Teddy Seidenfeld
Biographic Data
| ID | 1067640 |
|---|---|
| NAME | Teddy Seidenfeld |
| GIVEN NAMES | Teddy |
| FAMILY NAME | Seidenfeld |
| SIGNATURE | SEIDENFELD T |
| AFFILIATIONS | Carnegie Mellon University |
| ORCID | 0000-0003-4828-2388 |
| VERIFIED | Yes |
| TOTAL WORKS | 22 |
| TOTAL CITATIONS | 66 |
| AUTHOR COUNT | 22 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1977 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 5 |
Finite Additivity, Complete Additivity, and the Comparative Principle
In the longstanding foundational debate whether to require that probability is countably additive, in addition to being finitely additive, those who resist the added condition raise two concerns that we take up in this paper. (1) Existence : Settings where no countably additive probability exists though finitely additive probabilities do. (2) Complete Additivity : Where reasons for countable additivity don’t stop there. Those reasons entail compl…
Deceptive Credences
A familiar defense of Personalist or Subjective Bayesian theory is that, under a variety of sufficient conditions, asymptotically—with increasing shared evidence—almost surely, each non-extreme, countably additive Bayesian opinion, when updated by conditionalization, converges to certainty that is veridical about the truth/falsity of hypotheses of interest. Then, with probability 1 over possible evidential histories, personal probabilities track …
Subjective causal networks and indeterminate suppositional credences
Standards for Modest Bayesian Credences
Gordon Belot argues that Bayesian theory is epistemologically immodest. In response, we show that the topological conditions that underpin his criticisms of asymptotic Bayesian conditioning are self-defeating. They require extreme a priori credences regarding, for example, the limiting behavior of observed relative frequencies. We offer a different explication of Bayesian modesty using a goal of consensus: rival scientific opinions should be resp…
Sleeping Beauty’s Credences
The Sleeping Beauty problem has spawned a debate between “thirders” and “halfers” who draw conflicting conclusions about Sleeping Beauty's credence that a coin lands heads. Our analysis is based on a probability model for what Sleeping Beauty knows at each time during the experiment. We show that conflicting conclusions result from different modeling assumptions that each group makes. Our analysis uses a standard “Bayesian” account of rational be…
Probability Theory
The Effect of Exchange Rates on Statistical Decisions
Statistical decision theory, whether based on Bayesian principles or other concepts such as minimax or admissibility, relies on minimizing expected loss or maximizing expected utility. Loss and utility functions are generally treated as unit-less numerical measures of value for consequences. Here, we address the issue of the units in which loss and utility are settled and the implications that those units have on the rankings of potential decisio…
Coherent choice functions under uncertainty
Degrees of Belief
Nominalism and Its Aftermath
A Contrast Between two Decision Rules for use with (Convex) Sets of Probabilities
A Rate of Incoherence Applied to Fixed-Level Testing
It has long been known that the practice of testing all hypotheses at the same level (such as 0.05), regardless of the distribution of the data, is not consistent with Bayesian expected utility maximization. According to de Finetti's “Dutch Book” argument, procedures that are not consistent with expected utility maximization are incoherent and they lead to gambles that are sure to lose no matter what happens. In this paper, we use a method to mea…
Divisive Conditioning
Conditioning can make imprecise probabilities uniformly more imprecise. We call this effect “dilation”. In a previous paper (1993), Seidenfeld and Wasserman established some basic results about dilation. In this paper we further investigate dilation on several models. In particular, we consider conditions under which dilation persists under marginalization and we quantify the degree of dilation. We also show that dilation manifests itself asympto…
When Several Bayesians Agree that There will be no Reasoning to a Foregone Conclusion
When can a Bayesian investigator select an hypothesis H and design an experiment (or a sequence of experiments) to make certain that, given the experimental outcome(s), the posterior probability of H will be lower than its prior probability? We report an elementary result which establishes sufficient conditions under which this reasoning to a foregone conclusion cannot occur. Through an example, we discuss how this result extends to the perspecti…
Jeffreys, Fisher, and Keynes
