10/31/2011

Modeling Groundwater Flow and Pollution (Theory and Applications of Transport in Porous Media) Review

Modeling Groundwater Flow and Pollution (Theory and Applications of Transport in Porous Media)
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This book presents theory and practice of groundwater and pollution flow simulation. It has thirteen chapters. Its first seven chapters contain theoretical information related to general porous media fluid flow along with mathematical models for flow in aquifers, seawater intrusion, unsaturated flow, and groundwater pollution. The last six chapters present numerical methods for solving the models developed in the theoretical chapters. There are special emphases for finite difference and finite element methods with BASIC`s programs for steady and unsteady pressure equations. It also contains chapters with BASIC's programs for convection-diffusion equations. This book is self-contained and it explains the most important deterministic techniques to simulate fluid flow in groundwater and pollution problems. It is a classic book in the subject and it deserves five starts.

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Soil Physics with HYDRUS: Modeling and Applications Review

Soil Physics with HYDRUS: Modeling and Applications
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I (my employer actually) spent over $3000 (including hotel and per diem) to take the Hydrus 1D/2D/3D course; I could have gotten just as much information, actually more, from this book. Well worth the price. I'd recommend this book long before you take their 3-day course.

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Numerical models have become much more efficient, making their application to problems increasingly widespread. User-friendly interfaces make the setup of a model much easier and more intuitive while increased computer speed can solve difficult problems in a matter of minutes. Co-authored by the software's creator, Dr. Jirka Šimůnek, Soil Physics with HYDRUS: Modeling and Applications demonstrates one- and two-dimensional simulations and computer animations of numerical models using the HYDRUS software. Classroom-tested at the University of Georgia by Dr. David Radcliffe, this volume includes numerous examples and homework problems. It provides students with access to the HYDRUS-1D program as well as the Rosseta Module, which contains large volumes of information on the hydraulic properties of soils. The authors use HYDRUS-1D for problems that demonstrate infiltration, evaporation, and percolation of water through soils of different textures and layered soils. They also use it to show heat flow and solute transport in these systems, including the effect of physical and chemical nonequilibrium conditions. The book includes examples of two-dimensional flow in fields, hillslopes, boreholes, and capillary fringes using HYDRUS (2D/3D). It demonstrates the use of two other software packages, RETC and STANMOD, that complement the HYDRUS series. Hands-on use of the windows-based codes has proven extremely effective when learning the principles of water and solute movement, even for users with very little direct knowledge of soil physics and related disciplines and with limited mathematical expertise. Suitable for teaching an undergraduate or lower level graduate course in soil physics or vadose zone hydrology, the text can also be used for self-study on how to use the HYDRUS models.With the information in this book,you can run models for different scenarios and with different parameters, andthus gain a better understanding of the physics of water flow and contaminant transport.

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Digital Terrain Modeling: Principles and Methodology Review

Digital Terrain Modeling: Principles and Methodology
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This is an excellent text providing a complete overview of the principles of digital terrain modeling. The reader will obtain a thorough understanding of terrain modeling from data sources and acquisition methods, to surface modeling. It provides insight into the methodology of creating a triangular irregular network, or TIN, model. It also provides insight into contouring, aspect angles, slope, drains (hydrological interpretation), etc. It also provides an excellent discussion of error and accuracy and how each are affected in the different phases of terrain data processing, from source/acquisition to final digital elevation model. Many mathematical methods are presented. I would recommend this text to anyone wishing to obtain an understanding of the processes and methodologies behind digital terrain modeling. The only reason that I did not give this text a 5-star rating is that I would have liked to have seen a more in-depth examination of efficient data processing algorithms with examples. But this is a minor deficiency and I would not let this keep someone from purchasing this text if he/she wishes to obtain a full understanded of digital terrain modeling. The References section is also quite useful pointing to many other interesting sources of information to further your knowledge.

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Written by experts, Digital Terrain Modeling: Principles and Methodology provides comprehensive coverage of recent developments in the field. The topics include terrain analysis, sampling strategy, acquisition methodology, surface modeling principles, triangulation algorithms, interpolation techniques, on-line and off-line quality control in data acquisition, DTM accuracy assessment and mathematical models for DTM accuracy prediction, multi-scale representation, data management, contouring, visual analysis (or visualization), the derivation of various types of terrain parameters, and future development and applications.

