Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Sampling (Statistics)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"A state-of-the-art presentation of optimum spatio-temporal sampling design - bridging classic ideas with modern statistical modeling concepts and the latest computational methods.Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem at hand.Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to discuss optimum spatio-temporal sampling design.Spatio-temporal Design: Advances in Efficient Data Acquisition: Provides an up-to-date account of how to collect space-time data for monitoring, with a focus on statistical aspects and the latest computational methods Discusses basic methods and distinguishes between design and model-based approaches to collecting space-time data. Features model-based frequentist design for univariate and multivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout the book in order to demonstrate the different approaches and their integration. Includes real data sets, data generating mechanisms and simulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book for graduate level students as well as a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences"-- "Provides a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition"--

Sampling (Statistics) --- Spatial analysis (Statistics)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Sampling (Statistics) --- Social surveys --- Response rate

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Jason Gibson explains how to calculate population and sample variances. He explains the difference between these two variances and gives examples of each.

Population research. --- Population --- Sampling (Statistics) --- Analysis of variance. --- Statistical methods.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and limitations, and the skills needed to take advantage of compressive sensing in wireless networks.

Coding theory. --- Data compression (Telecommunication) --- Signal processing --- Sampling (Statistics) --- Compressed sensing (Telecommunication) --- Digital techniques.