This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.

Master the syntax for working with R's plotting functions in graphics and stats in this easy reference to formatting plots. The approach in Visualizing Data in R 4 toward the application of formatting in ggplot() will follow the structure of the formatting used by the plotting functions in graphics and stats. This book will take advantage of the new features added to R 4 where appropriate including a refreshed color palette for charts, Cairo graphics with more fonts/symbols, and improved performance from grid graphics including ggplot 2 rendering speed. Visualizing Data in R 4 starts with an introduction and then is split into two parts and six appendices. Part I covers the function plot() and the ancillary functions you can use with plot(). You'll also see the functions par() and layout(), providing for multiple plots on a page. Part II goes over the basics of using the functions qplot() and ggplot() in the package ggplot2. The default plots generated by the functions qplot() and ggplot() give more sophisticated-looking plots than the default plots done by plot() and are easier to use, but the function plot() is more flexible. Both plot() and ggplot() allow for many layers to a plot. The six appendices will cover plots for contingency tables, plots for continuous variables, plots for data with a limited number of values, functions that generate multiple plots, plots for time series analysis, and some miscellaneous plots. Some of the functions that will be in the appendices include functions that generate histograms, bar charts, pie charts, box plots, and heatmaps. What You Will Learn Use R to create informative graphics Master plot(), qplot(), and ggplot() Discover the canned graphics functions in stats and graphics Format plots generated by plot() and ggplot() Who This Book Is For Those in data science who use R. Some prior experience with R or data science is recommended.

This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics. The coverage is comprehensive, ranging from the underlying theory to computational implementation, methodology, and diverse applications in various areas of science. This is achieved by describing SMC algorithms as particular cases of a general framework, which involves concepts such as Feynman-Kac distributions, and tools such as importance sampling and resampling. This general framework is used consistently throughout the book. Extensive coverage is provided on sequential learning (filtering, smoothing) of state-space (hidden Markov) models, as this remains an important application of SMC methods. More recent applications, such as parameter estimation of these models (through e.g. particle Markov chain Monte Carlo techniques) and the simulation of challenging probability distributions (in e.g. Bayesian inference or rare-event problems), are also discussed. The book may be used either as a graduate text on Sequential Monte Carlo methods and state-space modeling, or as a general reference work on the area. Each chapter includes a set of exercises for self-study, a comprehensive bibliography, and a "Python corner," which discusses the practical implementation of the methods covered. In addition, the book comes with an open source Python library, which implements all the algorithms described in the book, and contains all the programs that were used to perform the numerical experiments.

This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.

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.

This book presents the best papers from the 1st International Conference on Mathematical Research for Blockchain Economy (MARBLE) 2019, held in Santorini, Greece. While most blockchain conferences and forums are dedicated to business applications, product development or Initial Coin Offering (ICO) launches, this conference focused on the mathematics behind blockchain to bridge the gap between practice and theory. Every year, thousands of blockchain projects are launched and circulated in the market, and there is a tremendous wealth of blockchain applications, from finance to healthcare, education, media, logistics and more. However, due to theoretical and technical barriers, most of these applications are impractical for use in a real-world business context. The papers in this book reveal the challenges and limitations, such as scalability, latency, privacy and security, and showcase solutions and developments to overcome them.

This book discusses enterprise hierarchies, which view a target system with varying degrees of abstraction. These requirement refinement hierarchies can be represented by goal models. It is important to verify that such hierarchies capture the same set of rationales and intentions and are in mutual agreement with the requirements of the system being designed. The book also explores how hierarchies manifest themselves in the real world by undertaking a data mining exercise and observing the interactions within an enterprise. The inherent sequence-agnostic property of goal models prevents requirement analysts from performing compliance checks in this phase as compliance rules are generally embedded with temporal information. The studies discussed here seek to extract finite state models corresponding to goal models with the help of model transformation. The i*ToNuSMV tool implements one such algorithm to perform model checking on i* models. In turn, the AFSR framework provides a new goal model nomenclature that associates semantics with individual goals. It also provides a reconciliation machinery that detects entailment or consistency conflicts within goal models and suggests corrective measures to resolve such conflicts. The authors also discuss how the goal maintenance problem can be mapped to the state-space search problem, and how A* search can be used to identify an optimal goal model configuration that is free from all conflicts. In conclusion, the authors discuss how the proposed research frameworks can be extended and applied in new research directions. The GRL2APK framework presents an initiative to develop mobile applications from goal models using reusable code component repositories.

