Chandra G., Nautiyal R., Chandra H. (Eds.) Statistical Methods and Applications in Forestry and Environmental Sciences

Springer, 2020. — 290 p. — (Forum for Interdisciplinary Mathematics). — ISBN: 9811514755.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.
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.Statistics in Indian Forestry: A Historical Perspective
National Forest Inventory in India: Developments Toward a New Design to Meet Emerging Challenges
Internet of Things in Forestry and Environmental Sciences
Inverse Adaptive Stratified Random Sampling
Improved Nonparametric Estimation Using Partially Ordered Sets
Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling
Calibration Approach-Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling
A Joint Calibration Estimator of Population Total Under Minimum Entropy Distance Function Based on Dual Frame Surveys
Fusing Classical Theories and Biomechanics into Forest Modeling
Investigating Selection Criteria of Constrained Cluster Analysis: Applications in Forestry
Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species
Some Investigations on Designs for Mixture Experiments with Process Variable
Development in Copula Applications in Forestry and Environmental Sciences
Forest Cover-Type Prediction Using Model Averaging
Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses
Small Area Estimation for Total Basal Cover in the State of Maharashtra in India
Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India