Research Article| December 01 1995 Jeffreys, Fisher, and Keynes: Predicting the Third Observation, Given the First Two Teddy Seidenfeld Teddy Seidenfeld Search for other works by this author on: This Site Google History of Political Economy (1995) 27 (Supplement): 39–52. https://doi.org/10.1215/00182702-27-Supplement-39 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Teddy Seidenfeld; Jeffreys, Fi…
Entropy and Uncertainty
This essay is, primarily, a discussion of four results about the principle of maximizing entropy (MAXENT) and its connections with Bayesian theory. Result 1 provides a restricted equivalence between the two: where the Bayesian model for MAXENT inference uses an “a priori“ probability that is uniform, and where all MAXENT constraints are limited to 0–1 expectations for simple indicator-variables. The other three results report on an inability to e…
Calibration, Coherence, and Scoring Rules
Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring “goodness“ of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of .5 occur, 70 percent of forecasts made with probability …
Probability and Evidence
A Conflict between Finite Additivity and Avoiding Dutch Book
For Savage (1954) as for de Finetti (1974), the existence of subjective (personal) probability is a consequence of the normative theory of preference. (De Finetti achieves the reduction of belief to desire with his generalized Dutch-Book argument for previsions. ) Both Savage and de Finetti rebel against legislating countable additivity for subjective probability. They require merely that probability be finitely additive. Simultaneously, they ins…
On After-Trial Properties of Best Neyman-Pearson Confidence Intervals
On pp. 55–58 of Philosophical Problems of Statistical Inference (Seidenfeld 1979), I argue that in light of unsatisfactory after-trial properties of “best” Neyman-Pearson confidence intervals, we can strengthen a traditional criticism of the orthodox N-P theory. The criticism is that, once particular data become available, we see that the pre-trial concern for tests of maximum power (and for their derivative confidence intervals of shortest expec…
Philosophical Problems of Statistical Inference
Induction, Probability, and Confirmation
Coherent choice functions under uncertainty
A Contrast Between two Decision Rules for use with (Convex) Sets of Probabilities
A Conflict between Finite Additivity and Avoiding Dutch Book
For Savage (1954) as for de Finetti (1974), the existence of subjective (personal) probability is a consequence of the normative theory of preference. (De Finetti achieves the reduction of belief to desire with his generalized Dutch-Book argument for previsions. ) Both Savage and de Finetti rebel against legislating countable additivity for subjective probability. They require merely that probability be finitely additive. Simultaneously, they ins…
Entropy and Uncertainty
This essay is, primarily, a discussion of four results about the principle of maximizing entropy (MAXENT) and its connections with Bayesian theory. Result 1 provides a restricted equivalence between the two: where the Bayesian model for MAXENT inference uses an “a priori“ probability that is uniform, and where all MAXENT constraints are limited to 0–1 expectations for simple indicator-variables. The other three results report on an inability to e…
Calibration, Coherence, and Scoring Rules
Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring “goodness“ of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of .5 occur, 70 percent of forecasts made with probability …
Divisive Conditioning
Conditioning can make imprecise probabilities uniformly more imprecise. We call this effect “dilation”. In a previous paper (1993), Seidenfeld and Wasserman established some basic results about dilation. In this paper we further investigate dilation on several models. In particular, we consider conditions under which dilation persists under marginalization and we quantify the degree of dilation. We also show that dilation manifests itself asympto…
Standards for Modest Bayesian Credences
Gordon Belot argues that Bayesian theory is epistemologically immodest. In response, we show that the topological conditions that underpin his criticisms of asymptotic Bayesian conditioning are self-defeating. They require extreme a priori credences regarding, for example, the limiting behavior of observed relative frequencies. We offer a different explication of Bayesian modesty using a goal of consensus: rival scientific opinions should be resp…
Subjective causal networks and indeterminate suppositional credences
Sleeping Beauty’s Credences
The Sleeping Beauty problem has spawned a debate between “thirders” and “halfers” who draw conflicting conclusions about Sleeping Beauty's credence that a coin lands heads. Our analysis is based on a probability model for what Sleeping Beauty knows at each time during the experiment. We show that conflicting conclusions result from different modeling assumptions that each group makes. Our analysis uses a standard “Bayesian” account of rational be…
