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An Introduction to Envelopes. Dimension Reduction for Efficient Estimation in Multivariate Statistics
3
Written by the leading expert in the field, this text reviews the major new developments in envelope models and methods An Introduction to Envelopes provides an overview of the theory and methods of envelopes, a class of procedures for increasing eff…
Written by the leading expert in the field, this text reviews the major new developments in envelope models and methods An Introduction to Envelopes provides an overview of the theory and methods of envelopes, a class of procedures for increasing eff…
Spatial Analysis Along Networks. Statistical and Computational Methods
3
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination …
In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination …
Understanding and Applying Research Design
4
A fresh approach to bridging research design with statistical analysis While good social science requires both research design and statistical analysis, most books treat these two areas separately. Understanding and Applying Research Design introduce…
A fresh approach to bridging research design with statistical analysis While good social science requires both research design and statistical analysis, most books treat these two areas separately. Understanding and Applying Research Design introduce…
Basic and Advanced Bayesian Structural Equation Modeling. With Applications in the Medical and Behavioral Sciences
4
This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces ba…
This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces ba…
Theory of Computational Complexity
4
Praise for the First Edition «…complete, up-to-date coverage of computational complexity theory…the book promises to become the standard reference on computational complexity.» -Zentralblatt MATH A thorough revision based on advances in the field of …
Praise for the First Edition «…complete, up-to-date coverage of computational complexity theory…the book promises to become the standard reference on computational complexity.» -Zentralblatt MATH A thorough revision based on advances in the field of …
Quantile Regression. Estimation and Simulation
4
Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores …
Contains an overview of several technical topics of Quantile Regression Volume two of Quantile Regression offers an important guide for applied researchers that draws on the same example-based approach adopted for the first volume. The text explores …
ARCH Models for Financial Applications
5
Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical backgroun…
Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical backgroun…
Robustness Theory and Application
5
A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop data analytical methods, which are resistant to outlying observations in the data, while capable of detecting outl…
A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop data analytical methods, which are resistant to outlying observations in the data, while capable of detecting outl…
Decision Theory. Principles and Approaches
4
Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for …
Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for …
Bayesian Networks. An Introduction
3
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets…
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets…
The Bayesian Way: Introductory Statistics for Economists and Engineers
4
A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian …
A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian …
Nonlinear Time Series Analysis
5
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and B…
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and B…
Panel Data Econometrics with R
3
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and …
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and …
GARCH Models. Structure, Statistical Inference and Financial Applications
5
This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of…
This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of…
A General Introduction to Data Analytics
4
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-t…
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-t…
SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics
5
Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come…
Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come…
Solving Partial Differential Equation Applications with PDE2D
5
Solve engineering and scientific partial differential equation applications using the PDE2D software developed by the author Solving Partial Differential Equation Applications with PDE2D derives and solves a range of ordinary and partial differential…
Solve engineering and scientific partial differential equation applications using the PDE2D software developed by the author Solving Partial Differential Equation Applications with PDE2D derives and solves a range of ordinary and partial differential…
INFORMS ABOK
5
Standardizes the definition and framework of analytics ABOK stands for Analytics Body of Knowledge. Based on the authors’ definition of analytics—which is “a process by which a team of people helps an organization make better decisions (the objective…
Standardizes the definition and framework of analytics ABOK stands for Analytics Body of Knowledge. Based on the authors’ definition of analytics—which is “a process by which a team of people helps an organization make better decisions (the objective…
Mathematical Statistics with Resampling and R
4
This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis …
This thoroughly updated second edition combines the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis …
Statistical Inference for Piecewise-deterministic Markov Processes
4
Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance… Such processes are defined by a deterministic motion punctuated by random jumps at …
Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance… Such processes are defined by a deterministic motion punctuated by random jumps at …

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