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Linear Programming

A comprehensive, up-to-date text on linear programming. Covers all practical modeling, mathematical, geometrical, algorithmic, and;

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Advances In Non-Linear Modeling For Speech Processing

Advances in Non-Linear Modeling for Speech Processing includes advanced topics in non-linear estimation and modeling techniques along with;

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Fuel Cells

This book describes advanced research results on Modeling and Control designs for Fuel Cells and their hybrid energy systems. Filled with;

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Fuel Cells

This book describes advanced research results on Modeling and Control designs for Fuel Cells and their hybrid energy systems. Filled with;

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Introduction to Computational Earthquake Engineering

advanced analytical methods for linear and non-linear stochastic models are presented. The verification of these methods by comparing the;

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Statistical Modeling and Computation

authors address the statistical analysis and computation of various advanced models, such as generalized linear, state-space and Gaussian models;

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Advanced Linear Modeling

This book introduces several topics related to linear model theory, including: multivariate linear models, discriminant analysis, principal;

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Advanced R Statistical Programming and Data Models

data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R;

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Advanced Optimization for Process Systems Engineering

Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization;

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Linear Programming and Resource Allocation Modeling

Resource Allocation Modeling is an excellent resource for professionals looking to solve linear optimization problems, and advanced undergraduate;

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Multiphysics Modeling

introduced and supported with practical problems. More advanced topics such as creep deformation, fatigue and fracture, multiphase flow or melting;

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Linear and Nonlinear Circuits: Basic & Advanced Concepts: Volume 1

This book provides readers with the necessary background information and advanced concepts in the field of circuits, at the crossroads;

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Linear and Nonlinear Circuits: Basic & Advanced Concepts: Volume 1

This book provides readers with the necessary background information and advanced concepts in the field of circuits, at the crossroads;

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Design Analysis

engineering systems have become more complex, classic linear methods of modeling and analysis have proved inadequate, creating a need for nonlinear;

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Generalized Linear Mixed Models

Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the;

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Optimization in Engineering

This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization;

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R for Marketing Research and Analytics

the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear;

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Signal Processing for Neuroscientists

the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing;

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Statistics and Data Analysis for Financial Engineering

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary;

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Advanced Materials Modelling for Structures

This volume presents the major outcome of the IUTAM symposium on Advanced Materials Modeling for Structures . It discusses advances;

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Time Series Analysis

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear;

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Introduction to Mathematical Biology, An

For advanced undergraduate and beginning graduate courses on Modeling offered in departments of Mathematics. This text introduces a variety;

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Mathematical Economics

introduces dynamic modeling, applicable in advanced macroeconomics courses. The materials assume prerequisites in undergraduate calculus and linear;

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Non-Linear Time Series Models in Empirical Finance

Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are;

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Non-Linear Time Series Models in Empirical Finance

Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are;

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Statistical Regression Modeling with R

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;

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Statistical Regression Modeling with R

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear;

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