A Rate of Incoherence Applied to Fixed-Level Testing
It has long been known that the practice of testing all hypotheses at the same level (such as 0.05), regardless of the distribution of the data, is not consistent with Bayesian expected utility maximization. According to de Finetti's “Dutch Book” argument, procedures that are not consistent with expected utility maximization are incoherent and they lead to gambles that are sure to lose no matter what happens. In this paper, we use a method to mea…
When Several Bayesians Agree that There will be no Reasoning to a Foregone Conclusion
When can a Bayesian investigator select an hypothesis H and design an experiment (or a sequence of experiments) to make certain that, given the experimental outcome(s), the posterior probability of H will be lower than its prior probability? We report an elementary result which establishes sufficient conditions under which this reasoning to a foregone conclusion cannot occur. Through an example, we discuss how this result extends to the perspecti…
On After-Trial Properties of Best Neyman-Pearson Confidence Intervals
On pp. 55–58 of Philosophical Problems of Statistical Inference (Seidenfeld 1979), I argue that in light of unsatisfactory after-trial properties of “best” Neyman-Pearson confidence intervals, we can strengthen a traditional criticism of the orthodox N-P theory. The criticism is that, once particular data become available, we see that the pre-trial concern for tests of maximum power (and for their derivative confidence intervals of shortest expec…
The Effect of Exchange Rates on Statistical Decisions
Statistical decision theory, whether based on Bayesian principles or other concepts such as minimax or admissibility, relies on minimizing expected loss or maximizing expected utility. Loss and utility functions are generally treated as unit-less numerical measures of value for consequences. Here, we address the issue of the units in which loss and utility are settled and the implications that those units have on the rankings of potential decisio…
Jeffreys, Fisher, and Keynes
Research Article| December 01 1995 Jeffreys, Fisher, and Keynes: Predicting the Third Observation, Given the First Two Teddy Seidenfeld Teddy Seidenfeld Search for other works by this author on: This Site Google History of Political Economy (1995) 27 (Supplement): 39–52. https://doi.org/10.1215/00182702-27-Supplement-39 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Teddy Seidenfeld; Jeffreys, Fi…
Induction, Probability, and Confirmation
On After-Trial Properties of Best Neyman-Pearson Confidence Intervals
On pp. 55–58 of Philosophical Problems of Statistical Inference (Seidenfeld 1979), I argue that in light of unsatisfactory after-trial properties of “best” Neyman-Pearson confidence intervals, we can strengthen a traditional criticism of the orthodox N-P theory. The criticism is that, once particular data become available, we see that the pre-trial concern for tests of maximum power (and for their derivative confidence intervals of shortest expec…
Philosophical Problems of Statistical Inference
A Conflict between Finite Additivity and Avoiding Dutch Book
For Savage (1954) as for de Finetti (1974), the existence of subjective (personal) probability is a consequence of the normative theory of preference. (De Finetti achieves the reduction of belief to desire with his generalized Dutch-Book argument for previsions. ) Both Savage and de Finetti rebel against legislating countable additivity for subjective probability. They require merely that probability be finitely additive. Simultaneously, they ins…
Probability and Evidence
Calibration, Coherence, and Scoring Rules
Can there be good reasons for judging one set of probabilistic assertions more reliable than a second? There are many candidates for measuring “goodness“ of probabilistic forecasts. Here, I focus on one such aspirant: calibration. Calibration requires an alignment of announced probabilities and observed relative frequency, e.g., 50 percent of forecasts made with the announced probability of .5 occur, 70 percent of forecasts made with probability …
Entropy and Uncertainty
This essay is, primarily, a discussion of four results about the principle of maximizing entropy (MAXENT) and its connections with Bayesian theory. Result 1 provides a restricted equivalence between the two: where the Bayesian model for MAXENT inference uses an “a priori“ probability that is uniform, and where all MAXENT constraints are limited to 0–1 expectations for simple indicator-variables. The other three results report on an inability to e…
Jeffreys, Fisher, and Keynes
