Book Description
This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and applications of structural equation modeling; 2) demonstrating basic applications of SEM using AMOS 4.0; and 3) highlighting features of AMOS 4.0 that address important caveats related to SEM analyses.
Written in a "user-friendly" style, the author "walks" the reader through 10 SEM applications from model specification to estimation to the assessment and interpretation of the output. Each of the book's applications is accompanied by:
*a statement of the hypothesis being tested;
*a schematic representation of the model under study;
*the use and function of a wide variety of icons and pull-down menus;
*a full explanation of related AMOS Graphic input models and output files;
*a model input file based on AMOS BASIC; and
*the published reference from which each application was drawn.
Customer Reviews:
Structural Equation Modeling With AMOS: Basic Concepts, Applications, and Programming (Multivariate Applications Series).......2007-02-21
Great book, easy to read. It goes well as a companion book about SEM with a more mathematically heavy text. The author makes using AMOS easy! I've already shown my Professor something about AMOS he didn't know!
Great Resource.......2006-01-29
If you are looking for a good resource on learning how to use AMOS for structural equation modeling, this is definitely the book. It is easy to understand and well laid out. Well recommended, especially for teaching SEM to students.
wonderful if familiar w/stats + new to sem.......2001-08-07
This book is a wonderful guide to understanding a good range of basics about sem, getting models to work with Amos, and interpreting your output. You will need to be familiar with one of the stats packages that Amos is compatible with. Very much user-friendly in this complicated topic. All of the statistically-related and theory-related aspects are well-referenced, so you can find sources to reference for different aspects of sem. A great book to fill the gap between the Amos user's manual and books on sem in general. (contact Erlbaum about educ pricng.)
Book Description
"Mr. Salov has taken one of my favorite creations – Perfect Profit – and provided an expanded description of his interpretation of it and put it in your hands with the included software. Like I said fifteen years ago, Perfect Profit is an important tool for the trading system developer. See for yourself."
—Robert Pardo, President, Pardo Capital Limited
"A very in-depth reference for programmers that should serve well into the future. The code herein lends itself well to other syntactically similar programming languages such as Java, PHP, and C#."
—Ralph Vince
The goal of trading is to make money, and for many, profits are the best way to measure that success. Author Valerii Salov knows how to calculate potential profit, and in Modeling Maximum Trading Profits with C++, he outlines an original and thought-provoking approach to trading that will help you do the same.
This detailed guide will show you how to effectively calculate the potential profit in a market under conditions of variable transaction costs, and provide you with the tools needed to compute those values from real prices. You'll be introduced to new notions of s-function, s-matrix, s-interval, and polarities of s-intervals, and discover how they can be used to build the r- and l-algorithms as well as the first and second profit and loss reserve algorithms. Optimal money management techniques are also illustrated throughout the book, so you can make the most informed trading decisions possible.
Filled with in-depth insight and expert advice, Modeling Maximum Trading Profits with C++ contains a comprehensive overview of trading, money management, and C++. A companion CD-ROM is also included to help you test the concepts described throughout the book before you attempt to use them in real-world situations.
Customer Reviews:
should have been a short journal article.......2007-06-29
SUMMARY: A potentially useful concept taken to ridiculous extremes.
The main theme is around the concept of *potential profit* offered by a particular market. When building automated trading strategies or evaluating human trader performance, the problem could be decomposed into a product of some intrinsic profit offered by the market and the percentage of that profit that is captured by a particular trader or strategy. This book spends most of its attention on the former factor and various derived performance metrics.
*Potential profit* is defined by an idealized strategy that has *perfect foresight about all future prices over a given time interval*. In addition to the original concept apparently suggested by Robert Pardo, the book's definition is made more realistic by constraining such a strategy with non-zero transaction costs. Although this connection is not made by the author, the concept is related to those used in offline algorithms and competitive analysis (see, for example, Online Computation and Competitive Analysis): in essence, you want to quantify the amount of *regret* you experience comparing your performance to that of a perfect adversary or algorithm that is allowed to solve the offline version of the same problem (with all of the future data available at the outset).
Three iterations of potential profit algorithms are introduced:
1. "r-/l-algorithms": position size is constrained with a given maximum. The perfect strategy can be proven to be pure reversal -- except for initial and final transactions, the maximum profit is obtained by always switching positions between +max_size and -max_size at certain transaction points. Although the underlying problem could be solved using a generic optimizer, Salov introduces a concept of *s-intervals* that makes it easy to see how the global maximum can be computed with a simple linear algorithm. This algorithm offers conceptual elegance of solving its related problem exactly -- the later two are heuristic improvements for less constrained versions of the problem.
2. "first P&L reserve algorithm": strategy remains a pure reversal strategy but position size is allowed to vary subject only to self-financing/account margin/buying power constraints. #2 can improve on #1 due to increases in account buying power after the initial entry/exit transactions.
3. "second P&L reserve algorithm": same as #2 but the strategy is allowed to change existing positions in between the transaction points used by #1 and #2, i.e. the strategy is no longer pure reversal. Again, #3 can improve on #1 due to increases in account buying power during trading.
