Statistical Methods and Applications in Forestry and Environmental Sciences
- List Price: $139.99
- Publisher: Springer (Springer Nature)
- Publish date: 02/17/2020
Description:
Chapter 1. Measurement, Data and Statistics: A Historical Voyage in Indian Forestry.- Chapter 2. National Forest Inventory in India: Developments Towards a New Design to Meet Emerging Challenges.- Chapter 3 . Internet of Things in Forestry and Environmental Sciences.- Chapter 4. Inverse Adaptive Stratified Random Sampling.- Chapter 5. Improved Nonparametric Estimation Using Partially Ordered Sets.- Chapter 6. Bayesian Inference of a Finite Population Mean Under Length-Biased Sampling.- Chapter 7. Calibration Approach Based Estimators for Finite Population Mean in Multistage Stratified Random Sampling.- Chapter 8. A Joint Calibration Estimator of Population Total Under Entropy Distance Function Based on Dual Frame Surveys.- Chapter 9. Fusing Classical Theories and Biomechanics Into Forest Modelling.- Chapter 10. Statistical Multivariate Methods for Decision Making in Classification of Water Quality Data and Management of Water Resources.- Chapter 11. Investigating Selection Criteria of Constrained Cluster Analysis: Applications in Forestry.- Chapter 12 . Ridge Regression Model for the Estimation of Total Carbon Sequestered by Forest Species.- Chapter 13. Some Investigations on Designs for Mixture Experiments with Process Variable.- Chapter 14 . Development in Copula Applications in Forestry and Environmental Sciences.- Chapter 15. Forest Cover Type Prediction Using Model Averaging.- Chapter 16. Small Area Estimation for Skewed Semicontinuous Spatially Structured Responses.- Chapter 17. Small Area Estimation for Total Basal Cover in the State of Maharashtra, India.- Chapter 18. Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India.- Chapter 19. Exploration of Metagenomics Tools for Analysis of Forest Soil Microbial Diversity and its Annotation.- Chapter 20. Integrated Survey Scheme to Capture Forestry Related Data in Bangladesh: Beyond the Traditional Approach.
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