Foundations of statistical algorithms. With references to R packages (Q2871231)

This book represents a new and modern approach to presenting the foundations of statistical algorithms. It differs from other books on the market for at least three reasons:{\parindent=8mmNEWLINENEWLINE\begin{itemize}\item[(i)] it covers the historical development and clarifies the evolution of more powerful algorithms, NEWLINE\item[(ii)] it emphasizes certain recurring themes in all statistical algorithms, such as computation, assessment and verification, iteration, intuition, randomness, repetition scalability, and parallelization, NEWLINE\item[(iii)] it covers two topics neglected in other books, namely, systematic verification and scalability.NEWLINENEWLINE\end{itemize}}NEWLINENEWLINEEach chapter offers examples, exercises and solutions to the selected exercises. It also provides access to a website with supplementary material: program code for selected figures, simulations, and exercises. Most exercises are considered to be solved using \texttt{R}.NEWLINENEWLINEThe book is suitable for readers who not only want to understand current statistical algorithms, but also gain a deeper understanding of how the algorithms are constructed and how they operate. It is addressed first and foremost to students and lecturers teaching the foundations of statistical algorithms.