Since both #2 and #3 consider how account equity grows over time subject to self-financing restrictions, connections to Kelly/Shannon
maximum growth rate formulas arise naturally. In later chapters, all algorithms are used to derive performance metrics and to compare potential profits offered by various markets using real-life price data.
Unfortunately, in my view the author should have stopped at #1 and not gone on for 180 more pages. Granted, the overall approach of comparing your actual performance to that of some idealized benchmark strategy is extremely sound and useful. As a benchmark, a single simple idealized strategy is sufficient. But the author does not emphasize enough that the single biggest advantage the idealized strategy has is the perfect knowledge of future prices. Algorithm #1 already has this advantage built in and there seems to be little practical value in gleaning further incremental benefits by adding optimal account growth heuristics. (Optimizing position sizes can't be done in real-life without simultaneously controlling risk etc.) In fact, the last chapter has a cocoa contract example making 13000% returns in just 5 days! Similarly, in some examples algorithms #2 and #3 manage to grow exponentially into such large position sizes that they overflow a 32-bit integer -- it is surprising that the author does not see the ridiculousness of that and reluctantly suggests that the algorithms should be applied to "short time intervals" or "with high transaction costs".
Other book shortcomings that seemed glaring to me:
- only deterministic strategies are considered. Real-life strategies have to incorporate uncertainty modeling in their decisioning. Furthermore, deterministic-only strategies can't reach Nash equilibria for some problems.
- only two commission cost models are considered: fixed per transaction and cost as a function of instrument price. Something like cost/share would invalidate much of the discussion.
- because they have perfect price foresight all idealized algorithms unavoidably go wild on max'ing out position sizes. In real life, risk management constraints on open positions can kick in sooner than margin constraints, unless you are diversified across many positions (situation not considered in the book).
- after observing how much the transaction costs can impact these idealized strategies, the author nonetheless goes on and makes very ballpark guesses about slippage etc -- it seems incongruent after all that energy spent on perfecting those strategies.
15 years is not enough: a new market property.......2007-02-25
I am a professional mathematician with a personal interest in mathematical finance and I know the author. I did not expect Dr. Salov to be writing a book but eventually I became one of the first readers. The book focuses on modeling and calculation of the potential profit - a new and fascinating market property. It also contains a gentle introduction explaining basic trading, financial and programming terms and helping better to understand the main topic. Therefore, the book should be interesting for all market participants: trading system developer, trader, theoretician working on finance or someone who wishes to learn the field of trading systems and quantitative finance.
It is interesting that the potential profit, as introduced by Robert Pardo, corresponds to a classical notion of a total variation of a function, the function being the time sequence of prices of a commodity. Computation of the potential profit in the presence of e.g. transaction costs becomes a sophisticated mathematical problem which Dr. Salov solves using the newly suggested r- and l-algorithms. In a systematic way, the author introduces s-function, s-matrix, polarity, s-intervals and proves their properties, producing an effective r- and l-algorithms.
While Robert Pardo introduced potential profit as a new concept, Valerii Salov brings this concept to a substantially higher level. He considers the maximum profit as a market property, which must be combined with a sequence of trading actions - trading strategy. He systematically comes the way from simple market and trading systems performance measures to a powerful and automatic tool filtering the most critical price events. This becomes possible because he takes into account transaction costs such as commissions, slippage, and others. A motivation for each decision leading to the complete software, new algorithms, or money management is carefully explained.
I highly recommend reading this book for anyone interested in development of trading systems and who wants to understand better the work of markets.
Book Description
Research in systems biology requires the collaboration of researchers from diverse backgrounds, including biology, computer science, mathematics, statistics, physics, and biochemistry. These collaborations, necessary because of the enormous breadth of background needed for research in this field, can be hindered by differing understandings of the limitations and applicability of techniques and concerns from different disciplines. This comprehensive introduction and overview of system modeling in biology makes the relevant background material from all pertinent fields accessible to researchers with different backgrounds.
The emerging area of systems level modeling in cellular biology has lacked a critical and thorough overview. This book fills that gap. It is the first to provide the necessary critical comparison of concepts and approaches, with an emphasis on their possible applications. It presents key concepts and their theoretical background, including the concepts of robustness and modularity and their exploitation to study biological systems; the best-known modeling approaches, and their advantages and disadvantages; lessons from the application of mathematical models to the study of cellular biology; and available modeling tools and datasets, along with their computational limitations.
Book Description
Practical and up-to-date,
Structural Equation Modeling includes chapters on major aspects of the structural equation modeling approach to research design and data analysis. Written by internationally recognized leaders in structural equation modeling, this book targets graduate students and seasoned researchers in the social and behavioral sciences who wish to understand the basic concepts and issues associated with the structural equation modeling approach and applications to research problems. Though technically sound, the chapters are primarily nontechnical in content and stylemaking the volume an excellent introduction to the structural equation modeling approach for readers studied in traditional inferential statistics. Early chapters are devoted to fundamental concepts such as estimation, fit, assumptions, power, and inference. Later chapters address such practical issues as the use of computer programs for applying the approach to research questions in the social and behavioral sciences.
