Books by Daniel Mandallaz

Containing many recent developments available for the first time in book form, this concise and up-to-date work presents the statistical concepts and tools needed to conduct a modern forest inventory. It develops the Monte Carlo approach for both simple and complex sampling schemes and explores design-based, model-assisted, and model-dependent inference, including geostatistics and Kriging procedures. The book also explains the design of optimal sampling schemes based on anticipated variance, introduces the g-weight technique for variance estimation, and presentsthe stereological approach to transect sampling. In addition, it includes numerous case studies, simulations, and instructive problems with solutions.

Presents the concepts and tools required in finite populations, and develops the Monte Carlo approach in infinite populations to analyze or design complex forest inventories. This book discusses design-based, model-assisted, and model-dependent inference as well as the design of optimal sampling schemes based on the anticipated variance.