Harness the power of Salesforce to manage and grow your business. This book shows you how to use the Salesforce CRM tool to consolidate consumer data into a single place to gain better insight into your business and more easily manage data. Data (such as email, spreadsheets, databases) is generated through the front office or face of your business, where your company interacts with customers and revenue is generated. In a hotel, for instance, the front office is the lobby where guests are greeted, their problems are handled, and room payments are made. Another example is a coffee shop, where the front office is an employee taking a customer's order or serving a drink. Salespeople connect to customers by selling your company's goods or services. Marketing team members connect with them through advertising and promotional activities. Service and support staff assist customers with problems and provide help with products. This book introduces the many ways Salesforce-based innovations are transforming the technology landscape and the strategies that may be used for designing and launching a digital front office. The book examines how organizations can launch and grow digital solutions and strategies for the governance of the platform and provides an overview of digital transformation across industries. What You Will Learn Understand basic Salesforce concepts, including the digital front office process tower, lead to cash journey, core CRM functions, best practices, and more Review data management concepts, integrated sales, customer service, marketing operations, and proposal and business development needs in a systematic way Use frameworks to build a business architecture and multi-year technology roadmap Get familiar with Salesforce business processes and concepts such as account, contact, lead, and opportunity management; marketing campaigns; master data management (MDM); and lead scoring, grading, and activity management across the front office Define and develop digital marketing challenges and strategy (people, process, brand, messaging, and ROI), measure campaign data, and create an end-to-end campaign in Salesforce Who This Book Is For Business executives, C-suites, IT management, and Salesforce managers and professionals working in IT, business development, sales operations, program management, marketing operations, and proposal development

Learn from Pro SharePoint Migration on how to migrate your existing farm - infrastructure, upgrade approaches, code, branding, and impact of new features of SharePoint 2010 - in a strategic way that results in smooth transition. Noted author Sahil Malik, with Srini Sistla, work together to provide detailed strategies and tools to assess, plan and execute a SharePoint 2010 migration that is efficient and cost-effective--and that doesn't use expensive third-party software. The clean slate approach embraced by this book, coupled with flexible tools designed by Microsoft and the author, will provide you with the statistics, charts, and diagrams necessary to perform a meaningful assessment of your current SharePoint 2007 environment. You'll then be able to plan the lowest-cost, least-hassle way to migrate your current environment, and its applications and data, to SharePoint 2010, and how to map your existing use of SharePoint 2007 to the new features and enhancements in SharePoint 2010. Pro SharePoint Migration will help you: * Gain a better understanding of high level comparison and changes you need to learn between the two versions * To migrate or not?Learn about new functionality that might replace your existing custom built code or non-code based solutions.* Build a strong toolset to create, update, administer, and migrate 90% of the most commonly used SharePoint objects * Grasp the intricacies of the SharePoint 2010 application programming interface (API) * Become a better SharePoint 2010 administrator in your newly-migrated environment What you'll learn * A high level comparison of MOSS 2007 and SharePoint 2010, asking what's new * Available supported and unsupported upgrade choices * Migration strategies to minimize disruption * Strategies for migrating old settings to new * Changes to security model, lists, libraries, and more * Visual changes, the impact on branding, and how to address overall branding artifacts * Statistics, monitoring and usage analysis of existing and new farms * Learn about ribbon changes and customizations * A discussion of being a savvy business user developer, using SharePoint designer 2010 and InfoPath 2010 * Overview of new changes and enhancements to enterprise content management features * Changes to SharePoint APIs Who this book is for Pro SharePoint Migration is for intermediate to advanced SharePoint administrators, and developers who are interested in migrating from SharePoint 2007 to SharePoint 2010 without third-party software.

