Bayesian Inference in Statistical Analysis by George E P Box
Designed to form the basis of a graduate course on Bayesian inference, this textbook discusses important general issues of the Bayesian approach. It investigates problems, illustrating the appropriate analysis of mathematical results with numerical examples.-
Enzyme Kinetics
-
Introductory Functional Analysis with Applications
-
Differential and Integral Calculus, Volume 1
-
Statistical Models in Engineering
-
Introduction to Geometry
-
Applied and Computational Complex Analysis, 3 Volume Set
-
Geometric Algebra
-
Survival Models and Data Analysis
-
Applied and Computational Complex Analysis, Volume 2
-
Integral Equations
-
Applied and Computational Complex Analysis, Volume 1
-
Lectures on Applications-Oriented Mathematics
-
A Course in Modern Algebra
-
An Introduction to Bayesian Inference in Econometrics
-
Topics in Complex Function Theory, Volume 3
-
Foundations of Differential Geometry, Volume 2
-
Statistics and the Law
-
The Elements of Stochastic Processes with Applications to the Natural Sciences
-
Fitting Equations to Data
-
Evolutionary Operation
-
The Statistical Analysis of Time Series
-
Combinatorial Theory
-
Linear Operators, Part 1
-
Statistical Design for Research
-
Statistics
-
Survival Analysis
-
Mathematical Programming in Statistics
-
Sample Survey Methods and Theory, Volume 2
-
Sample Survey Methods and Theory, Volume 1
-
Statistics for Spatial Data
-
Water Waves
-
Detection, Estimation, and Modulation Theory, Part II
-
Linear Operators, Part 3
-
Simple Groups of Lie Type
-
Stochastic Processes
-
Statistical Optics
-
Applied Statistical Decision Theory
-
Applied and Computational Complex Analysis, Volume 3
-
Planning of Experiments
-
Modern Probability Theory and Its Applications
-
Optimal Statistical Decisions
-
Topics in Complex Function Theory, Volume 2
-
Experimental Designs
-
The Elements of Integration and Lebesgue Measure
-
Understanding Robust and Exploratory Data Analysis
-
Design and Analysis of Clinical Experiments
GEORGE E. P. BOX, PhD, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin, Madison. His lifelong work has defined statistical analysis, while his name and research is a part of some of the most influential statistical constructs, including Box & Jenkins models, Box & Cox transformations, and Box & Behnken designs. Dr. Box is the coauthor of a number of Wiley books, including most recently, Statistical Control by Monitoring and Adjustment, Second Edition; Response Surfaces, Mixtures, and Ridge Analyses, Second Edition; and Improving Almost Anything: Ideas and Essays, Revised Edition.
NORMAN R. DRAPER is professor emeritus at the University of Wisconsin, Madison, in the Department of Statistics. His research interests include Experimental Design, Linear Models, and Nonlinear Estimation.
| SKU | Unavailable |
| ISBN 13 | 9780471574286 |
| ISBN 10 | 0471574287 |
| Title | Bayesian Inference in Statistical Analysis |
| Author | George E P Box |
| Series | Wiley Classics Library |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | John Wiley & Sons Inc |
| Year published | 1992-04-21 |
| Number of pages | 608 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |