Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than 200 full colour figures. • Includes many exercises to supplement understanding, with separate solutions available from the author. • Supported by a website with full code available to reproduce all methods and examples. The book is primarily designed as a textbook for postgraduate students studying GP regression from mathematics, statistics, computer science, and engineering. Given the breadth of examples, it could also be used by researchers from these fields, as well as from economics, life science, social science, etc.

Computer simulation experiments are essential to modern scientific discovery, whether that be in physics, chemistry, biology, epidemiology, ecology, engineering, etc. Surrogates are meta-models of computer simulations, used to solve mathematical models that are too intricate to be worked by hand. Gaussian process (GP) regression is a supremely flexible tool for the analysis of computer simulation experiments. This book presents an applied introduction to GP regression for modelling and optimization of computer simulation experiments. Features: • Emphasis on methods, applications, and reproducibility. • R code is integrated throughout for application of the methods. • Includes more than 200 full colour figures. • Includes many exercises to supplement understanding, with separate solutions available from the author. • Supported by a website with full code available to reproduce all methods and examples. The book is primarily designed as a textbook for postgraduate students studying GP regression from mathematics, statistics, computer science, and engineering. Given the breadth of examples, it could also be used by researchers from these fields, as well as from economics, life science, social science, etc.

Surrogates is a graduate textbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling, design of experiments, and optimization. Experimentation through simulation, management of dynamic processes, online and real-time analysis, automation and practical application are at the forefro

The year is 2054, and life has been reduced to a data feed. The fusing of virtual reality and cybernetics has ushered in the era of the surrogate, a new technology that lets users interact with the world without ever leaving their homes. It's a perfect world, and it's up to Detectives Harvey Greer and Pete Ford of the Metro Police Department to keep it that way. But to do so they'll need to stop a techno-terrorist bent on returning society to a time when people lived their lives instead of merely experiencing them. Welcome to The Surrogates, a daring, five-issue, full-color miniseries from Top Shelf Productions. First released ten years ago, when social media was in its infancy, The Surrogates anticipated numerous trends that have emerged with the ever-increasing confluence of technology and social connection. Nowhere is this more evident than in its exploration of identity, remote interaction, and the masks we hide behind. Now is the time to discover—or rediscover—this ground-breaking modern classic; it's never been more relevent.

If you need help having a baby, reproductive technology can supply the answer. But it also raises a host of questions that won’t arise until after the child is born: What will you say to “Where did I come from?” when the answer includes a donor or surrogate? Will knowing the truth about how you conceived make your child love you less? Will having a baby with someone else strain your relationship with your spouse or partner? What will grandparents, family members, friends, and coworkers think? Dr. Diane Ehrensaft--a developmental and clinical psychologist who’s worked with families formed using assisted reproductive technology for more than 20 years--helps you anticipate the big questions and find solutions that are right for you and your loved ones. Dr. Ehrensaft offers information, support, and straightforward advice for coping with private worries, confronting public prejudices, and raising happy, healthy children. Single or married, straight or gay, anyone looking forward to the joys and challenges of building a family with the help of a donor or surrogate will discover a wealth of thought-provoking ideas and fresh insights in this sensitive, practical, and positive book.