This small book addresses different kinds of datafiles, as commonly encountered in clinical research, and their data-analysis on SPSS Software. Some 15 years ago serious statistical analyses were conducted by specialist statisticians using ma- frame computers. Nowadays, there is ready access to statistical computing using personal computers or laptops, and this practice has changed boundaries between basic statistical methods that can be conveniently carried out on a pocket calculator and more advanced statistical methods that can only be executed on a computer. Clinical researchers currently perform basic statistics without professional help from a statistician, including t-tests and chi-square tests. With help of user-friendly software the step from such basic tests to more complex tests has become smaller, and more easy to take. It is our experience as masters' and doctorate class teachers of the European College of Pharmaceutical Medicine (EC Socrates Project Lyon France) that s- dents are eager to master adequate command of statistical software for that purpose. However, doing so, albeit easy, still takes 20-50 steps from logging in to the final result, and all of these steps have to be learned in order for the procedures to be successful.

MATLAB Mathematical Analysis is a reference book that presents the techniques of mathematical analysis through examples and exercises resolved with MATLAB software. The purpose is to give you examples of the mathematical analysis functions offered by MATLAB so that you can use them in your daily work regardless of the application. The book supposes proper training in the mathematics and so presents the basic knowledge required to be able to use MATLAB for calculational or symbolic solutions to your problems for a vast amount of MATLAB functions. The book begins by introducing the reader to the use of numbers, operators, variables and functions in the MATLAB environment. Then it delves into working with complex variables. A large section is devoted to working with and developing graphical representations of curves, surfaces and volumes. MATLAB functions allow working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. Additional work implements twisted curves, surfaces, meshes, contours, volumes and graphical interpolation. The following part covers limits, functions, continuity and numerical and power series. Then differentiation is addressed in one and several variables including differential theorems for vector fields. Thereafter the topic of integration is handled including improper integrals, definite and indefinite integration, integration in multiple variables and multiple integrals and their applications. Differential equations are exemplified in detail, Laplace transforms, Tayor series, and the Runga-Kutta method and partial differential equations.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential and Integral Calculus introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving a short introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work with ease in differential and integral calculus in one and several variables. Among other core topics of calculus, you will use MATLAB to investigate convergence, find limits of sequences and series and, for the purpose of exploring continuity, limits of functions. Various kinds of local approximations of functions are introduced, including Taylor and Laurent series. Symbolic and numerical techniques of differentiation and integration are covered with numerous examples, including applications to finding maxima and minima, areas, arc lengths, surface areas and volumes. You will also see how MATLAB can be used to solve problems in vector calculus and how to solve differential and difference equations.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential Equations introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to giving an introduction to the MATLAB environment and MATLAB programming, this book provides all the material needed to work on differential equations using MATLAB. It includes techniques for solving ordinary and partial differential equations of various kinds, and systems of such equations, either symbolically or using numerical methods (Euler's method, Heun's method, the Taylor series method, the Runge-Kutta method,...). It also describes how to implement mathematical tools such as the Laplace transform, orthogonal polynomials, and special functions (Airy and Bessel functions), and find solutions of finite difference equations.

The implementation of a TMS solution is a highly complex and mission critical project. If executed correctly a good TMS can deliver a number of benefits to the organization in terms of optimization, greater efficiency, reduced errors and improved revenue through accurate invoicing. However a number of projects fail to realize these benefits for a host of reasons such as an incorrect product selection, over customization of the system and lack of detailed processes. The evaluation and selection of the right transportation management system is a very critical step in the successful implementation of a TMS product as well as ensuring that the organization is able to realize the benefits expected from the system.Transportation Management with SAP TM 9 is a guide for CIO/CXOs evaluating options for various transportation management solutions available in the market and helps inappropriate decision making before committing investment. A proven evaluation framework and guidance provided in the book can help decision makers with product selection and help to create a business case for management approval and design a future roadmap for the organization. The book provides a comprehensive understanding of what SAP transportation management is and is useful for teams involved in TM Implementation and roll outs to ensure preparedness. The book explains end-to-end freight life cycle processes, functional system landscape, implementation challenges and post go-live precautions required to optimize investments in SAP TM. Transportation Management with SAP TM 9 also acts as a step by step implementation guide with details of configuration required to set up a TM9 system. This book also covers the upgrade of SAP TM8 to SAP TM9 which will be useful for existing clients who are on TM 8. Nonavailability of SAP TM skilled resources is a major challenge faced by organizations and the book provides a detailed competency building plan along with skill set requirements to create a competent and trained workforce to manage-transformation.The current book available in the market on SAP TM is based on Version 6 release which does not cover air freight processes. Our book covers end-to-end air freight configuration scenarios for logistic companies.

Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others.

This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate. The challenging proposals provide a connection between statistical methodology and the social domain with particular attention to computational issues in order to effectively address complicated data analysis problems.
The papers in this volume stem from contributions initially presented at the joint international meeting JCS-CLADAG held in Anacapri (Italy) where the Japanese Classification Society and the Classification and Data Analysis Group of the Italian Statistical Society had a stimulating scientific discussion and exchange.

Modern algorithmic techniques for summation, most of which were introduced in the 1990s, are developed here and carefully implemented in the computer algebra system Maple (TM). The algorithms of Fasenmyer, Gosper, Zeilberger, Petkovsek and van Hoeij for hypergeometric summation and recurrence equations, efficient multivariate summation as well as q-analogues of the above algorithms are covered. Similar algorithms concerning differential equations are considered. An equivalent theory of hyperexponential integration due to Almkvist and Zeilberger completes the book. The combination of these results gives orthogonal polynomials and (hypergeometric and q-hypergeometric) special functions a solid algorithmic foundation. Hence, many examples from this very active field are given. The materials covered are suitable for an introductory course on algorithmic summation and will appeal to students and researchers alike.

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area. Due to progress made in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochastic processes used for input modeling. Graduate students and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacity planning will find the unified notation and up-to-date results presented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models.

The goal of input modeling is to find a stochastic model to describe a sequence ofmeasurements from a real system to model for example the inter-arrival times of packets in a computer network or failure times of components in a manufacturing plant. Typical application areas are performance and dependability analysis of computer systems, communication networks, logistics or manufacturing systems but also the analysis of biological or chemical reaction networks and similar problems. Often the measured values have a high variability and are correlated. It s been known for a long time that Markov based models like phase type distributions or Markovian arrival processes are very general and allow one to capture even complex behaviors. However, the parameterization of these models results often in a complex and non-linear optimization problem. Only recently, several new results about the modeling capabilities of Markov based models and algorithms to fit the parameters of those models have been published.

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This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs.

Dynamical system theory has developed rapidly over the past fifty years. It is a subject upon which the theory of limit cycles has a significant impact for both theoretical advances and practical solutions to problems. Hopf bifurcation from a center or a focus is integral to the theory of bifurcation of limit cycles, for which normal form theory is a central tool. Although Hopf bifurcation has been studied for more than half a century, and normal form theory for over 100 years, efficient computation in this area is still a challenge with implications for Hilbert's 16th problem.

This book introduces the most recent developments in this field and provides major advances in fundamental theory of limit cycles. Split into two parts, the first focuses on the study of limit cycles bifurcating from Hopf singularity using normal form theory with later application to Hilbert's 16th problem, while the second considers near Hamiltonian systems using Melnikov function as the main mathematical tool.

Classic topics with new results are presented in a clear and concise manner and are accompanied by the liberal use of illustrations throughout. Containing a wealth of examples and structured algorithms that are treated in detail, a good balance between theoretical and applied topics is demonstrated. By including complete Maple programs within the text, this book also enables the reader to reconstruct the majority of formulas provided, facilitating the use of concrete models for study.

Through the adoption of an elementary and practical approach, this book will be of use to graduate mathematics students wishing to study the theory of limit cycles as well as scientists, across a number of disciplines, with an interest in the applications of periodic behavior."

The theme of the meeting was Statistical Methods for the Analysis of Large Data-Sets . In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event.
The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on Advanced Statistical Methods for the Analysis of Large Data-sets. "

The interaction of the solar and heat radiation with the atmosphere and surface is the subject of the book. It is useful also for wide circle scientists involved in environmental studies. The book contains the description of 17 computer studying programs supporting different topics of courses. It includes only the base ground for comprehension of key topics and provides the accomplishment of practical works with using specially elaborated computer programs. Themes of practical works reflect main sections of mentioned courses of lectures. The packet of computer programs is added for solution of direct and inverse problems. It promotes deep and reliable comprehension of corresponding topics by students. All described approaches and computer programs are valuable resources for solving radiative transfer problems and they could be used by students for courses and diploma studies concerned atmospheric optics.

