Randomness and Optimal Estimation in Data Sampling PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Randomness and Optimal Estimation in Data Sampling PDF full book. Access full book title Randomness and Optimal Estimation in Data Sampling by M. Khoshnevisan, S. Saxena, H. P. Singh, S. Singh, F. Smarandache. Download full books in PDF and EPUB format.
Author: M. Khoshnevisan, S. Saxena, H. P. Singh, S. Singh, F. Smarandache
Publisher: Infinite Study
ISBN: 1931233683
Category : Estimation theory
Languages : en
Pages : 63
Get Book Here
Book Description
Author: M. Khoshnevisan, S. Saxena, H. P. Singh, S. Singh, F. Smarandache
Publisher: Infinite Study
ISBN: 1931233683
Category : Estimation theory
Languages : en
Pages : 63
Get Book Here
Book Description
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
Get Book Here
Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: Sarjinder Singh
Publisher: Springer Science & Business Media
ISBN: 9781402017070
Category : Mathematics
Languages : en
Pages : 640
Get Book Here
Book Description
A comprehensive expose of basic and advanced sampling techniques along with their applications in the diverse fields of science and technology.
Author: S. Singh
Publisher: Springer Science & Business Media
ISBN: 9400707894
Category : Medical
Languages : en
Pages : 1242
Get Book Here
Book Description
This book is a multi-purpose document. It can be used as a text by teachers, as a reference manual by researchers, and as a practical guide by statisticians. It covers 1165 references from different research journals through almost 1900 citations across 1194 pages, a large number of complete proofs of theorems, important results such as corollaries, and 324 unsolved exercises from several research papers. It includes 159 solved, data-based, real life numerical examples in disciplines such as Agriculture, Demography, Social Science, Applied Economics, Engineering, Medicine, and Survey Sampling. These solved examples are very useful for an understanding of the applications of advanced sampling theory in our daily life and in diverse fields of science. An additional 173 unsolved practical problems are given at the end of the chapters. University and college professors may find these useful when assigning exercises to students. Each exercise gives exposure to several complete research papers for researchers/students.
Author: John L. Crassidis
Publisher: CRC Press
ISBN: 0203509129
Category : Mathematics
Languages : en
Pages : 606
Get Book Here
Book Description
Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals receiv
Author: Dick J. Brus
Publisher: CRC Press
ISBN: 1000600017
Category : Mathematics
Languages : en
Pages : 549
Get Book Here
Book Description
Scientific research often starts with data collection. However, many researchers pay insufficient attention to this first step in their research. The author, researcher at Wageningen University and Research, often had to conclude that the data collected by fellow researchers were suboptimal, or in some cases even unsuitable for their aim. One reason is that sampling is frequently overlooked in statistics courses. Another reason is the lack of practical textbooks on sampling. Numerous books have been published on the statistical analysis and modelling of data using R, but to date no book has been published in this series on how these data can best be collected. This book fills this gap. Spatial Sampling with R presents an overview of sampling designs for spatial sample survey and monitoring. It shows how to implement the sampling designs and how to estimate (sub)population- and space-time parameters in R. Key features Describes classical, basic sampling designs for spatial survey, as well as recently developed, advanced sampling designs and estimators Presents probability sampling designs for estimating parameters for a (sub)population, as well as non-probability sampling designs for mapping Gives comprehensive overview of model-assisted estimators Covers Bayesian approach to sampling design Illustrates sampling designs with surveys of soil organic carbon, above-ground biomass, air temperature, opium poppy Explains integration of wall-to-wall data sets (e.g. remote sensing images) and sample data Data and R code available on github Exercises added making the book suitable as a textbook for students The target group of this book are researchers and practitioners of sample surveys, as well as students in environmental, ecological, agricultural science or any other science in which knowledge about a population of interest is collected through spatial sampling. This book helps to implement proper sampling designs, tailored to their problems at hand, so that valuable data are collected that can be used to answer the research questions.
Author: Zongming Li
Publisher: CRC Press
ISBN: 1000835030
Category : Technology & Engineering
Languages : en
Pages : 621
Get Book Here
Book Description
Advances in Measurement Technology, Disaster Prevention and Mitigation collects papers resulting from the conference on Measurement Technology, Disaster Prevention and Mitigation (MTDPM 2022), Zhengzhou, China, 27–29 May, 2022. The primary goal is to promote research and developmental activities in measurement, disaster prevention and mitigation, and another goal is to promote scientific information interchange between scholars from the top universities, business associations, research centers and high-tech enterprises working all around the world. The conference conducts in-depth exchanges and discussions on relevant topics such as measurement, disaster prevention and mitigation, aiming to provide an academic and technical communication platform for scholars and engineers engaged in scientific research and engineering practice in the field of measurement application, measurement in civil engineering and disaster reduction. By sharing the research status of scientific research achievements and cutting-edge technologies, it helps scholars and engineers all over the world comprehend the academic development trend and broaden research ideas. So as to strengthen international academic research, academic topics exchange and discussion, and promote the industrialization cooperation of academic achievements.
Author: Mohan L. Kolhe
Publisher: Springer Nature
ISBN: 9811506949
Category : Technology & Engineering
Languages : en
Pages : 679
Get Book Here
Book Description
This book gathers a collection of high-quality peer-reviewed research papers presented at the 2nd International Conference on Data and Information Sciences (ICDIS 2019), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on March 29–30, 2019. In chapters written by leading researchers, developers, and practitioner from academia and industry, it covers virtually all aspects of computational sciences and information security, including central topics like artificial intelligence, cloud computing, and big data. Highlighting the latest developments and technical solutions, it will show readers from the computer industry how to capitalize on key advances in next-generation computer and communication technology.
Author: R. Lynn Kirlin
Publisher: SEG Books
ISBN: 156080081X
Category : Science
Languages : en
Pages : 355
Get Book Here
Book Description
Rather than address one seismic data-processing problem and present several methods, this book presents one fundamental methodology - analysis of the sample covariance matrix - and many seismic data problems to which it applies, providing the geophysical signal analyst with sufficient material to understand the usefulness of this approach.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 912
Get Book Here
Book Description
