Statistical Multisource-Multitarget Information Fusion Review

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(More customer reviews)Mahler's book is an outstanding effort to lay down a unified framework for data and information fusion. Admittedly it is a difficult book, very comprehensive, probably too applied for mathematicians and too mathematical for engineers. But it contains a very well thought out and technical vision of what it takes to process vast amounts of data, especially data of disparate types, and extract useful and correct information. Written by someone who has worked in the field for many years, I believe this book is a guide to the future of data and information fusion.

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Longitudinal Data Analysis (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) Review

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(More customer reviews)First of all, this isn't really a textbook. It's more of an encyclopedia-textbook hybrid. You won't find proofs of theorems or (many) fully worked examples, however you'll get thorough descriptions of methods, their current status and their full history. Each section is written by one to four of the 32 contributors of the text, with each contributor writing on his/her expertise. Contributors include: Fitzmaurice, Verbeke, Molenberghs, Brumback, Carroll, Diggle, Little, Muller, Robins, among others.
If a section is not thorough enough for your liking, the authors refer you to a plethora of relevant papers for just about everything that is stated in the text. This makes it incredibly easy to investigate further into a given topic. Furthermore, the references are fairly current, with some sections including references up to the year 2007.
As I eluded to before, not only does each chapter cover different methodologies for analyzing longitudinal data, but also includes a history of research regarding a method -- what we used before those methods were introduced, why they were lacking, how the current methods address some of those problems, and what directions exist for further research. This gives the reader a picture of how the field has evolved and adapted to problems that longitudinal data analyses presents researchers. Some may find this uninteresting, but to see the historical research process for some of these methods, in my opinion, illustrates how the field has reached the point it is today and more generally, how research progresses in the real world.
The non-parametric/semi-parametric regression methods and missing data sections are especially appealing for I am unaware of any other source which compiles all current research in these areas in one volume.
As I say in the title of my review, this is akin to a 'travel-guide.' For example you won't find a derivation of GEE in this text, but you'll find what they are, why they were introduced, what they replaced, why we bother using them, what properties they have, what extensions researchers have come up with, and what we still don't know...and most importantly, you'll be directed to where you can find the derivations of all of these. Thus it won't be your final stop in researching any methodology for longitudinal data, but it most likely turn into your first.
This text is a great picture of what can be done with this series of texts (Handbooks of Modern Statistical Methods). I look forward to future installments.

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Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data.
After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines.
Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

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Architectural Graphic Standards for Residential Construction (Ramsey/Sleeper Architectural Graphic Standards Series) Review

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(More customer reviews)Whether you're designing a new residential structure or renovating an existing one, this book is a must-have. Found exactly what I needed, including a reference to the building code--what a time-saver! Also have the CD-ROM version so that I could have the details to work with(Architectural Graphic Standards for Residential Construction 1.0 CD-ROM (Ramsey/Sleeper Architectural Graphic Standards Series)
And, as I delve deeper into Building Information Modeling (BIM), I can really appreciate the organization. BIM needs you to think in terms of building elements, and that is exactly how this book is organized.

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Applied Equity Analysis: Stock Valuation Techniques for Wall Street Professionals Review