Research Article| December 01 1995 Jeffreys, Fisher, and Keynes: Predicting the Third Observation, Given the First Two Teddy Seidenfeld Teddy Seidenfeld Search for other works by this author on: This Site Google History of Political Economy (1995) 27 (Supplement): 39–52. https://doi.org/10.1215/00182702-27-Supplement-39 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Teddy Seidenfeld; Jeffreys, Fi…
When Several Bayesians Agree that There will be no Reasoning to a Foregone Conclusion
When can a Bayesian investigator select an hypothesis H and design an experiment (or a sequence of experiments) to make certain that, given the experimental outcome(s), the posterior probability of H will be lower than its prior probability? We report an elementary result which establishes sufficient conditions under which this reasoning to a foregone conclusion cannot occur. Through an example, we discuss how this result extends to the perspecti…
Divisive Conditioning
Conditioning can make imprecise probabilities uniformly more imprecise. We call this effect “dilation”. In a previous paper (1993), Seidenfeld and Wasserman established some basic results about dilation. In this paper we further investigate dilation on several models. In particular, we consider conditions under which dilation persists under marginalization and we quantify the degree of dilation. We also show that dilation manifests itself asympto…
A Rate of Incoherence Applied to Fixed-Level Testing
It has long been known that the practice of testing all hypotheses at the same level (such as 0.05), regardless of the distribution of the data, is not consistent with Bayesian expected utility maximization. According to de Finetti's “Dutch Book” argument, procedures that are not consistent with expected utility maximization are incoherent and they lead to gambles that are sure to lose no matter what happens. In this paper, we use a method to mea…
A Contrast Between two Decision Rules for use with (Convex) Sets of Probabilities
Degrees of Belief
Nominalism and Its Aftermath
Coherent choice functions under uncertainty
The Effect of Exchange Rates on Statistical Decisions
Statistical decision theory, whether based on Bayesian principles or other concepts such as minimax or admissibility, relies on minimizing expected loss or maximizing expected utility. Loss and utility functions are generally treated as unit-less numerical measures of value for consequences. Here, we address the issue of the units in which loss and utility are settled and the implications that those units have on the rankings of potential decisio…
Probability Theory
Sleeping Beauty’s Credences
The Sleeping Beauty problem has spawned a debate between “thirders” and “halfers” who draw conflicting conclusions about Sleeping Beauty's credence that a coin lands heads. Our analysis is based on a probability model for what Sleeping Beauty knows at each time during the experiment. We show that conflicting conclusions result from different modeling assumptions that each group makes. Our analysis uses a standard “Bayesian” account of rational be…
Standards for Modest Bayesian Credences
Gordon Belot argues that Bayesian theory is epistemologically immodest. In response, we show that the topological conditions that underpin his criticisms of asymptotic Bayesian conditioning are self-defeating. They require extreme a priori credences regarding, for example, the limiting behavior of observed relative frequencies. We offer a different explication of Bayesian modesty using a goal of consensus: rival scientific opinions should be resp…
Deceptive Credences
A familiar defense of Personalist or Subjective Bayesian theory is that, under a variety of sufficient conditions, asymptotically—with increasing shared evidence—almost surely, each non-extreme, countably additive Bayesian opinion, when updated by conditionalization, converges to certainty that is veridical about the truth/falsity of hypotheses of interest. Then, with probability 1 over possible evidential histories, personal probabilities track …
Subjective causal networks and indeterminate suppositional credences
Finite Additivity, Complete Additivity, and the Comparative Principle
In the longstanding foundational debate whether to require that probability is countably additive, in addition to being finitely additive, those who resist the added condition raise two concerns that we take up in this paper. (1) Existence : Settings where no countably additive probability exists though finitely additive probabilities do. (2) Complete Additivity : Where reasons for countable additivity don’t stop there. Those reasons entail compl…
Mathematics (17 works) · Epistemology (14 works) · Computer Science (13 works) · Philosophy (13 works) · Statistics (12 works) · Bayesian Modeling and Causal Inference (11 works) · Mathematical economics (9 works) · Artificial Intelligence (6 works) · Bayesian probability (6 works) · Decision-Making and Behavioral Economics (6 works)