Sandy L Zabell
Biographic Data
| ID | 376683 |
|---|---|
| NAME | Sandy L Zabell |
| GIVEN NAMES | Sandy L |
| FAMILY NAME | Zabell |
| SIGNATURE | ZABELL S L |
| VERIFIED | No |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 18 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1980 |
| LATEST PUBLICATION YEAR | 2015 |
| H-INDEX | 2 |
Neyman, Jerzy (1894–1981)
Updating Subjective Probability
Jeffrey's rule for revising a probability P to a new probability P* based on new probabilities P* (Ei ) on a partition {Ei } i = 1 n is P*(A) = Σ P(A| Ei ) P* (Ei ). Jeffrey's rule is applicable if it is judged that P* (A | Ei ) = P(A | Ei ) for all A and i. This article discusses some of the mathematical properties of this rule, connecting it with sufficient partitions, and maximum entropy updating of contingency tables. The main results concern…
Babies and the blackout: The genesis of a misconception
Why Gibbs Phase Averages Work—The Role of Ergodic Theory
We propose an “explanation scheme” for why the Gibbs phase average technique in classical equilibrium statistical mechanics works. Our account emphasizes the importance of the Khinchin-Lanford dispersion theorems. We suggest that ergodicity does play a role, but not the one usually assigned to it
Why Gibbs Phase Averages Work—The Role of Ergodic Theory
We propose an “explanation scheme” for why the Gibbs phase average technique in classical equilibrium statistical mechanics works. Our account emphasizes the importance of the Khinchin-Lanford dispersion theorems. We suggest that ergodicity does play a role, but not the one usually assigned to it
Babies and the blackout: The genesis of a misconception
Why Gibbs Phase Averages Work—The Role of Ergodic Theory
We propose an “explanation scheme” for why the Gibbs phase average technique in classical equilibrium statistical mechanics works. Our account emphasizes the importance of the Khinchin-Lanford dispersion theorems. We suggest that ergodicity does play a role, but not the one usually assigned to it
Babies and the blackout: The genesis of a misconception
Updating Subjective Probability
Jeffrey's rule for revising a probability P to a new probability P* based on new probabilities P* (Ei ) on a partition {Ei } i = 1 n is P*(A) = Σ P(A| Ei ) P* (Ei ). Jeffrey's rule is applicable if it is judged that P* (A | Ei ) = P(A | Ei ) for all A and i. This article discusses some of the mathematical properties of this rule, connecting it with sufficient partitions, and maximum entropy updating of contingency tables. The main results concern…
Neyman, Jerzy (1894–1981)
Mathematics (4 works) · Statistics (4 works) · Statistical analysis (2 works) · Advanced Thermodynamics and Statistical Mechanics (1 works) · Bayesian Modeling and Causal Inference (1 works) · Bayesian probability (1 works) · Blackout (1 works) · Census and Population Estimation (1 works) · Chain rule (probability) (1 works) · Combinatorics (1 works)