This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.

This book is a short, focused introduction to Mathematica, the comprehensive software system for doing mathematics. Written for the novice, this engaging book contains an explanation of essential Mathematica commands, as well as the rich Mathematica interface for preparing polished technical documents. Mathematica can be used to graph functions, solve equations, perform statistics tests, and much more. In addition, it incorporates word processing and desktop publishing features for combining mathematical computations with text and graphics, and producing polished, integrated, interactive documents. You can even use it to create documents and graphics for the Web. This book explains everything you need to know to begin using Mathematica to do all these things and more. Written for Mathematica version 3, this book can also be used with earlier versions of the software. Intermediate and advanced users may even find useful information here, especially if they are making the switch to version 3 from an earlier version.

The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed. These methods often yield high quality solutions with a more reasonable use of computational resources (e.g. memory and processing effort). Examples of popular modern methods discussed in this book are: simulated annealing; tabu search; genetic algorithms; differential evolution; and particle swarm optimization. This book is suitable for undergraduate and graduate students in computer science, information technology, and related areas, as well as data analysts interested in exploring modern optimization methods using R. This new edition integrates the latest R packages through text and code examples. It also discusses new topics, such as: the impact of artificial intelligence and business analytics in modern optimization tasks; the creation of interactive Web applications; usage of parallel computing; and more modern optimization algorithms (e.g., iterated racing, ant colony optimization, grammatical evolution).

This book discusses the development of the Rosenbrock-Wanner methods from the origins of the idea to current research with the stable and efficient numerical solution and differential-algebraic systems of equations, still in focus. The reader gets a comprehensive insight into the classical methods as well as into the development and properties of novel W-methods, two-step and exponential Rosenbrock methods. In addition, descriptive applications from the fields of water and hydrogen network simulation and visual computing are presented.

Want to use the power of R sooner rather than later? Don't have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides the building blocks you need to fit R's astounding capabilities to your analytics, reporting, and visualization needs. CRAN Recipes recognizes how needless jargon and complexity get in your way. Busy professionals need simple examples and intuitive descriptions; side trips and meandering philosophical discussions are left for other books. Here R scripts are condensed, to the extent possible, to copy-paste-run format. Chapters and examples are structured to purpose rather than particular functions (e.g., "dirty data cleanup" rather than the R package name "janitor"). Everyday language eliminates the need to know functions/packages in advance. What You Will Learn Carry out input/output; visualizations; data munging; manipulations at the group level; and quick data exploration Handle forecasting (multivariate, time series, logistic regression, Facebook's Prophet, and others) Use text analytics; sampling; financial analysis; and advanced pattern matching (regex) Manipulate data using DPLYR: filter, sort, summarize, add new fields to datasets, and apply powerful IF functions Create combinations or subsets of files using joins Write efficient code using pipes to eliminate intermediate steps (MAGRITTR) Work with string/character manipulation of all types (STRINGR) Discover counts, patterns, and how to locate whole words Do wild-card matching, extraction, and invert-match Work with dates using LUBRIDATE Fix dirty data; attractive formatting; bad habits to avoid Who This Book Is For Programmers/data scientists with at least some prior exposure to R.

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11-13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG's goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.

