Synopsis
Reflecting current technological capacities and analytical trends, this book/CD-ROM package showcases Monte Carlo and nonparametric statistical methods for models, simulations, analyses, and interpretations of statistical and econometric data. Tanizaki (economics, Kobe University, Japan) reviews introductory notions in statistics, explores applications of Monte Carlo methods in Bayesian estimation, state space modeling, and bias correction of ordinary least squares in autoregressive models, and examines computer-intensive, statistical techniques other than Monte Carlo methods and simulations. A beginning chapter introduces statistics and econometrics. Material is written for first-year graduate students.
Annotation ©2004 Book News, Inc., Portland, OR

Table of Contents

Preface
1 Elements of Statistics 1
I Monte Carlo Statistical Methods 77
2 Random Number Generation I 79
3 Random Number Generation II 171
II Selected Applications of Monte Carlo Methods 247
4 Bayesian Estimation 249
5 Bias Correction of OLSE in AR Models 285
6 State Space Modeling 313
III Nonparametric Statistical Methods 391
7 Difference between Two-Sample Means 393
8 Independence between Two Samples 445
Source Code Index 485
Index 489

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