This book illustrates the role of software architecture and its application in business. The author describes enterprise architecture along with business architecture to show the role of software architecture in both areas. The place of software architecture in business is outlined from many perspectives in this context. The book outlines quality attributes and how managers can use software architecture to build high quality products. Topics include business software architecture, dealing with qualities, achieving quality attributes, managing business qualities, software product line, Internet of Things (IOT), and Service Oriented Business Architecture. The book is intended to benefit students, researchers, software architects, and business architects. Provides quick and easy access to all the important aspects of software architecture in business; Highlights a wide variety of concepts of software architecture in a straightforward manner, for students, practitioners, or architects; Presents different applications of software architecture in business.

This Element is intended for students and practitioners as a gentle and intuitive introduction to the field of discrete-time yield curve modelling. I strive to be as comprehensive as possible, while still adhering to the overall premise of putting a strong focus on practical applications. In addition to a thorough description of the Nelson-Siegel family of model, the Element contains a section on the intuitive relationship between P and Q measures, one on how the structure of a Nelson-Siegel model can be retained in the arbitrage-free framework, and a dedicated section that provides a detailed explanation for the Joslin, Singleton, and Zhu (2011) model.

This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.

All the Essentials to Start Using Adaptive Designs in No Time Compared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time. Introductory Adaptive Trial Designs: A Practical Guide with R motivates newcomers to quickly and easily grasp the essence of adaptive designs as well as the foundations of adaptive design methods. The book reduces the mathematics to a minimum and makes the material as practical as possible. Instead of providing general, black-box commercial software packages, the author includes open-source R functions that enable readers to better understand the algorithms and customize the designs to meet their needs. Readers can run the simulations for all the examples and change the input parameters to see how each input parameter affects the simulation outcomes or design operating characteristics. Taking a learning-by-doing approach, this tutorial-style book guides readers on planning and executing various types of adaptive designs. It helps them develop the skills to begin using the designs immediately.

Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity. It also features a large number of worked examples and a wide range of applications from various disciplines. The book introduces regression models, techniques for criticism and comparison, and a wide range of modelling issues before going into the vital area of hierarchical models, one of the most common applications of Bayesian methods. It deals with essentials of modelling without getting bogged down in complexity. The book emphasises model criticism, model comparison, sensitivity analysis to alternative priors, and thoughtful choice of prior distributions-all those aspects of the "art" of modelling that are easily overlooked in more theoretical expositions. More pragmatic than ideological, the authors systematically work through the large range of "tricks" that reveal the real power of the BUGS software, for example, dealing with missing data, censoring, grouped data, prediction, ranking, parameter constraints, and so on. Many of the examples are biostatistical, but they do not require domain knowledge and are generalisable to a wide range of other application areas. Full code and data for examples, exercises, and some solutions can be found on the book's website.

Everything You Need to Know and Do to Coach Your Agile Project Team to Success As an agile coach, you can help project teams become outstanding at agile development, creating products that make them proud and helping organizations reap the powerful benefits of teams that deliver both innovation and excellence. More and more frequently, ScrumMasters and project managers are being asked to coach agile teams. However, the role of coach is a challenging one that often doesn't exist in traditional application development. Migrating from command and control to agile coaching requires new skills and a whole new mindset. In Coaching Agile Teams, leading agile coach Lyssa Adkins helps you master both so you can guide your agile teams to extraordinary performance. This practical book is packed with ideas, best practices, and checklists you can start using immediately. All of it reflects Adkins's own hard-won experience transitioning to agile coaching from traditional, large-scale project management, including the remarkable lessons she's learned from the teams she's worked with.You'll gain deep insight into the role of the agile coach, discover what works and what doesn't, and learn how to adapt powerful skills from the fields of professional coaching and mentoring. Coverage includes *Understanding what it takes to be a great agile coach*Mastering all of the agile coach's roles: teacher, mentor, problem solver, conflict navigator, and performance coach*Moving from agile team member or project leader to coach*Creating an environment where self-organized, high-performance teams can emerge*Coordinating collaboration *Evolving your leadership style as your team grows and changes*Staying actively engaged without dominating your team and stunting its growth*Operating in failure, recovery, and success modes*Getting the most out of your own personal agile coaching journey Whether you're an agile coach, leader, trainer, mentor, facilitator, ScrumMaster, project manager, product owner, or team member, this book will help you become skilled at helping others become truly great. What could possibly be more rewarding?

This book presents recent non-asymptotic results for approximations in multivariate statistical analysis. The book is unique in its focus on results with the correct error structure for all the parameters involved. Firstly, it discusses the computable error bounds on correlation coefficients, MANOVA tests and discriminant functions studied in recent papers. It then introduces new areas of research in high-dimensional approximations for bootstrap procedures, Cornish-Fisher expansions, power-divergence statistics and approximations of statistics based on observations with random sample size. Lastly, it proposes a general approach for the construction of non-asymptotic bounds, providing relevant examples for several complicated statistics. It is a valuable resource for researchers with a basic understanding of multivariate statistics.

Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control. Additionally, a firm's data-particularly in the case of finance, software, insurance and biotech firms- comprises most of the audited value of the firm. Financial audits are critical mechanisms for ensuring the integrity of information systems and the reporting of organizational finances. They help avoid the abuses that led to passage of legislation such as the Foreign Corrupt Practices Act (1977), and the Sarbanes-Oxley Act (2002). Audit effectiveness has declined over the past two decades as auditor skillsets have failed to keep up with advances in information technology. Information and communication technology lie at the core of commerce today and are integrated in business processes around the world. This book is designed to meet the increasing need of audit professionals to understand information technology and the controls required to manage it. The material included focuses on the requirements for annual Securities and Exchange Commission audits (10-K) for listed corporations. These represent the benchmark auditing procedures for specialized audits, such as internal, governmental, and attestation audits. Using R and RStudio, the book demonstrates how to render an audit opinion that is legally and statistically defensible; analyze, extract, and manipulate accounting data; build a risk assessment matrix to inform the conduct of a cost-effective audit program; and more.

Fulfilling the need for a practical user's guide, Statistics in MATLAB: A Primer provides an accessible introduction to the latest version of MATLAB (R) and its extensive functionality for statistics. Assuming a basic knowledge of statistics and probability as well as a fundamental understanding of linear algebra concepts, this book: Covers capabilities in the main MATLAB package, the Statistics Toolbox, and the student version of MATLAB Presents examples of how MATLAB can be used to analyze data Offers access to a companion website with data sets and additional examples Contains figures and visual aids to assist in application of the software Explains how to determine what method should be used for analysis Statistics in MATLAB: A Primer is an ideal reference for undergraduate and graduate students in engineering, mathematics, statistics, economics, biostatistics, and computer science. It is also appropriate for a diverse professional market, making it a valuable addition to the libraries of researchers in statistics, computer science, data mining, machine learning, image analysis, signal processing, and engineering.

Pro SharePoint 2010 Search gives you expert advice on planning, deploying and customizing searches in SharePoint 2010. Drawing on the authors' extensive experience of working with real-world SharePoint deployments, this book teaches everything you'll need to know to create well-designed SharePoint solutions that always keep the end-user's experience in mind. Increase your search efficiency with SharePoint 2010's search functionality: extend the search user interface using third-party tools, and utilize analytics to improve relevancy. This practical hands-on book is a must-have resource for anyone looking to unlock the full potential of their SharePoint server's search capabilities. Pro SharePoint 2010 Search empowers you to customize a SharePoint 2010 search deployment and maximize the platform's potential for your organization. What you'll learn Design and implement effective search crawls and indexing Create intuitive user interfaces, and improve search findability Understand how to configure core SharePointcomponents Customize SharePoint's existing search functionality

Who this book is for

This book is aimed at intermediate to advanced SharePoint administrators who want to incorporate well-designed search functionality into their sites. Table of Contents Overview of SharePoint 2010 Search Planning Your Search Deployment Setting Up the Crawler Deploying the Search Center The Search User Interface Configuring Search Settings and the User Interface Working with Search Page Layouts Searching Through the API Business Connectivity Services Relevancy and Reporting Search Extensions

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy for a missed minus sign to generate a false prediction that you don't spot until it's too late. Testing is the only way to be sure that your code, and your results, are correct. Testing R Code teaches you how to perform development-time testing using the testthat package, allowing you to ensure that your code works as intended. The book also teaches run-time testing using the assertive package; enabling your users to correctly run your code. After beginning with an introduction to testing in R, the book explores more advanced cases such as integrating tests into R packages; testing code that accesses databases; testing C++ code with Rcpp; and testing graphics. Each topic is explained with real-world examples, and has accompanying exercises for readers to practise their skills - only a small amount of experience with R is needed to get started!

This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed integer, multiobjective and dynamic programming problems. Comparative studies and conclusions on intelligent global solvers are also provided.

This book and app is for practitioners, professionals, researchers, and students who want to learn how to make a plot within the R environment using ggplot2, step-by-step without coding. In widespread use in the statistical communities, R is a free software language and environment for statistical programming and graphics. Many users find R to have a steep learning curve but to be extremely useful once overcome. ggplot2 is an extremely popular package tailored for producing graphics within R but which requires coding and has a steep learning curve itself, and Shiny is an open source R package that provides a web framework for building web applications using R without requiring HTML, CSS, or JavaScript. This manual-"integrating" R, ggplot2, and Shiny-introduces a new Shiny app, Learn ggplot2, that allows users to make plots easily without coding. With the Learn ggplot2 Shiny app, users can make plots using ggplot2 without having to code each step, reducing typos and error messages and allowing users to become familiar with ggplot2 code. The app makes it easy to apply themes, make multiplots (combining several plots into one plot), and download plots as PNG, PDF, or PowerPoint files with editable vector graphics. Users can also make plots on any computer or smart phone. Learn ggplot2 Using Shiny App allows users to Make publication-ready plots in minutes without coding Download plots with desired width, height, and resolution Plot and download plots in png, pdf, and PowerPoint formats, with or without R code and with editable vector graphics

This book focuses the solutions of linear algebra and matrix analysis problems, with the exclusive use of MATLAB. The topics include representations, fundamental analysis, transformations of matrices, matrix equation solutions as well as matrix functions. Attempts on matrix and linear algebra applications are also explored.

