Offers a comprehensive review of introductory notions in statistics such as variable transformation, statistical inference, hypothesis testing, and regression analysis Illuminates the fundamental topic of uniform random number generation Demonstrates the generation of diverse continuous- and discrete-type random draws Explains the inverse transform method for use with Laplace, Cauchy, and other distributions Details random draw approaches for multivariate distributions Describes random number generation via importance and rejection sampling methods and the Metropolis-Hastings algorithm Outlines nonparametric methods for finding the difference between two sample means, including logistic and Cauchy score tests and Fisher's randomization test Considers Monte Carlo and nonparametric methods for testing correlation and regression coefficients and establishing the independence of two samples
Reflecting current technological capacities and analytical trends, Computational Methods in Statistics and Econometrics showcases Monte Carlo and nonparametric statistical methods for models, simulations, analyses, and interpretations of statistical and econometric data. The author explores applications of Monte Carlo methods in Bayesian estimation, state space modeling, and bias correction of ordinary least squares in autoregressive models. The book offers straightforward explanations of mathematical concepts, hundreds of figures and tables, and a range of empirical examples. A CD-ROM packaged with the book contains all of the source codes used in the text.
Table of Contents
Elements of Statistics
MONTE CARLO STATISTICAL METHODS
Random Number Generation I
Random Number Generation II
SELECTED APPLICATIONS OF MONTE CARLO METHODS
Bias Correction of OLSE in AE Models
State Space Modeling
NONPARAMETRIC STATISTICAL METHODS
Difference Between Two-Sample Means
Independence Between Two Samples
Source Code Index
"…this collection brings together the fundamentals, process engineering, and pharmaceutical applications of supercritical fluid technologies."
"This book is easy to read; it is written clearly and correctly…This book will be very useful for researchers, applied statisticians, and PhD students."
-Journal of Applied Statistics
"The book has an attractive layoutand includes a useful companion CD-ROM displaying all source codes used in the book Fortran 77 and sometimes in C Languages."
Technometrics, November 2005