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10/30/2011

Operational Risk : Modeling Analytics (Wiley Series in Probability and Statistics) Review

Operational Risk : Modeling Analytics (Wiley Series in Probability and Statistics)
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I train and consult bankers in credit and operational risk modeling for a living. I mention this because I think I have a decent feel for the pedagogy necessary for helping practitioners grasp the step-by-step application of these often highly theoretical concepts. Not all of us are rocket-scientists from birth and even though I have a quantitative PhD from Princeton, my often slow brain likes having things explained in simple terms. Panjer's book does this beautifully.
He has found the perfect balance between rigor and application--both in the exposition and scope of the book. He also includes examples of every concept that are easy to follow, replicate and extend. Moreover, Panjer takes you right to the edge of where advanced modeling of operational risk is at present. For example, he discusses EVT, copulas, infinite-mean models, kernel smoothing, robust methods, Bayesian methods, aggregation principles and compound processes as well as model selection--all of which characterize the current state of operational risk modeling and research. Indeed, beyond these points of technical modeling, most researchers (even mathematicians) are starting to agree that the returns are greatly diminishing and better qualitative/quantitative mixtures need to be developed (see Neslehova, et.al. Journal of Operational Risk, Spring, (2006)).
"Weak" spots in the book relate, for example, to how it fails to base itself firmly within the current operational risk literature. This is without loss of generality during this the infancy of operational risk modeling but I believe subsequent editions should address (at least to comment on) the growing number of papers popping up on websites and in trade journals. On the other hand, since I am not a statistician, I appreciated the author's references within that field as many of the topics are not part of the standard statistics canon. Finally, the book does not discuss operational risk management though, buying a book entitled "Operational Risk Modeling", I am not sure whether or why anyone would expect it to.
If this book were twice the price (such as for RiskBooks) I would still be happy with my purchase.

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Discover how to optimize business strategies from both qualitative and quantitative points of viewOperational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors.Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts.Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science.In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features:* Ample exercises to further elucidate the concepts in the text* Definitive coverage of distribution functions and related concepts* Models for the size of losses* Models for frequency of loss* Aggregate loss modeling* Extreme value modeling* Dependency modeling using copulas* Statistical methods in model selection and calibrationAssuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.

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Vehicle Propulsion Systems: Introduction to Modeling and Optimization Review

Vehicle Propulsion Systems: Introduction to Modeling and Optimization
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This is by far the best book on the topic I have found. If you plan to design or model any vehicle, but in particular a hybrid or electric vehicle, I recommend you own this book.
Specifically, a large portion of the mathematical models required for design-level calculations are available directly from the text. The text is very concise, making good use of external citations to remain thorough. Finally, the optimization case studies are very helpful in understanding hybrid design goals.
Highly Recommended for engineers and students with some experience in vehicles.

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The authors of this text have written a comprehensive introduction to the modeling and optimization problems encountered when designing new propulsion systems for passenger cars. It is intended for persons interested in the analysis and optimization of vehicle propulsion systems. Its focus is on the control-oriented mathematical description of the physical processes and on the model-based optimization of the system structure and of the supervisory control algorithms.

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Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design (The Morgan Kaufmann Series in Data Management Systems) Review

Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design (The Morgan Kaufmann Series in Data Management Systems)
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I used to think that the best book one could read in order to really learn the science and the art of data modeling was Conceptual Schema and Relational Database Design. I used to think that, that is, until I read the Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design.
Originally intended to be the third edition of the "Conceptual Schema" text, this new book offers the same definitive information as its predecessor with a large amount of added information. So much more information, in fact, that the book has grown by roughly 250 pages (and that is not counting the additional appendices available online)!
The text begins with a warning. Halpin refers to the 1999 Mars Climate Orbiter accident in which a simple conversion from imperial to metric units caused the $125 million dollar craft to be destroyed. "Data itself is not enough," Halpin cautions, "what we really need is information."
And so begins the introduction of the most accurate way to model data: Object-Role Modeling (ORM). For those of you not familiar with the technique, ORM is a fact-based approach to modeling that not only captures the semantics of data - in the native language of the subject matter expert - but it also captures many rules, offers an embedded process to ensure the model is correct, and completely maps to any fully normalized logical notation (e.g. ER, UML).
Let me re-phrase the above, because it is extremely important. With ORM, you can:
a) Talk to subject matter experts in their language and in terms they can understand - you don't have to define tuples, entities, foreign keys, attributes, and all that other nonsense;
b) Verify that the model is correct by using a robust method (ORM is more than just a notation) filled with quality checks;
c) Document more rules - intrinsic in ORM's rich constraint language - to ensure the resulting system captures all of the rules crucial to the data being modeled;
d) And finally map the conceptual schema into a fully normalized database structure.
If you are new to data modeling, this is the first book you should read. This book will detail the concepts you need to know in order to analyze and create correct data schemas - regards less of which notation or tool you end up using (although both Halpin and myself have an opinion on which to choose). In other words, use this book to learn how to think about the problem. In so doing, you can easily map the concepts into the more trendy notations and methodologies, if you must.
If you are a modeling veteran, you should also read this book. In so doing, I'll wager that you will discover you have been making correct models the hard way all these years. You'll see, in exquisitely clear detail, the inherent problems in the other techniques (such as ER and UML). Further, if you are open minded enough to temporarily forget what you have learned so far, you too can learn how to think correctly about data modeling problems - and their solutions.
Now that I (hopefully) have convinced you to give this book a try, I'll detail the contents.
The first two chapters are introductory material intended to give the reader a sneak peek at what is coming up. In them, Halpin provides a brief overview of three techniques (ORM, ER, and UML) and discusses the pros and cons of each. With Halpin's witty, clear, concise writing style, and the clear evidence of problems with the other techniques, I expect the reader to be fully motivated to read on and delve into the more rigid explanation of the technique.
Don't let the academic nature of the topics intimidate you; Halpin uses easy-to-follow examples and well-tuned prose to inform academics and industry professionals alike. Just because the method is academically sound (it's firmly rooted in predicate calculus and set theory) doesn't mean that the material has to be boring. In fact, the tone of the text and the sample data provided in the examples will imply to the reader Halpin's distinct sense of humor that actually makes database theory fun to read.
The next five chapters form the definitive explanation of the ORM technique. This material is solid. Written, adjusted, instructed, and adjusted again over the past couple of decades, Halpin once again delivers this material in an optimal way. Those of you familiar with Halpin's "Conceptual Schema" text will be glad (even, as I was, surprised) to see that this material is even more solid than his past explanations of the technique.
The latter half of the book has, perhaps, changed the most from the "Conceptual Schema" text. In it, Halpin details Entity Relationship (ER) modeling, relational implementations (mapping ORM into tables and columns), the Unified Modeling Language (UML), and relational languages (SQL) - all from the ORM perspective you have just learned.
Further, these chapters are fascinating. I expect the reader to both understand how to map ORM concepts into the vendor-controlled world of information systems and to wonder in amazement at how techniques with so many fundamental problems have become "industry standards".
Finally, Halpin closes the text with more advanced chapters on schema transformations (equivalent models) and other design methods, issues and trends.
All in all, this book is great. It instructs in the fundamentals and them maps those orthogonal concepts into the current trends. Along the way, the book is filled with real world examples, easy to follow explanations, and sample problems for the reader to work on (in fact, I expect that this book, like its predecessor, will be used internationally as secondary/post-secondary class texts).
And finally, as someone who regularly attempts to explain technical concepts via writing, I am truly impressed - awed, even - with the style and ease with which Halpin delivers this content.
Thus, in summary, I have to say that this book is a great explanation of a robust technique; data architects and information systems analysts/designers need to own this book.

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Information Modeling and Relational Databases provides an introduction to ORM (Object Role Modeling)-and much more.In fact, it's the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design.
Inside, ORM authority Terry Halpin blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible.Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model and then, where needed, abstract ER and UML models from it.This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives. * The most in-depth coverage of Object Role Modeling available anywhere-written by a pioneer in the development of ORM.* Provides additional coverage of Entity Relationship (ER) modeling and the Unified Modeling Language-all from an ORM perspective.* Intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, instructors, managers, and programmers.* Explains and illustrates required concepts from mathematics and set theory.* Via a companion Web site, provides answers to exercises, appendices covering the history of computer generations, subtype matrices, and advanced SQL queries, and links to downloadable ORM tools.

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10/29/2011

Building Information Modeling: Planning and Managing Construction Projects with 4D CAD and Simulations (McGraw-Hill Construction Series) (Set 2) Review

Building Information Modeling: Planning and Managing Construction Projects with 4D CAD and Simulations (McGraw-Hill Construction Series) (Set 2)
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Well organized, well written. Provides information about model composition which most books on this subject do not include. Very informative. Organizations looking to move down the BIM/VDC path should definitely take the time to read as they will learn a great deal about the process changes needed to effectively utilize 3D models in their workflow.

