Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book …
This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. Each chapter is complemented by numerous exercises, many of them with detailed solutions, and computer labs in R that convey valuable practical insights. The book cover…
This book discusses quantum theory as the theory of random (Brownian) motion of small particles (electrons etc.) under external forces. Implying that the Schrödinger equation is a complex-valued evolution equation and the Schrödinger function is a complex-valued evolution functi…
The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristi…
1. What is a Stochastic Process? -- 2. The Simple Random Walk I: Associated Boundary Value Distributions, Transience and Recurrence -- 3. The Simple Random Walk II: First Passage Times -- 4. Multidimensional Random Walk -- 5. The Poisson Process, Compound Poisson Process, and Po…
Il volume fornisce un'introduzione a teoria e applicazioni dei modelli lineari generalizzati. Si presentano modelli di regressione per risposte continue, binarie, categoriali e di conteggio. Si offre anche un'introduzione ai modelli per risposte correlate. Utilizzando il softwar…
Statistical Signal Processing: Frequency Estimation
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 observat…
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 est…
Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2016 for Engineering Statistics, this volume is a step-by-step, exercise-driven guide f…
Newly revised to specifically address Microsoft Excel 2019, this book shows the capabilities of Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2016 for Engineering Statistics, this volume is a step-by-step, exercise-driven guide f…
Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 20…