Probability With a View Towards Statistics, Volume II
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A01=J. Hoffman-Jorgensen
asymptotic properties of estimators
Author_J. Hoffman-Jorgensen
banach
Bounded Borel Functions
boundedness
Brownian Motion
Cardinal Number
Category=PBT
Compact Interval
Continuous Sample Paths
Distribution Function
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
estimator consistency theory
exponential family statistics
function
Generalized Inverse
Glivenko Cantelli Theorem
Hausdorff measure applications
Inductive Set
J. Hoffmann-Jorgensen
Local Extremum
Markov chain theory
measurable
Metric Space
Ordinal Number
Poisson Process
Polyhedral Set
Probability Measure
Probability Space
process
random
Random Variables
random walk models
Sample Paths
Separable Metric Space
space
stochastic
Stochastic Process
stochastic process analysis
total
Totally Bounded
variable
Product details
- ISBN 9780412052316
- Weight: 1180g
- Dimensions: 156 x 234mm
- Publication Date: 15 May 1994
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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Volume II of this two-volume text and reference work concentrates on the applications of probability theory to statistics, e.g., the art of calculating densities of complicated transformations of random vectors, exponential models, consistency of maximum estimators, and asymptotic normality of maximum estimators. It also discusses topics of a pure probabilistic nature, such as stochastic processes, regular conditional probabilities, strong Markov chains, random walks, and optimal stopping strategies in random games. Unusual topics include the transformation theory of densities using Hausdorff measures, the consistency theory using the upper definition function, and the asymptotic normality of maximum estimators using twice stochastic differentiability. With an emphasis on applications to statistics, this is a continuation of the first volume, though it may be used independently of that book. Assuming a knowledge of linear algebra and analysis, as well as a course in modern probability, Volume II looks at statistics from a probabilistic point of view, touching only slightly on the practical computation aspects.