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Improve Planningand Management on Any Construction Project with Powerful BIM Tools

Building information modeling (BIM) integrates 3D drawings and 4D animations to dramatically improve the communication, coordination, and planning of construction projects, while reducing risks, errors, and costs. Building Information Modeling is an in-depth resource that shows architects and building professionals how to capitalize on BIM concepts, tools, and techniques for their own building projects.
An in-depth explanation of BIM concepts, tools, and techniques
Guidance on applying BIM to new and retrofit construction projects
More than 200 photos, charts, diagrams, and details of the BIM process
Detailed case studies

Inside this Comprehensive Guide to BIM Technology
Background: • The Setting for BIM • Current Practice • Legal Considerations Building Information Modeling: • BIM Concepts • BIM Planning • BIM ImplementationSoftware Tools: • Modeling Tools • Model Production • Model Analysis • Specific SoftwareOptionsLearning BIM: • Learning Methods • Skill Sets • The LearnersCase Studies

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Process Control: Modeling, Design and Simulation Review

Process Control: Modeling, Design and Simulation
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This book successfully teaches how to analyze dynamic chemical processes and develop automatic control strategies to operate them safely and economically. Rather than simply present theory topics and develop analytical solutions, this textbook uses "interactive learning" through computer-based simulation exercises, employing for this the very popular "Matlab" engineering software package, and the "Simulink" block-diagram simulation environment. Introductions to both "Matlab" and "Simulink" are included in the book.
Each chapter of the book is followed by a series of "learning modules" that serve several purposes: some focus on software tools, while others focus on particular control problems.
An introduction to process control and instrumentation is presented in chapter 1. The development and use of models is very important in control systems engineering, and fundamentals models are developed in chapter 2, including the steady-state solution and linearization to form steady-state models. Chapter 3 focuses on the dynamic behavior of linear systems, starting with state space models and then covering transfer function-based models in detail. Chapter 4 covers the development of empirical models, including continuous and discrete transfer function models.
Chapter 5 provides a detailed introduction to feedback control, developing the basics of feedback systems, PID controllers, and methods of analyzing closed-loop stability. Chapter 6 presents methods for controller tuning. Frequency response analysis techniques, important for determining control system robustness, are presented in chapter 7.
Model-based control leads to improved control loop performance, and one of the clearest model-based techniques (Internal Model Control o IMC) is presented in chapter 8. The PID controller remains the most widely used controller in industry, so chapter 9 is very valuable since it shows how to convert internal model controllers to classical feedback PID controllers.
Chapter 10 develops two widely used control strategies: Cascade and feed-forward control. Chapter 11 presents auto-tuning and gain scheduling, two methods used to deal with poor performance due to changing operating conditions and poor tuned control loops. The phenomenon of reset windup and the development of anti-reset windup strategies are also presented in this chapter.
Chapter 12 presents the split-range, selective, and override control strategies, which are used when we need the control loop to be able of switching between manipulated inputs or select from several measured outputs. Chapter 13 deals with the effect of control loops interactions, while the design of multivariable controllers is developed in chapter 14.
Chapter 15 presents the challenging tasks encountered when developing Plant-wide optimization and control schemes. Chapter 16 presents the most widely applied advanced control strategy: Model Predictive Control (MPC).
Even though the book is designed for Chemical Engineering students, I truly believe that this text would also be suitable for industrial practitioners and students in mechanical, nuclear, industrial, and electrical engineering. I am an Industrial Practitioner of Process Measurement & Control who has been working in the Process Industries for more than 16 years as an Automation, Instrumentation, Process Safety and Process Control Engineer. My academic background is in electrical and electronics engineering (I am an Electronic Engineer), not in chemical engineering as might be the case of the usual reader of this book, but working in the Oil & Gas Industry all this time, I have been dealing with Chemical-Process Control issues in a day-to-day basics. I found this book to be a very useful reference and refresher to gain a better understanding of Modern Process Control Applications.
If you are a practitioner of Process Control you may want to consider also "Instrument Engineers' Handbook, Fourth Edition, Volume Two: Process Control and optimization" by Bela Liptak, for its practical and comprehensive coverage of Process Control.

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Process Control: Modeling, Design, and Simulation is the first complete introduction to process control that fully integrates software tools-helping you master critical techniques hands-on, using MATLAB-based computer simulations. Author B. Wayne Bequette includes process control diagrams, dynamic modeling, feedback control, frequency response analysis techniques, control loop tuning, and start-to-finish chemical process control case studies.

