesianism: How Verisimilitude and Counterfactual Degrees of Belief Solve the Interpretive Problem in Bayesian Inference. (deposited 04 Aug 2017 15:17) [Currently Displayed]
Monthly Views for the past 3 years
Monthly Downloads for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](http://philsci-archive.pitt.edu/style/images/feed-icon-32x32.png){kind=icon}