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(More customer reviews)James English's "Applied Equity Analysis" is a how-to manual on evaluating stocks based on his 20 years of experience at JP Morgan. The book is very well-written and readable since the author employs plain english (no pun intended) to make his three major points: 1) accounting numbers--while by no means perfect--are excellent tools in evaluating stocks, 2) accounting-based stock valuation is superior to (but does not neccessarily supplant) cash flows, and 3) competition ensures that eye-popping financial performance doesn't last forever.
Contrary to another reviewer, English employs excellent examples to clarify and explain his points. Some examples: Gateway 2000's earnings history was used to explain how to find and interpret non-recurring items (NRI) on financial statements. Ratio analysis was demonstrated by looking at the PC industry in 1998. Emerson Electric was the company chosen to show why mature companies were still good buys. Many other examples abound, and English does a successful job in tying their relevance to his arguements.
But successful use of examples is not just the only strength of the book. The author also tackles a range of topics complete with insightful and clear discussions: the flaws of the Efficient Market Hypothesis (EMH), Economic Value Added (EVA), financial statement analysis, fundamental analysis, etc.
A quick glance at the table of contents below gives you an idea of the scope of English's book. I highly recommend this book to not just Wall Street analysts, anyone who is interested in finding fundamental value in evaluating stocks instead of following the crowd.
Pt. 1Getting Started
Ch. 1A Day in the Life
Ch. 2Fundamentals of Equity Valuation
Ch. 3Strategy and Competition I: The Firm's External Environment
Ch. 4Strategy and Competition II: The Firm's Internal Competitive Resources
Ch. 5Fundamentals of Stock Behavior
Pt. 2The Basic Tools
Ch. 6Reading a Financial Statement: The Accuracy, Sustainability, and Predictability of Financial Information
Appendix 6-1Gateway Financial Statements
Ch. 7Reading a Financial Statement: the Composition of Returns
Appendix 7-1Comparative Financial Analysis: Personal Computer Industry
Ch. 8Reading a Financial Statement: Early-Stage Companies and Investment Capacity
Ch. 9Reading a Financial Statement: Later-Stage Companies and the Transition to Maturity
Ch. 10Economic Value Added: An Alternative to Traditional Analysis Techniques
Appendix 10-1Gateway's Cost of Capital
Pt. 3Financial Models
Ch. 11Financial Modeling: Base Case Assumptions and Model Design
Appendix 11-1Dell Computer Corporation Consolidated Statement of Income
Ch. 12Financial Modeling: The Income Statement and Balance Sheet
Ch. 13Financial Modeling: The Statement of Cash Flows
Pt. 4Equity Valuation
Ch. 14Valuation: Foundations and Fundamentals
Ch. 15Combat Finance: Relative Methods and Companion Variable Models
Ch. 16Hybrid Valuation Techniques
Ch. 17The Quirky Price/Earnings Ratio
Ch. 18Valuation of Speculative Stocks
Ch. 19Equity Analysis and Business Combinations
Pt. 5Getting It Down on Paper
Ch. 20Financial Writing: Don't Bury the Lead
Bibliography
Index

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Applied Equity Analysis treats stock valuation as a practical, hands-on tool rather than a vague, theoretical exercise—and covers the entire valuation process from financial statement analysis through the final investment recommendation. Its integrated approach to valuation builds viable connections between a firm's competitive situation and the ultimate behavior of its common stock. Techniques explained include EVA, newer hybrid valuation techniques, and relative multiple analysis.

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Modeling Life: Art Models Speak About Nudity, Sexuality, And the Creative Process Review

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(More customer reviews)Sarah Philips undertook this research in Portland, during the mid-1990s. She puts in print words of art models themselves, which surprisingly hadn't happened much before. In the book we can read four more or less extended interviews with models, but dozens of conversations took place. Philips relates the models' words with interesting theoretical issues. It's a very enlightening book, since we come to know a very ignored and undervalued occupation. The book raises questions such as:
Why are there more female than male art models?
Is the myth that a model is an artist's mistress true?
Is a model the same as a stripper?
Does modeling objectify or degrade the person (usually the woman), as some feminists say?
Why would nudity be empowering and boost the model's self-confidence?
Why would someone do this job, normally part-time, since they could earn more money elsewhere? (In Portland, in the 1990s, they earned from $8.50 to $10 an hour.)
Is modeling always passive?
Why do most models underrate photography as "less artistic" than drawing, for instance?
What's the role of pornography, especially on the internet, when handling photos of artistic nudity?
What specific boundaries exist in personal space, verbal contact or eye contact when posing?
What's the difference between a "sublimely" sensual pose and a blunt sex pose?
How do models handle cold, and physical stressful or painful poses?
How do models deal with erections and menstruation?
There are no definite answers, but the discussion is really fascinating. Not all models agree upon all issues, and age and gender usually influence the answers.
I think the core of the whole question is the fact that in art modeling there are new rules, for our everyday regulations are upside down: a person doesn't hide his/her nakedness, and the others ARE supposed to observe it. The boundary is the motto "nothing unusual is happening". Don't behave as if this situation is abnormal, surprising, sexually arousing or deserving lewd peeking. It's just natural for professional artists and models to work with nudity, which can make many newcomers and art students blush.
Nudity in art is not for a particular physical aesthetics that discriminates all other bodies. It's not for sexuality, either. It's rather a celebration of the natural, general beauty of every human body, no matter its shape, color, size or other specific characteristics.
I am a painter myself, and I always work with the female nude. I can say that I am grateful to my models for their good work and professionalism. They are the body of my art, and they inspire its soul. As the model "Michael" says in the book: "If it wasn't for us, we wouldn't have a lot of the greatest works of art." For all the curious, and all of us artists who work with models, this book is necessary to understand, not stigmatize this indispensable job, in the models' own words.