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Data Modeling Fundamentals: A Practical Guide for IT Professionals Review

Data Modeling Fundamentals: A Practical Guide for IT Professionals
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This is a must have book that a Data Modeler will want to keep for a long time.
It discusses every aspect of the Data Modeling discipline.
Does not matter what DBMS you use the information in this book is priceless.


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The purpose of this book is to provide a practical approach for IT professionals to acquire the necessary knowledge and expertise in data modeling to function effectively. It begins with an overview of basic data modeling concepts, introduces the methods and techniques, provides a comprehensive case study to present the details of the data model components, covers the implementation of the data model with emphasis on quality components, and concludes with a presentation of a realistic approach to data modeling. It clearly describes how a generic data model is created to represent truly the enterprise information requirements.

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10/28/2011

Dynamic Modeling and Control of Engineering Systems Review

Dynamic Modeling and Control of Engineering Systems
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A great introduction to control theory.However, it would help if you know something about differential equations. I read Ogata's book on control (over 900 pages) from cover to cover twice and still could not figure out exactly what state variables are. This book explains things very well but you do need to do the problems at the end of each chapter. The use of "free-body" diagrams is a great idea.Ogata's book is great for explaining a lot of the details but this book explains the important things in a concise but easy to understand manner. I now finally understand how to draw a system diagram by starting from the inputs for each separate system. Everything is brought together -- system diagrams,transfer functions,state variables,the purpose for LaPlace transforms,and input-output models. This is not a book about control theory and it is covered in only the last two chapters but if you are taking, or going to take, a course in control theory,read this book first. It will save you a lot of frustration and bewilderment.

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This textbook is ideal for an undergraduate course in Engineering System Dynamics and Controls. It is intended to provide the reader with a thorough understanding of the process of creating mathematical (and computer-based) models of physical systems. The material is restricted to lumped parameter models, which are those models in which time is the only independent variable. It assumes a basic knowledge of engineering mechanics and ordinary differential equations. The new edition has expanded topical coverage and many more new examples and exercises.

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Antenna and EM Modeling with Matlab Review

Antenna and EM Modeling with Matlab
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The book is well written but not very extensive. It points to the applications right from the beggining and it is certainly of great value for students and engineers already engagged with Balanis Book on antenna theory. I strongly recommend Makarov's book for training students with a strong numerical methods background on electromagnetics, as a prerequisite before taking the course.

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An accessible and practical tool for effective antenna designDue to the rapid development of wireless communications, the modeling of radiation and scattering is becoming more important in the design of antennas. Consequently, it is increasingly important for antenna designers and students of antenna design to have a comprehensive simulation tool.Sergey Makarov's text utilizes the widely used Matlab(r) software, which offers a more flexible and affordable alternative to other antenna and electromagnetic modeling tools currently available. After providing the basic background in electromagnetic theory necessary to utilize the software, the author describes the benefits and many practical uses of the Matlab package. The text demonstrates how Matlab solves basic radiation/scattering antenna problems in structures that range from simple dipoles to patch antennas and patch antenna arrays. Specialized antenna types like fractal antennas and frequency selective surfaces are considered as well. Finally, the text introduces Matlab applications to more advanced problems such as broadband and loaded antennas, UWB pulse antennas, and microstrip antenna arrays.For students and professionals in the field of antenna design, Antenna and EM Modeling with Matlab:* Strikes an important balance between text and programming manual* Provides numerous examples on how to calculate important antenna/target parameters* Provides means for modifying existing codes for various individual projects* Includes a CD-ROM with Matlab codes and antenna geometry files
The present MATLAB codes are only supported by MATLAB 5 and 6 (up to 2004).

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Modeling a Likeness in Clay (Practical Craft Books) Review

Modeling a Likeness in Clay (Practical Craft Books)
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Mrs Grubbs has lots of talent, being a pedagogue is not the least of them. As she shares her technique with the reader, every step is thoroughly illustrated and commented. Numerous examples of specific situations are shown in detail along with the sculptor's comments.
The first sections establishes the general principles governing the achievement of a likeness, going step by step through the measurements and accurate mass and volume placement, with practical demonstration.
Further sections detail the progress of the work, and the end sections are practical examples of different portrait renditions of models which vary in age, sex, ethnic features, all being taken from actual work carried out by the artist.
As Mrs Grubbs favors kiln-firing of her clay portraits, readers interested in this technique will also find very valuable information, and will learn how to properly prepare a portrait for this purpose.

