Modern Statistical Methods for Spatial and Multivariate Data eBook

Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please send contact us.
Compatible Devices: Can be read on any devices.

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field.  In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.

This is a digital product.

Modern Statistical Methods for Spatial and Multivariate Data is written by Norou Diawara and published by Springer. The Digital and eTextbook ISBNs for Modern Statistical Methods for Spatial and Multivariate Data are 9783030114312, 3030114317 and the print ISBNs are 9783030114305, 3030114309.