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Titlebook: Statistical Methods and Applications in Forestry and Environmental Sciences; Girish Chandra,Raman Nautiyal,Hukum Chandra Book 2020 The Edi

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书目名称Statistical Methods and Applications in Forestry and Environmental Sciences
编辑Girish Chandra,Raman Nautiyal,Hukum Chandra
视频video
概述Provides a broad overview of methodologies used in statistical investigations of forestry and environmental issues.Discusses important case studies related to forestry and environmental sciences.Inclu
丛书名称Forum for Interdisciplinary Mathematics
图书封面Titlebook: Statistical Methods and Applications in Forestry and Environmental Sciences;  Girish Chandra,Raman Nautiyal,Hukum Chandra Book 2020 The Edi
描述.This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences. It discusses important methodologies like ranked set sampling, adaptive cluster sampling, small area estimation, calibration approach-based estimators, design of experiments, multivariate techniques, Internet of Things, and ridge regression methods. It also covers the history of the implementation of statistical techniques in Indian forestry and the National Forest Inventory of India..The book is a valuable resource for applied statisticians, students, researchers, and practitioners in the forestry and environment sector. It includes real-world examples and case studies to help readers apply the techniques discussed. It also motivates academicians and researchers to use new technologies in the areas of forestry and environmental sciences with the help of software like R, MATLAB, Statistica, and Mathematica..
出版日期Book 2020
关键词Indian Forestry; Nonparametric Estimation; Bayesian Inference; Stratified Random Sampling; Joint Calibra
版次1
doihttps://doi.org/10.1007/978-981-15-1476-0
isbn_softcover978-981-15-1478-4
isbn_ebook978-981-15-1476-0Series ISSN 2364-6748 Series E-ISSN 2364-6756
issn_series 2364-6748
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Improved Nonparametric Estimation Using Partially Ordered Sets,Environmental and Ecological Statistics 19(3):309–326, .) proposed a sampling scheme based on to allow for partially ordered sets. This scheme permits a ranker to declare ties and then record the tie structure for potential use in statistical analysis. We first introduce two nonparametric maximum li
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Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling,n of unknown size. Specifically, by using Bayesian predictive inference, we estimate the finite population mean of shrub widths in a limestone quarry area with plenty of regrown mountain mahogany. The data on shrub widths are collected using transect sampling, and it is assumed that the probability
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Fusing Classical Theories and Biomechanics into Forest Modelling,heory, Metzger’s theory, self-thinning rule, Da Vinci’s tree form concept, Logarithmic spiral technique, etc., which have greater significance in forestry science. With advanced computational tools from the IT revolution at disposal, a better understanding of the above-mentioned theories is now poss
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