More by Robin Lovelace, Morgane Dumont
Harry J Hoople, retired chemist, shop owner, Auschwitz survivor and keeper of an ancient wish machine, wondered if the stardust would bring something good...or something very, very bad.
When Harry saw the green station wagon with Kentucky license plates roll by, he braced himself, because he knew this meant the something had arrived.
Eleven year-old Will saw the station wagon too. He hoped it meant there were new kids moving into Fountain Square. Will was right. The station wagon carried the Avery family, including a strange kid named Mott and his beautiful older sister named Selma.
Mott and Will and their two friends Dallas and Kevin, soon embark on a summer filled with magic wishes and un-intended consequences. From finding hidden treasure to witnessing a murder, to receiving an enchanted bean brought all the way from Bombay, the boys face a lot of problems.
Selma falls into some problems too. She must decide if she wants to marry into a life of privilege or run away to New York with her true love. Like Will’s father says, Selma is playing with fire.
Only Hoople and his wish machine could help. But Hoople gives out wishes sparingly. Would he grant the boys one more chance to make things right?
Stardust can do peculiar things to a neighborhood.
Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language.
Get Insight into Complex Behaviors
The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility.
Implement the Methods on Your Own Data
Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.
Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming.Get advice for setting up an R programming environmentExplore general programming concepts and R coding techniquesUnderstand the ingredients of an efficient R workflowLearn how to efficiently read and write data in RDive into data carpentry—the vital skill for cleaning raw dataOptimize your code with profiling, standard tricks, and other methodsDetermine your hardware capabilities for handling R computationMaximize the benefits of collaborative R programmingAccelerate your transition from R hacker to R programmer