Statistical Inference Based on Divergence Measures by Leandro Pardo
Presents classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence with applications to multinomial and generation populations. On the basis of divergence measures, this book introduces minimum divergence estimators as well as divergence test statistics.-
Handbook of Parallel Computing and Statistics
-
Probability and Statistical Inference, Second Edition
-
Handbook of Beta Distribution and Its Applications
-
Bayesian Biostatistics
-
Item Response Theory
-
Response Surfaces: Designs and Analyses
-
Survey Sampling
-
Advanced Linear Models
-
Growth Curves
-
Randomized Response and Indirect Questioning Techniques in Surveys
-
Lognormal Distributions
-
A Primer in Probability
-
Analytical Methods for Risk Management
-
Introduction to Spatial Econometrics
-
Statistical Methods in Discrimination Litigation
-
Mathematical Statistics With Applications
-
The Inverse Gaussian Distribution
-
Asymptotics, Nonparametrics, and Time Series
-
Probability and Statistical Inference
-
Handbook of Empirical Economics and Finance
-
Random Processes
-
Seemingly Unrelated Regression Equations Models
-
Parameter Estimation in Reliability and Life Span Models
-
Applied Regression Analysis and Experimental Design
-
Robust Regression
-
Statistics of Quality
-
Statistical Methods for Engineers and Scientists
-
Econometrics
-
Regression Analysis of Survival Data in Cancer Chemotherapy
-
Randomization Tests
-
Multiple Comparisons, Selection and Applications in Biometry
-
Introduction to Probability and Statistics
-
Linear Least Squares Computations
-
Sample Size Choice
-
Bivariate Discrete Distributions
-
The EM Algorithm and Related Statistical Models
-
Statistics for the 21st Century
-
Improving Efficiency by Shrinkage
"There are a number of measures of divergence between distributionsDescribing them properly requires a very mathematically well-written book, which the author here provides … This book is a fine course text, and is beautifully produced. There are about four hundred references. Recommended."
-ISI Short Book Reviews
". . . suitable for a beginning graduate course on information theory based on statistical inference. This book will be a useful and important addition to the resources of practitioners and many others engaged information theory and statistics. Overall, this is an impressive book on information theory based statistical inference."
– Prasanna Sahoo, in Zentralblatt Math, 2008, Vol. 1120
| SKU | Unavailable |
| ISBN 13 | 9781584886006 |
| ISBN 10 | 1584886005 |
| Title | Statistical Inference Based on Divergence Measures |
| Author | Leandro Pardo |
| Series | Statistics: A Series Of Textbooks And Monographs |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | CRC Press LLC |
| Year published | 2005-10-10 |
| Number of pages | 512 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |