Abstract
Probability. Measure. Integration. Random Variables and Expected Values. Convergence of Distributions. Derivatives and Conditional Probability. Stochastic Processes. Appendix. Notes on the Problems. Bibliography. List of Symbols. Index.
Keywords
Measure (data warehouse)StatisticsMathematicsComputer scienceData mining
Related Publications
Analysis of Longitudinal Data
1. Introduction 2. Design considerations 3. Exploring longitudinal data 4. General linear models 5. Parametric models for covariance structure 6. Analysis of variance methods 7....
Training Products of Experts by Minimizing Contrastive Divergence
It is possible to combine multiple latent-variable models of the same data by multiplying their probability distributions together and then renormalizing. This way of combining ...
Multivariate Smoothing Spline Functions
Given data $z_i = g(t_i ) + \varepsilon _i , 1 \leqq i \leqq n$, where g is the unknown function, the $t_i $ are known d-dimensional variables in a domain $\Omega $, and the $\v...
Inference from Iterative Simulation Using Multiple Sequences
The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, ho...
An Intertemporal General Equilibrium Model of Asset Prices
This paper develops a continuous time general equilibrium model of a simple but complete economy and uses it to examine the behavior of asset prices. In this model, asset prices...
Publication Info
- Year
- 1996
- Type
- article
- Volume
- 91
- Issue
- 433
- Pages
- 441-441
- Citations
- 6652
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
6652
OpenAlex
Cite This
PE,
P. Billingsley
(1996).
Probability and Measure..
Journal of the American Statistical Association
, 91
(433)
, 441-441.
https://doi.org/10.2307/2291440
Identifiers
- DOI
- 10.2307/2291440