Write automated unit tests for the ABAP language. This book teaches programmers using simple examples and metaphors and explains the underlying concepts of writing effective automated unit tests. Many, if not most, ABAP programmers learned their programming and testing skills before the ABAP development environment provided an automated unit testing facility. Automated Unit Testing with ABAP: A Practical Approach offers hope and salvation to ABAP programmers who continue to toil with antiquated manual unit testing processes, taking them by the hand and lifting them out of that dungeon of despair with a modern and proven alternative. It begins by explaining how the xUnit family of automated testing frameworks provides a quick and effective means of insuring high-quality software. It then focuses on the ABAP Unit Testing Facility, the xUnit framework applicable specifically to the ABAP language, showing how it can be used to bring ABAP applications under automated testing control, from old legacy applications to those newly written. Whereas xUnit testing has been widely accepted with developers writing in many other programming languages, it is an unfortunate fact in the ABAP community that many programmers still are unfamiliar with xUnit concepts and do not know how to begin implementing automated unit testing into their development process. This book demonstrates how to refactor programs so they become designed for testability, showing how to use process encapsulation and test isolation to facilitate automated testing, including a thorough explanation of test-driven development and the use of test doubles. The book: Shows how to write automated unit tests for ABAP Instills ABAP programmers with the confidence to refactor poorly written code Explains how an automated testing harness facilitates rapid software development Teaches how to utilize test-driven development (TDD) with ABAP Offers advice and tips on the best ways to write automated unit tests What You Will Learn Become familiar with the xUnit approach to testing Know the ABAP statements that interfere with running automated unit tests and how to accommodate them Understand what it means to isolate code for testing and how this is achieved Gain the confidence to refactor poorly written code Make ABAP programs designed for testability Reap the benefits of spending less time manually unit testing ABAP programs Use test-driven development (TDD) with ABAP programming Use configurable test doubles in ABAP Who This Book Is For ABAP programmers who remain unfamiliar with the automated unit testing facility and those who already use it but want to improve their skill writing and using automated tests. The book addresses the reluctance and trepidation felt by procedural ABAP programmers who need to know some object-oriented concepts to use this facility, expands their horizons, and helps them step through the doorway leading to a different approach to program design.

Confidently shepherd your organization's implementation of Microsoft Dynamics 365 to a successful conclusion In Mastering Microsoft Dynamics 365 Implementations, accomplished executive, project manager, and author Eric Newell delivers a holistic, step-by-step reference to implementing Microsoft's cloud-based ERP and CRM business applications. You'll find the detailed and concrete instructions you need to take your implementation project all the way to the finish line, on-time, and on-budget. You'll learn: The precise steps to take, in the correct order, to bring your Dynamics 365 implementation to life What to do before you begin the project, including identifying stakeholders and building your business case How to deal with a change management throughout the lifecycle of your project How to manage conference room pilots (CRPs) and what to expect during the sessions Perfect for CIOs, technology VPs, CFOs, Operations leaders, application directors, business analysts, ERP/CRM specialists, and project managers, Mastering Microsoft Dynamics 365 Implementations is an indispensable and practical reference for guiding your real-world Dynamics 365 implementation from planning to completion.

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing methodological and computational aspects, as well as real-world applications. It covers topics like classification, confidence bands, density estimation, depth, diagnostic tests, dimension reduction, estimation on manifolds, high- and infinite-dimensional statistics, inference on functional data, networks, operatorial statistics, prediction, regression, robustness, sequential learning, small-ball probability, smoothing, spatial data, testing, and topological object data analysis, and includes applications in automobile engineering, criminology, drawing recognition, economics, environmetrics, medicine, mobile phone data, spectrometrics and urban environments. The book gathers selected, refereed contributions presented at the Fifth International Workshop on Functional and Operatorial Statistics (IWFOS) in Brno, Czech Republic. The workshop was originally to be held on June 24-26, 2020, but had to be postponed as a consequence of the COVID-19 pandemic. Initiated by the Working Group on Functional and Operatorial Statistics at the University of Toulouse in 2008, the IWFOS workshops provide a forum to discuss the latest trends and advances in functional statistics and related fields, and foster the exchange of ideas and international collaboration in the field.

