{"product_id":"9783032207890","title":"Space-Time Point Processes An Applied Statistics Course","description":"\u003ch3\u003eSpringer Texts in Statistics\u003c\/h3\u003e\u003ch1\u003eSpace-Time Point Processes\u003c\/h1\u003e\u003ch2\u003eAn Applied Statistics Course\u003c\/h2\u003e\u003ch3\u003eFrederic Schoenberg\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eThe book focuses on applied methodology, and summarizes the main issues in the practical applications associated with space-time point processes. In particular, the questions addressed in this book are:\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cul type=\"disc\"\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eHow can one summarize space-time point process data?\u003c\/span\u003e\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eHow are space-time point processes modeled?\u003c\/span\u003e\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eWhat are the different ways of estimating parameters in space-time point process models, and how do they compare?\u003c\/span\u003e\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eHow can space-time point process models be estimated non-parametrically?\u003c\/span\u003e\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eWhat techniques exist for assessing how well a space-time point process model fits to data, or for comparing the fit of multiple models?\u003c\/span\u003e\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan; mso-list: l0 level1 lfo1; tab-stops: list .5in;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eHow can one use a space-time point process model to forecast the probability of future events? \u003c\/span\u003e\u003c\/li\u003e\r\n\u003c\/ul\u003e\r\n\u003cp class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eApplied examples are used throughout the book, and the text includes R code for implementing all the techniques discussed in the book. The book covers standard, classical methods for point processes, such as Poisson processes, Cox processes, Neyman-Scott processes, Hawkes models, conditional intensities, kernel smoothing, and Ripley's K-function, and also describes important recent advances for space-time point processes, such as Model-Independent Stochastic Declustering (MISD), Stoyan-Grabarnik parameter estimation, Voronoi deviance residuals, and super-thinned residuals.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto; line-height: normal; mso-pagination: widow-orphan;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: EN-US;\"\u003eThe book is meant to be used for teaching at the graduate or undergraduate levels. Sample exercises are given at the end of each chapter, and these problems are not too difficult and thus suitable for undergraduate or graduate students in applied statistics. The goal is to educate and train students in the practical aspects of the summary, description and forecasting of spatial-temporal point process data.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\" style=\"margin-bottom: .0001pt; line-height: normal;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Yu Mincho'; mso-font-kerning: 0pt; mso-ligatures: none; mso-fareast-language: JA;\"\u003e \u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\" style=\"margin-bottom: .0001pt; line-height: normal;\"\u003e\u003cstrong style=\"mso-bidi-font-weight: normal;\"\u003e\u003cspan style=\"font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Yu Mincho'; mso-fareast-language: JA;\"\u003e \u003c\/span\u003e\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cp class=\"MsoNormal\" style=\"margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal;\"\u003e\u003cstrong\u003e\u003cspan style=\"mso-bidi-font-size: 11.0pt; font-family: 'Calibri',sans-serif;\"\u003eFrederic Schoenberg\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"mso-bidi-font-size: 11.0pt; font-family: 'Calibri',sans-serif;\"\u003e has been a professor of Statistics at UCLA since 1998, serving as Chair of Statistics from 2012 to 2015 and Director of the Masters of Applied Statistics program since 2018. His research specializes in point processes and their applications in the environmental sciences, especially to the study of earthquakes, wildfires, crimes, and epidemic diseases. He is Associate Editor for \u003cem\u003e\u003cspan style=\"font-family: 'Calibri',sans-serif;\"\u003eAnnals of Applied Statistics\u003c\/span\u003e\u003c\/em\u003e, founder and co-Editor of the \u003cem\u003e\u003cspan style=\"font-family: 'Calibri',sans-serif;\"\u003eJournal of Environmental Statistics\u003c\/span\u003e\u003c\/em\u003e, and Board Member of \u003cem\u003e\u003cspan style=\"font-family: 'Calibri',sans-serif;\"\u003eInternational Journal of Environmental Research and Public Health\u003c\/span\u003e\u003c\/em\u003e (IJERPH) Section for Health Care Sciences and Services. In 2017, he published the 2nd edition of his book,\u003cem\u003e\u003cspan style=\"font-family: 'Calibri',sans-serif;\"\u003e An Introduction to Probability with Texas Hold'em Examples.\u003c\/span\u003e\u003c\/em\u003e\u003c\/span\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e23 July 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Switzerland\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032207890\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e133\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":46265555222668,"sku":"9783032207890","price":107.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032207890.jpg?v=1781056889","url":"https:\/\/lateknightbooks.com\/products\/9783032207890","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}