"Functional and Phylogenetic Ecology in R" is designed to teach readers to use R for phylogenetic and functional trait analyses. Over the past decade, a dizzying array of tools and methods were generated to incorporate phylogenetic and functional information into traditional ecological analyses. Increasingly these tools are implemented in R, thus greatly expanding their impact. Researchers getting started in R can use this volume as a step-by-step entryway into phylogenetic and functional analyses for ecology in R. More advanced users will be able to use this volume as a quick reference to understand particular analyses. The volume begins with an introduction to the R environment and handling relevant data in R. Chapters then cover phylogenetic and functional metrics of biodiversity; null modeling and randomizations for phylogenetic and functional trait analyses; integrating phylogenetic and functional trait information; and interfacing the R environment with a popular C-based program. This book presents a unique approach through its focus on ecological analyses and not macroevolutionary analyses. The author provides his own code, so that the reader is guided through the computational steps to calculate the desired metrics. This guided approach simplifies the work of determining which package to use for any given analysis. Example datasets are shared to help readers practice, and readers can then quickly turn to their own datasets.

Post-Optimal Analysis in Linear Semi-Infinite Optimization examines the following topics in regards to linear semi-infinite optimization: modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis. Linear semi-infinite optimization (LSIO) deals with linear optimization problems where the dimension of the decision space or the number of constraints is infinite. The authors compare the post-optimal analysis with alternative approaches to uncertain LSIO problems and provide readers with criteria to choose the best way to model a given uncertain LSIO problem depending on the nature and quality of the data along with the available software. This work also contains open problems which readers will find intriguing a challenging. Post-Optimal Analysis in Linear Semi-Infinite Optimization is aimed toward researchers, graduate and post-graduate students of mathematics interested in optimization, parametric optimization and related topics.

Practical SharePoint 2013 Enterprise Content Management is the first book to guide you through planning and designing each phase of your information life cycle with SharePoint 2013. Author and SharePoint expert Steve Goodyear walks you through how to analyze and plan enterprise content management (ECM) solutions for an effective and end-to-end information design based on your organization's needs and business requirements. Inside, you will develop a full understanding of how SharePoint 2013 manages content including identifying and understanding your organization's information within SharePoint, collaborating on transitory content, and capturing and controlling your records. You'll get practical advice and best practice instruction for each phase of the information life cycle to guide you on designing your ECM strategy and implementing your own ECM solution.You learn how to: * Apply a content life cycle model to analyze and understand your organization's information * Design your file plan with content routing rules for your SharePoint records repository * Plan and configure your eDiscovery portal and manage discovery cases * Design solutions to interface and integrate with external records management systems * Identify your organization's information security requirements * Design content types and implement an enterprise content type hub to organize your information Practical SharePoint 2013 Enterprise Content Management is for you if you are a SharePoint architect, administrator, consultant, or project manager, and you implement SharePoint solutions that relate to one or more aspects of the information life cycle involved with ECM.What you'll learn * Apply a content life cycle model to analyze and understand your organization's information * Plan and configure your SharePoint 2013 enterprise eDiscovery portal and manage discovery cases * Design your file plan with content routing rules for your SharePoint records repository * Design solutions to interface and integrate with external records management systems * Design content types and implement an enterprise content type hub to categorize and organize your information * Identify your organization's information security requirements Who this book is for Practical SharePoint 2013 Enterprise Content Management is for you if you are a SharePoint architect, administrator, consultant, or project manager, and you implement SharePoint solutions that relate to one or more aspects of the information life cycle involved with ECM. This book is also for you if you are an enterprise architect or a records manager and you want to learn how ECM fits in SharePoint. This book is definitely for you if you want to learn how to analyze, design, and implement an ECM solution on SharePoint 2013.

World Wide Web is becoming an utility, not unlike electricity or running water in our homes. This creates new ways of using the web, where Social Media plays a particular role. This gives an unprecedented opportunity to study the emerging social phenomena in the virtual world. In addition, it opens new avenues for improving public services such as schooling and education. This book includes some of the latest developments in employing the information and communications technologies for examining both virtual and real-life social interactions. Investigating modern challenges such as online education, web security or organized cybercrime, this book outlines the state of the art in social applications and implications of ICT.

This book presents methods for computing correlation equations. All the topics treated hefe are eluci dated in terms of concrete examples, which have been chosen, for the most part, from the Held of analysis of the mechanical properties of steel, wood, and other materials. A necessary prerequisite for any study of correlation equations is so me knowledge of the moments of random variables. In the Appendix, there is provided a brief treatment of moments, as well as a discussion of the simplest methods of computing them. We have paid particular attention in this book to the techniques of computing correlation equations, and to the use of tables for alleviating the computationalload. The mathematical bases of the methods used in setting up correlation equations are expounded in the books cited at the end of this volume. A. M. December 1965 PIe ase note that the abbreviation 19 is used in this book to designate the logarithm to base ten, Note further that the comma has been retained as the decimal point in tabular material."