This book focuses on solving practical problems in calculus with MATLAB. Descriptions and sketching of functions and sequences are introduced first, followed by the analytical solutions of limit, differentiation, integral and function approximation problems of univariate and multivariate functions. Advanced topics such as numerical differentiations and integrals, integral transforms as well as fractional calculus are also covered in the book.

This book presents fundamentals in MATLAB programming, including data and statement structures, control structures, function writing and bugging in MATLAB programming, followed by the presentations of algebraic computation, transcendental function evaluations and data processing. Advanced topics such as MATLAB interfacing, object-oriented programming and graphical user interface design are also addressed.

QuickBooks 2011 has impressive features, like financial and tax reporting, invoicing, payroll, time and mileage tracking, and online banking. So how do you avoid spending more time learning the software than using it? This Missing Manual puts you in control: you learn not only how QuickBooks works, but why and when to use specific features. You also get basic accounting advice along the way. QuickBooks can handle many of the financial tasks small companies face. With QuickBooks 2011: The Missing Manual, you can handle QuickBooks by following clear, step-by-step instructions that help you get the job done. * Set up your QuickBooks files and preferences to fit your company * Track inventory, control spending, run a payroll, and manage income * Follow the money all the way from customer invoices to year-end reports * Export key snapshots in the convenient new Report Center * Streamline your workflow with the new Online Banking Center * Build and monitor budgets to keep your company financially fit * Share information with your accountant quickly and easily

This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.

This book provides statistical methodologies for time series data, focusing on copula-based Markov chain models for serially correlated time series. It also includes data examples from economics, engineering, finance, sport and other disciplines to illustrate the methods presented. An accessible textbook for students in the fields of economics, management, mathematics, statistics, and related fields wanting to gain insights into the statistical analysis of time series data using copulas, the book also features stand-alone chapters to appeal to researchers. As the subtitle suggests, the book highlights parametric models based on normal distribution, t-distribution, normal mixture distribution, Poisson distribution, and others. Presenting likelihood-based methods as the main statistical tools for fitting the models, the book details the development of computing techniques to find the maximum likelihood estimator. It also addresses statistical process control, as well as Bayesian and regression methods. Lastly, to help readers analyze their data, it provides computer codes (R codes) for most of the statistical methods.

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

This book depicts a wide range of situations in which there exist finite form representations for the Meijer G and the Fox H functions. Accordingly, it will be of interest to researchers and graduate students who, when implementing likelihood ratio tests in multivariate analysis, would like to know if there exists an explicit manageable finite form for the distribution of the test statistics. In these cases, both the exact quantiles and the exact p-values of the likelihood ratio tests can be computed quickly and efficiently. The test statistics in question range from common ones, such as those used to test e.g. the equality of means or the independence of blocks of variables in real or complex normally distributed random vectors; to far more elaborate tests on the structure of covariance matrices and equality of mean vectors. The book also provides computational modules in Mathematica (R), MAXIMA and R, which allow readers to easily implement, plot and compute the distributions of any of these statistics, or any other statistics that fit into the general paradigm described here.

This book sheds light on cross-industry and industry-specific trends in today's digital economy. Prepared by a group of international researchers, experts and practitioners under the auspices of SAP's Digital Thought Leadership & Enablement team within SAP's Business Transformation Services (BTS) unit, the book furthermore presents relevant use cases in digital transformation and innovation. The book argues that breakthrough technologies have matured and hit scale together, enabling five defining trends: hyper-connectivity, supercomputing, cloud computing, a smarter world, and cyber security. It presents in detail how companies are now reimagining their products and services, business models and processes, showcasing how every business today is a digital business. Digitalization, defined as the process of moving to a digital business, is no longer a choice but an imperative for all businesses across all industries and regions. Taking a step toward becoming a digital enterprise is demanding and challenging. The dimensions of customer centricity, leadership and strategy, business models, including offerings (products and services), processes, structure and governance, people and skills, culture, and technology foundation can serve as orientation for digitalization. The articles in this book touch on all dimensions of this digital innovation and transformation framework and offer possible answers to some of the pressing questions that arise when practitioners seek to digitalize their business.

Mathematical Statistics with Applications in R, Third Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods, such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem-solving in a logical manner. Step-by-step procedure to solve real problems make the topics very accessible.