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Bayesian Non- and Semi-parametric Methods and Applications

This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative;

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Statistical Paradigms

semi-parametric, frequentist and Bayesian encompassing both theoretical advances and emerging applications in a variety of scientific;

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BAYESIAN INFERENCE

and outliers; hierarchical, multivariate and non-parametric models; asymptotics; computations and Monte Carlo methods; and Bayesian;

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Essential Bayesian Models

of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric;

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Identification Methods for Structural Health Monitoring

overview on fundamental methods, introductory concepts are provided on the general framework of time and frequency domain, parametric and non;

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Bayesian Thinking, Modeling and Computation

point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to;

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Maximum Entropy and Bayesian Methods

This volume contains the proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, held in Sante Fe, New;

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Non Parametric and Semi Parametric Estimation of the Engel Curves

Non parametric specification has become vital recipe in estimation of the Engel Curves. This book provide an introduction to the method and;

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Bayesian Time Series Models

introduces switching, multi-object, non-parametric and agent-based models in a variety of application environments. It demonstrates that the basic;

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Handbook of Missing Data Methodology

cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular;

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Duration Analysis

influencing factors on unemployment duration. A non-parametric analysis method, the Kaplan-Meier-estimation as well as parametric estimations are;

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Multivariate Survival Analysis and Competing Risks

inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case;

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Multivariate Survival Analysis and Competing Risks

inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case;

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Asymptotics, Nonparametrics, and Time Series

Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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Analysis of Doubly Truncated Data

the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can;

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Theory & Methods of Computational Vibronic Spectroscopy

This book discusses semi-empirical approaches and parametric methods developed for modelling molecular vibronic spectra. These methods;

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Asymptotics, Nonparametrics, and Time Series

"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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Bayesian Estimation and Tracking

for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and;

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Bayesian Theory and Methods with Applications

Bayesian methods are growing more and more popular, finding new practical applications in the fields of health sciences, engineering;

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Introduction to Bayesian Estimation and Copula Models of Dependence

parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the;

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Generalized Linear Models

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective;

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Bayesian Inference and Maximum Entropy Methods in Science and Engineering

, thermodynamics (equilibrium and non-equilibrium), particle physics, plasma physics, quantum mechanics, robotics, and the social sciences. Bayesian;

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Nonparametric Statistics for Applied Research

textbook on non-parametric statistics for applied research. The authors propose to use a realistic yet mostly fictional situation and series;

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International Symposia in Economic Theory and Econometrics

selection models, (ii) nonparametric and semi-parametric approaches to qualitative and sample selection models, and (iii) nonlinear estimation;

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Nonlinear Statistical Modeling

selection models, (ii) nonparametric and semi-parametric approaches to qualitative and sample selection models, and (iii) nonlinear estimation;

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Bayesian Methods in Pharmaceutical Research

conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to;

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Advances and Challenges in Parametric and Semi-Parametric Analysis for Correlated Data: Proceedings of the 2015 International Symposium in Statistics

Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St;

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