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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Environmental and Ecological Statistics with R

explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many;

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Environmental and Ecological Statistics with R

explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many;

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Statistical Models In Engineering

Directed at engineers, this is a detailed treatment of the use of statistical models to represent physical phenomena. The main intent;

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Statistical Methods for the Social and Behavioural Sciences

Flora provides a comprehensive survey of the major statistical procedures, along with an innovative model-based approach, teaching;

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Statistical Methods for the Social and Behavioural Sciences

Flora provides a comprehensive survey of the major statistical procedures, along with an innovative model-based approach, teaching;

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Methods of Statistical Model Estimation

algorithms used for statistical model fitting. The text presents algorithms for the estimation of a variety of regression procedures using;

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Methods of Statistical Model Estimation

algorithms used for statistical model fitting. The text presents algorithms for the estimation of a variety of regression procedures using;

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Bayesian Model Selection and Statistical Modeling

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model;

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Making Money with Statistical Arbitrage

part, I am going to introduce a semi-variance model for statistical arbitrage. The model is compared to the standard Garch model, which;

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Exactly Solved Models in Statistical Mechanics

This text explores two-dimensional lattice models in statistical mechanics and illustrates methods for their solution. Comprehensive but;

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Advanced Linear Models

This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and;

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Statistical Language Models for Information Retrieval

with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage;

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Statistical Inference

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;

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Statistical Inference

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;

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A Methodology to Model the Statistical Fracture Behavior of Acrylic Glasses for Stochastic Simulation

A statistical modelling method for simulating the fracture behaviour of acrylic glass is presented using the application case of an;

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The Two-Dimensional Ising Model

is the definitive survey of the Ising model, a mathematical model of ferromagnetism in statistical mechanics. This updated edition of the classic;

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The Balancing Act

nature of language, the role of data in building a model or theory, and the impact of the competence-performance distinction on the field;

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Building Better Econometric Models Using Cross Section and Panel Data

objective for fear of the statistical complexities involved in specifying that model. This book is intended to alleviate those anxieties by;

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Model Selection and Error Estimation in a Nutshell

true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory;

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Quantum Statistical Mechanics

in Chapters 1 and 2 are already applicable to a much broader class of model systems from statistical physics and the theory of elementary particles.;

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A Statistical Approach to Neural Networks for Pattern Recognition

that a statistical modeling approach can make valuable contributions, and further exploration for fitting MLP models is made possible via the R;

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Multivariate Analysis

. 1985 (0-471-81930-1) 324 pp. Linear Statistical Models and Related Methods With Applications to Social Research John Fox A comprehensive;

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Statistical Models For Causal Analysis

This volume provides an overview of statistical models commonly used in the causal analyses of non-experimental data in the social and;

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Statistical Thinking in Epidemiology

statistical modeling, and Amos and Mplus are used for structural equation modeling.;

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Statistical Thinking in Epidemiology

statistical modeling, and Amos and Mplus are used for structural equation modeling.;

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