Ready for SAP SuccessFactors Employee Central? First, master the Employee Central workforce admin functionality for hiring, time sheets, benefits, payments, and termination. Next, learn to configure permissions, implement mass changes, and set up workflows, company structures, and business rules. Finally, explore integration with SAP and third-party applications to get the most out of your HR setup. From implementation to operations, this Employee Central book has it all! Highlights include: 1) Time sheets 2) Benefits management 3) Payment 4) Time management 5) Workforce management 6) Mass changes 7) Implementation and integration 8) Reporting 9) Data import and migration 10) SAP SuccessFactors HCM Suite 11) Intelligent services

Explore the architecture, product offerings, and the various stages of implementation processes in Azure DevOps. The book starts with the basic concepts of DevOps and moves on to discuss project management in Azure DevOps. Next, you will learn requirement management and version control in DevOps. Along the way, you will go through test management followed by continuous integration and build automation with more details on code quality and security implementations. Moving forward, you will learn release pipeline and infrastructure as code implementation including ARM-based environment provisioning and execution. Finally, you'll cover DevOps architecture blueprints used for deploying your web applications to different platforms . After reading this book, you will be able to understand each stage of Azure DevOps and master its implementation. What You Will Learn Understand the various concepts of Azure DevOps Apply DevOps concepts in a variety of application contexts including web applications, containers, and database Understand the implementation of end-to-end DevOps in Azure Work with the different DevOps design patterns and architectures in Azure Who Is This Book For: Developers and architects working with Azure.

This book features selected papers from the 5th International Conference on Mathematics and Computing (ICMC 2019), organized by the School of Computer Engineering, Kalinga Institute of Industrial Technology Bhubaneswar, India, on February 6 - 9, 2019. Covering recent advances in the field of mathematics, statistics and scientific computing, the book presents innovative work by leading academics, researchers and experts from industry.

This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins by explaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.

Testing for economic convergence across countries has been a central issue in the literature of economic growth and development. This book introduces a modern framework to study the cross-country convergence dynamics in labor productivity and its proximate sources: capital accumulation and aggregate efficiency. In particular, recent convergence dynamics of developed as well as developing countries are evaluated through the lens of a non-linear dynamic factor model and a clustering algorithm for panel data. This framework allows us to examine key economic phenomena such as technological heterogeneity and multiple equilibria. In this context, the book provides a succinct review of the recent club convergence literature, a comparative view of developed and developing countries, and a tutorial on how to implement the club convergence framework in the statistical software Stata.

This book presents the state of the art on numerical semigroups and related subjects, offering different perspectives on research in the field and including results and examples that are very difficult to find in a structured exposition elsewhere. The contents comprise the proceedings of the 2018 INdAM "International Meeting on Numerical Semigroups", held in Cortona, Italy. Talks at the meeting centered not only on traditional types of numerical semigroups, such as Arf or symmetric, and their usual properties, but also on related types of semigroups, such as affine, Puiseux, Weierstrass, and primary, and their applications in other branches of algebra, including semigroup rings, coding theory, star operations, and Hilbert functions. The papers in the book reflect the variety of the talks and derive from research areas including Semigroup Theory, Factorization Theory, Algebraic Geometry, Combinatorics, Commutative Algebra, Coding Theory, and Number Theory. The book is intended for researchers and students who want to learn about recent developments in the theory of numerical semigroups and its connections with other research fields.

This book covers applications of R to the general discipline of radiation dosimetry and to the specific areas of luminescence dosimetry, luminescence dating, and radiation protection dosimetry. It features more than 90 detailed worked examples of R code fully integrated into the text, with extensive annotations. The book shows how researchers can use available R packages to analyze their experimental data, and how to extract the various parameters describing mathematically the luminescence signals. In each chapter, the theory behind the subject is summarized, and references are given from the literature, so that researchers can look up the details of the theory and the relevant experiments. Several chapters are dedicated to Monte Carlo methods, which are used to simulate the luminescence processes during the irradiation, heating, and optical stimulation of solids, for a wide variety of materials. This book will be useful to those who use the tools of luminescence dosimetry, including physicists, geologists, archaeologists, and for all researchers who use radiation in their research.