Discovering Statistics Using R

This 5th edition of this popular graduate textbook, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. It includes numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The R package 'astsa' has had major updates and the text will reflect those updates. In general, the graphics have been improved. New topics include random number generation, modeling and fitting predator-prey interactions, more emphasis on structural models, testing for linearity, discussion of EM algorithm is more extensive, Bayesian analysis of state space models and MCMC is more extensive (including new scripts in astsa), particle methods are introduced, stochastic volatility coverage is expanded, changepoint detection is introduced (new topic).The

This book uniquely presents accurate and up-to-date information related to crops in small and fragmented agricultural lands with mixed cropping patterns. The book involves research using remote sensing (RS), Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to develop crop inventories in three growing seasons in three villages across India to inform decision makers and planners on best practices for agricultural management. The data analysis of crop details using various geospatial technologies fills in gaps in statistical agriculture research, and provides reliable, replicable and efficient methods for generating agricultural statistics. The book will be of interest to statisticians, planners and decision makers in crop management and production.