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A fascinating consideration of the work of life models and the models' own perspectives on their craft.

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Integrated Practice in Architecture: Mastering Design-Build, Fast-Track, and Building Information Modeling Review

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(More customer reviews)The term "integrated practice" was quickly dispatched in 2007 when the California Council of the AIA presented "Integrated Project Delivery - A Working Definition" at the AIA National Convention - and for good reason. Integrated practice is an internal affair for each of the Owner, Architect and Contractor. Integrated Project Delivery brings all parties involved in the development of a project into the discussion. In addition, for the time being - and for some time into the future - any practice is going to involve both traditional and integrated project delivery. Finally, I found the book confusing in the way it tends to equate BIM with Integrated Practice, when the two are certainly seperable, if not independent. I don't know of a better book out there at present, but I wish I'd waited for one before buying.

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Molecular Modeling and Simulation: An Interdisciplinary Guide (Interdisciplinary Applied Mathematics) Review

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(More customer reviews)I am a computer science professional with around 10 years of experience. I got this book to get my self started with molecular simulation for real world practical applications. although this book is titled molecular modeling and simulation, it starts with protein folding. I found reading this book extremely painful due to few reasons.
1) Author just states what she knows, but does not seem to explain them. Rather than starting from a simple scale and gradually building up, the information is presented in ad-hoc manner. The manner in which this information is presented in not in tutorial style and not even in a style that can be used for reference.
2) lots of unnecessary information - author seem to write about every thing that comes to her mind. For some one who has been in this field for long, this is acceptable, but for some one who is just starting like me, this is bit of an overload. Reader might not know what to read and what to skip.
3) The chapters are cyclic dependent. (there are references to later chapters from earlier chapters, but to read later chapters you first need to read earlier chapters). Author herself ask the reader to read some early chapters after reading later ones. This is very confusing at least for me.
For me, this book was a total waste. I am thinking of re-starting with "Molecular Modelling: Principles and Applications" by A.R Leach. Although this book is bit old, it should be enough for me to get started.


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Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text

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Environmental Systems and Processes: Principles, Modeling, and Design Review

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(More customer reviews)I am an envoronmental engineering student, and my instructor for a course used this book. I thought it was cumbersome to use, I came from a civil engineering department, as much of it was referencing chemical engineering material without sufficient review and background. I also thought that it made so much reference to PDES, weber's other text, that it should just be included as part of that book. I wouldnt recommend this to another sudent.

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Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence Review

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(More customer reviews)This book is, bar none, the best book on longitudinal analysis in social sciences.
The book has three outstanding features that make it the must-have for researchers who conduct longitudinal studies. First, the book has numerous examples that use data from real studies, collected by prominent scholars in this area. With the help of the accompanying website at UCLA, you will learn how to set up data files, which is crucial in longitudinal analysis. The sample codes and data files in SAS, SPSS, Stata, MLwiN, Mplus, HLM, and Splus will allow you to replicate the analyses. The authors use every effort to explain the results in plain, understandable language. They use a lot of graphs and tables to compare different nested models and help you to choose the one that best describes your data. It feels like you have an excellent tutor by your side when you are reading this book.
Second, the coverage of this book is comprehensive. Part I covers the regular growth curve modeling and multilevel modeling, with a few chapters dealing with time-varying covariates, discontinuous and nonlinear change. Part II covers discrete-time and continuous-time survival analysis. If you are conducting a longitudinal study, chances are you will find a technique in this book that suits you just right.
Third, the book is quite deep. Although it gears toward applications of different longitudinal analyses, it is no cakewalk. You need at least some background in multiple regression and multivariate statistics. I think the treatment of mathematics (both concepts and formulas) is just right. In some sections you may need to revisit them often in order to fully understand the subject.


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Change is constant in everyday life.Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful.Beyond these natural processes and events, external forces and interventions instigate and disrupt change:test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences.It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: Downloadable data sets Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more Additional material for data analysis

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