Customer Reviews:
Highly Theorectical.......2006-03-03
Comprehensive coverage of SEM, highly technical and heavy with references. Better for advanced students of SEM rather than novices.
A must read for the novice SEM user.......1998-08-29
This book was my saving grace in writing my dissertation. The book provides an excellent review of SEM's concepts, issues, and applications in both EQS and Lisrel, in a manner which is understandable to a budding researcher.
Product Description
This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the readers familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the books CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chaptersgrowth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.
Customer Reviews:
Clear, easy to follow intro to LGCM theory and techniques.......1999-10-21
This is an excellent book for anyone who wishes to not only understand the theory behind latent growth curve modeling but also seeing how it is directly applied in a number of situations. For a reader like me who depends upon the literature to help understand newer statistical approaches, a book like this is a breath of fresh air. The book presents very clearly how to set up a basic LGC model and includes other topics such as dealing with missing data, interaction effects and multilevel approaches to longitudinal data analysis. The appendix contains a number of example LGCM models in the software language of EQS, LISREL and AMOS. I most highly recommend this text for beginners and more advanced modelers alike!
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Geochemical Reaction Modeling: Concepts and Applications
Craig M. Bethke
Manufacturer: Oxford University Press, USA
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Environmental Applications of Geochemical Modeling
ASIN: 0195094751 |
Book Description
Geochemical reaction modeling plays an increasingly vital role in several areas of geoscience, from environmental geochemistry and petroleum geology to the study of geothermal and hydrothermal fluids. This book provides an up-to-date overview of the use of numerical methods to model reaction processes in the Earth's crust and on its surface. Early chapters develop the theoretical foundations of the field, derive a set of governing equations, and show how numerical methods can be used to solve these equations. Other chapters discuss the distribution of species in natural waters; methods for computing activity coefficients in dilute solutions and in brines; the complexation of ions into mineral surfaces; the kinetics of precipitation and dissolution reactions; and the fractionation of stable isotopes. Later chapters provide a large number of fully worked calculation examples and case studies demonstrating the modeling techniques that can be applied to scientific and practical problems. Students in a variety of specialties from low-temperature geochemistry to groundwater hydrology will benefit from the wealth of information and practical applications this book has to offer.
Book Description
Appropriate for undergraduate and graduate students, this text features independent sections that illustrate the most important principles of mathematical modeling, a variety of applications, and classic models. The range of subjects includes topics from the physical, biological, and social sciences, as well as those of operations research. Excerises. 1984 edition.
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Decision Modeling in Policy Management: An Introduction to the Analytic Concepts
G.E. Beroggi
Manufacturer: Springer
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ASIN: 0792383303 |
Book Description
The effectiveness of policy decisions depends not only on the quality of the analysis but also on the communication between analyst and decision-maker. As a result, this book employs the following three-step decomposition of the decision modeling process throughout the book: (1) visual-structural modeling, (2) analytic-formal modeling, and (3) algorithmic resolution modeling. The 10 chapters address the most relevant issues in decision modeling in policy management: the problem-solving process, visual decision modeling, descriptive and normative preference elicitation and aggregation methods, dealing with uncertainty in dynamic problems, social choices, conflict resolution, and constraint-optimization problems. A problem-oriented engineering approach has been taken throughout the book because this approach covers the most popular decision modeling issues in: (1) decision analysis (decision trees, probabilistic influence diagrams, fuzzy decision-making, risk analysis), (2) operations research (facility location, scheduling, linear and non-linear programming, network optimization), and (3) economics (cost-benefit analysis, capital budgeting, shadow prices, marginal rate of substitution, net present value, game theory).
Decision Modeling in Policy Management:
- Introduces a visual approach to decision modeling in policy management (over 100 figures and illustrations), integrating the European School (outranking relations, dimension reduction, ordinal preferences, rank correlation) and the American School (utility theory, analytic hierarchy process, game theory, constraint-optimization).
- Presents analytic approaches in the context of structural, formal, and resolution modeling; references to further practical and theoretical readings; intuitive visual reasoning; detailed numerical examples replacing theorems and formal proofs.
- Discusses new decision analytical features: visual interactive preference ordering; dynamic plots in virtual negotiation; hypermedia influence diagram modeling.
- Integrates 100 problems with worked-out solutions; an Internet syllabus with assignments, students comments, and Internet multimedia software are available.
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Graph-Theoretic Concepts in Computer Science: 24th International Workshop, WG'98, Smolenice Castle, Slovak Republic, June 18-20, Proceedings (Lecture Notes in Computer Science)
Manufacturer: Springer
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ASIN: 3540651950 |
Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the 24th International Workshop on Graph-Theoretic Concepts in Computer Science, WG'98, held in Smolenice Castle, Slovak Republic, in June 1998.The 30 revised full papers presented were carefully selected from a total of 61 submissions. The papers provide a wealth of new results for various classes of graphs, graph computations, graph algorithms and graph-theoretic applications in computer science.
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- The Great Human Diasporas: The History of Diversity and Evolution (Helix Books)
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- The Selfish Gene: 30th Anniversary Edition--with a new Introduction by the Author
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