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10/27/2011

Mathematics in Nature: Modeling Patterns in the Natural World Review

Mathematics in Nature: Modeling Patterns in the Natural World
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For those of us who admire nature and see it as a product of processes both beautiful and rational, Adam's book is the perfect bedside long-termer for anyone more than casually interested in math or the intricate patterns in nature.
This book is chock full of ponderous examples of mathematical simplicity and complexity in nature, and reading it I was constantly reading only one topic and then putting the book down for days to think about and tinker with the question myself.
Good pictures, solid math (I prefer clean, modelistic equations to numerical approximations anyday), and a charming, conversational writing style make this book highly readable and highly inspiring in the way it makes you reexamine your perception of nature as unintegrated or inelegant. The very repetition of mathematical themes throughout nature - such as the omnipresent Golden Ration - proves otherwise.
For me, this is staying on my "constantly referenced" shelf.

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A Developer's Guide to Data Modeling for SQL Server: Covering SQL Server 2005 and 2008 Review

A Developer's Guide to Data Modeling for SQL Server: Covering SQL Server 2005 and 2008
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"A Developers Guide to Data Modeling for SQL Server" is billed to be for all level of data modelling development, however it is written in a style targeted to beginning novice developers only, and never progresses very far beyond demonstrating the fundamentals of Data Modeling. For novices, it is extremely good resource, explaining highly technical concepts in an easy to understand non-technical language. However, for the experienced developer, it would be best to look elsewhere.

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Modeling with Data: Tools and Techniques for Scientific Computing Review

Modeling with Data: Tools and Techniques for Scientific Computing
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Klemens teaches how to tame and understand a dataset the way it should be done: in C. Invest some time in this excellent book full of gentle humor and respect for the reader's intelligence. The payoffs will be immense. The best resource (a full set of programs used in the book) accompanying this book is available for FREE(!) on Klemens's website!

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Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results.

Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date.

Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.


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10/26/2011

Principles and Practice of Structural Equation Modeling Review

Principles and Practice of Structural Equation Modeling
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Rex Kline easy writing style will take you through step-by-step in one of the most comprehesive yet accessible introductions to multivariate analysis and structural equation modeling. After outlining the building blocks of SEM (multiple regression, path analysis, and factor analysis), Kline gets the reader ready to tackle popular SEM software with examples for AMOS, LISREL and EQS. There is also a great chapter on what NOT to do with this often misused technique. For a preview, see Kline's article in the Journal of Clinical Psychology (1991), Latent variable path analysis: A beginner's tour guide. This book is an excellent read, and a must have for researchers and statisticians.

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Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation, and pitfalls of structural equation modeling (SEM) in the social sciences. This is an accessible volume which covers introductory techniques, including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods, such as the evaluation of nonlinear effects, the analysis of means in covariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the author offers clear instructions on the preparation and screening of data, common mistakes to avoid, and features of widely used software programs (Amos, EQS, and LISREL). Readers will acquire the skills necessary to begin to use SEM in their own research and to interpret and critique the use of the method by others.

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Mathematical Modeling in the Environment (Mathematical Association of America Textbooks) Review

Mathematical Modeling in the Environment (Mathematical Association of America Textbooks)
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I used this as the text for a course in Mathematical Models and Applications, and I do not recommend that other teachers use it. I spent an average of somewhere between 5 and 10 hours per presentation (the class met three times per week) and that wasn't enough. The book's background information on groundwater, air quality, and hazardous materials was enough to get me started, but I found I had to spend a lot of time learning environmental information not covered in the book. I also spent an incredible amount of time constructing homework and exam problems. The book really isn't all that bad, and can serve well as an introduction to the subject for a college teacher who wants to learn something about this, but as a primary text it requires way too much preparation time on the part of the teacher, especially at an institution with a heavy teaching load. (I had an 11-hour teaching load.) By the way, the hazardous materials program used by the authors of the text, ARCHIE, is being phased out, and information about it is hard to obtain. (It doesn't even run on some modern computer systems.) Its replacement, CAMEO, currently has serious installation problems. It isn't all that hard to get around them on your own computer, but installation on computers in a lab may be a different story. Dave Trautman, The Citadel, Department of Mathematics and Computer Science

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This book has a dual objective: first to introduce the reader to some of the most important and widespread environmental issues of the day; and second to illustrate the vital role played by mathematical models in investigating these issues. The subjects covered are ground water contamination, air pollution, and hazardous materials emergencies. These issues are presented in their full real-world context and are used to develop important classical mathematical themes. The emphasis throughout is on fundamental principles and concepts, not on achieving technical mastery of state-of-the-art models.

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