The first MATLAB-based numerical methods textbook for bioengineers that uniquely integrates modelling concepts with statistical analysis, while maintaining a focus on enabling the user to report the error or uncertainty in their result. Between traditional numerical method topics of linear modelling concepts, nonlinear root finding, and numerical integration, chapters on hypothesis testing, data regression and probability are interweaved. A unique feature of the book is the inclusion of examples from clinical trials and bioinformatics, which are not found in other numerical methods textbooks for engineers. With a wealth of biomedical engineering examples, case studies on topical biomedical research, and the inclusion of end of chapter problems, this is a perfect core text for a one-semester undergraduate course.

Microsoft Dynamics CRM has a robust API that includes web services and an extensive SDK. As you develop CRM Plugins and custom integrations, you will find that there are many complexities and challenges associated with successfully interacting with this API In order to ensure that you have all of the tools necessary to achieve success with CRM development, Microsoft Dynamics CRM 2011 API Development presents the essential aspects of API development including plugin development and registration. In addition to Plugins, you will work through building out several integrations that work with both the SDK and the Web Service layer. You will also build a C# application that creates records within CRM using the API, work with Scribe Online for integration and migration, design reports that read data from CRM using FetchXML, and interact with the OData REST service using JScript. Once you've worked through the various topics presented, you will find that you will have the advanced skills required for working with CRM 2011 Online and On Premises. What you'll learn Learn to develop, test, and deploy CRM Plugins Create custom integrations using the CRM API Create applications that interface with the SDK and CRM Web Services Use JScript to read and write data using the OData REST service Design SSRS reports that interact with CRM using FetchXML Who this book is for Experienced Microsoft Dynamics CRM developers new to version 2011, and all CRM developers new to Microsoft Dynamics CRM. Also for C# developers wanting to learn Microsoft Dynamics CRM.

Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, with extensions to local likelihood and density estimation. Practical information is also included on how to implement these methods in the programs S-PLUS and LOCFIT.

"Enterprise Applications Administration" prepares you for the full breadth of work associated with administering large enterprise applications. This book provides essential information on tasks such as operating systems administration, network design, system architecture, project planning, working within a team, protecting the network, and how to keep applications up and running. The book effectively bridges the gap between what is taught in the technology-specific literature and the real world of enterprise application administrators.
Provides a general understanding of all key knowledge areas needed by enterprise application administratorsBridges the gap between technology-specific literature and the actual work being performed by enterprise application administratorsShows how to define and standardize processes and documentation to make enterprise application administration easier and more consistent

Engineering mechanics involves the development of mathematical models of the physical world. Statics addresses the forces acting on and in mechanical objects and systems. Statics with MATLAB (R) develops an understanding of the mechanical behavior of complex engineering structures and components using MATLAB (R) to execute numerical calculations and to facilitate analytical calculations. MATLAB (R) is presented and introduced as a highly convenient tool to solve problems for theory and applications in statics. Included are example problems to demonstrate the MATLAB (R) syntax and to also introduce specific functions dealing with statics. These explanations are reinforced through figures generated with MATLAB (R) and the extra material available online which includes the special functions described. This detailed introduction and application of MATLAB (R) to the field of statics makes Statics with MATLAB (R) a useful tool for instruction as well as self study, highlighting the use of symbolic MATLAB (R) for both theory and applications to find analytical and numerical solutions

Rcpp is the glue that binds the power and versatility of R with the speed and efficiency of C++. With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp should be part of every statistician's toolbox. -- Michael Braun, MIT Sloan School of Management

"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business

Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management

The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book -- Soren Hojsgaard," "Department of Mathematical Sciences, Aalborg University, Denmark

"Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++.

Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.

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This book collects the proceedings of the 10th Workshop on Model-Oriented Design and Analysis (mODa). A model-oriented view on the design of experiments, which is the unifying theme of all mODa meetings, assumes some knowledge of the form of the data-generating process and naturally leads to the so-called optimum experimental design. Its theory and practice have since become important in many scientific and technological fields, ranging from optimal designs for dynamic models in pharmacological research, to designs for industrial experimentation, to designs for simulation experiments in environmental risk management, to name but a few. The methodology has become even more important in recent years because of the increased speed of scientific developments, the complexity of the systems currently under investigation and the mounting pressure on businesses, industries and scientific researchers to reduce product and process development times. This increased competition requires ever increasing efficiency in experimentation, thus necessitating new statistical designs. This book presents a rich collection of carefully selected contributions ranging from statistical methodology to emerging applications. It primarily aims to provide an overview of recent advances and challenges in the field, especially in the context of new formulations, methods and state-of-the-art algorithms. The topics included in this volume will be of interest to all scientists and engineers and statisticians who conduct experiments.