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Exploring Statistics
This book provides an overview of the commonly used statistical methodology. It is intended to enable professionals such as medical doctors, engineers, business executives, laboratory technicians, school teachers, and others to understand the basics of statistical thought through self study.
Choice-Based Conjoint Analysis
Conjoint analysis (CA) and discrete choice experimentation (DCE) are tools used in marketing, economics, transportation, health, tourism, and other areas to develop and modify products, services, policies, and programs, specifically ones that can be described in terms of attributes. A specific combination of attributes is called a concept profile.
Block Designs
Combinatorial mathematicians and statisticians have made a wide range of contributions to the development of block designs, and this book brings together much of that work. The designs developed for a specific problem are used in a variety of different settings. Applications include controlled sampling, randomized response, validation and valuation studies, intercropping experiments, brand cross-effect designs, lotto and tournaments.The intra- and inter- block, nonparametric and covariance analysis are discussed for general block designs, and the concepts of connectedness, orthogonality, and all types of balances in designs are carefully summarized. Readers are also introduced to the designs currently playing a prominent role in the field: alpha designs, trend-free designs, balanced treatment-control designs, nearest neighbor designs, and nested designs.This book provides the important background results required by researchers in block designs and related areas and prepares them for more complex research on the subject.
Constructions and Combinatorial Problems in Design of Experiments
This book presents first full-length treatment of the subject examines orthogonal Latin squares, incomplete block design, tactical configuration, partial geometry, symmetrical and unequal-block arrangements, many other areas of interest. Abundant explanations, examples, references.
The Inverse Gaussian Distribution
This monograph is a compilation of research on the inverse Gaussian distribution. It emphasizes the presentation of the statistical properties, methods, and applications of the two-parameter inverse Gaussian family of distribution. It is useful to statisticians and users of statistical distribution.
Problems in Probability Theory, Mathematical Statistics and Theory of Random Functions
Approximately 1,000 problems — with answers and solutions included at the back of the book — illustrate such topics as random events, random variables, limit theorems, Markov processes, and much more.
Nonlinear Lp-Norm Estimation
Complete with valuable FORTRAN programs that help solve nondifferentiable nonlinear LtandLo.-norm estimation problems, this important reference/text extensively delineates ahistory of Lp-norm estimation. It examines the nonlinear Lp-norm estimation problem that isa viable alternative to least squares estimation problems where the underlying errordistribution is nonnormal, i.e., non-Gaussian.Nonlinear LrNorm Estimation addresses both computational and statistical aspects ofLp-norm estimation problems to bridge the gap between these two fields . . . contains 70useful illustrations ... discusses linear Lp-norm as well as nonlinear Lt, Lo., and Lp-normestimation problems . . . provides all appro...
Mathematical Foundations of Quantum Statistics
A coherent, well-organized look at the basis of quantum statistics’ computational methods, the determination of the mean values of occupation numbers, the foundations of the statistics of photons and material particles, thermodynamics.
Computational Methods in Statistics and Econometrics
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.
Stochastic Models for Carcinogenesis
An up-to-date survey of mathematical models of carcinogenesis, providing the most recent findings of cancer biology as evidence of the models, as well as extensive bibliographies of cancer biology and in-depth mathematical analyses for each of the models. May be used as a reference for biostaticians, biometricians, mathematical and molecular biologists, applied mathematicians, oncologists, cancer and toxicology researchers, environmental scientists, and graduate students in these fields.
