Markov chain Monte Carlo in practice
This book draws together contributions from authorities in the field and fills the urgent need to communicate the state of the art to a general statistical audience. Emphasis is placed on practice rather than theory, although fundamental theoretical concepts are discussed. The i…
Markov chain Monte Carlo in practice
by Spiegelhalter, D. J., Gilks, W. R., Richardson, S.
Markov chain Monte Carlo in practice
by Spiegelhalter, D. J., Gilks, W. R., Richardson, S.
This book draws together contributions from authorities in the field and fills the urgent need to communicate the state of the art to a general statistical audience. Emphasis is placed on practice rather than theory, although fundamental theoretical concepts are discussed. The i…
The two volumes LNCS 8814 and 8815 constitute the thoroughly refereed proceedings of the 11th International Conference on Image Analysis and Recognition, ICIAR 2014, held in Vilamoura, Portugal, in October 2014. The 107 revised full papers presented were carefully reviewed and s…
The two volumes LNCS 8814 and 8815 constitute the thoroughly refereed proceedings of the 11th International Conference on Image Analysis and Recognition, ICIAR 2014, held in Vilamoura, Portugal, in October 2014. The 107 revised full papers presented were carefully reviewed and s…
This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spec…
Nonparametric statistics
Annotation
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models fo…
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models fo…
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models fo…
This book discusses the problem of model choice when the statistical models are separate, also called nonnested. Chapter 1 provides an introduction, motivating examples and a general overview of the problem. Chapter 2 presents the classical or frequentist approach to the problem…
The Cox Model and Its Applications
by Wu, Hong-Dar Isaac, Nikulin, Mikhail
fromSpringerBriefs in statistics
This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control. Since Sir David Cox's pioneering work in 1972, the proportional hazards model has become the most important model in survi…
The Cox Model and Its Applications
by Wu, Hong-Dar Isaac, Nikulin, Mikhail
fromSpringerBriefs in statistics