Hakutulokset: Hakutulos
yhteensä 48 hakutulosta
Statistical Mechanics of Disordered Systems
This self-contained book is a graduate-level introduction for mathematicians and for physicists interested in the mathematical foundations of the field, and can be used as a …
Confidence, Likelihood, Probability
This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from …
Bootstrap Methods and their Application
Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The …
From Finite Sample to Asymptotic Methods in Statistics
Exact statistical inference may be employed in diverse fields of science and technology. As problems become more complex and sample sizes become larger, mathematical and …
Applied Asymptotics
In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available …
Design of Comparative Experiments
This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. …
Essentials Of Statistical Inference
Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this book presents the concepts and results underlying the Bayesian, frequentist and …
Markov Chains
Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate …
Fundamentals of Nonparametric Bayesian Inference
Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding …
Analysis of Multivariate and High-Dimensional Data
'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the …
Long-Range Dependence and Self-Similarity
This modern and comprehensive guide to long-range dependence and self-similarity starts with rigorous coverage of the basics, then moves on to cover more specialized, up-to-date …
The Coordinate-Free Approach to Linear Models
This book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear regression models with non-random predictors …