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Kernel smoothing has greatly evolved since its inception to become an essential methodology in the data science tool kit for the 21st century. Its wid...Lees meer
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Statistical methods for sequential hypothesis testing and changepoint detection have applications across many fields. This book presents an overview o...Lees meer
Kernal Smoothing provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilitated b...Lees meer
Written by pioneers in an exciting new field, this book introduces the application of polynomial algebra to experimental design, discrete probability,...Lees meer
This book covers recent advances in the field, including vine copula modeling of high-dimensional data. The author develops vine copula models and gen...Lees meer
Bovine Spongiform Encephalopathy (BSE) or "mad cow disease," first diagnosed in late 1986, is transmitted through feed, indirect horizontal transmissi...Lees meer
Extreme value theory (EVT) provides tools for assessing risk of highly unusual developments, such as financial market crashes. This book presents a sy...Lees meer
This book describes the properties of stochastic probabilistic models and develops the applied mathematics of stochastic point processes. It is useful...Lees meer
Bayesian nonparametric (BNP) methods can be used to flexibly model joint or conditional distributions, as well as functional relationships. These meth...Lees meer
Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique...Lees meer
Energy statistics are functions of distances between statistical observations in metric spaces. The authors hope this book will spark the interest of ...Lees meer
This book addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. It...Lees meer