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

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Forest Cover-Type Prediction Using Model Averaging,l. The methodology is applied to forest cover-type dataset. We have also transformed the wilderness areas and soil types variables into two variables. Such type of transformation provides improved predictive performance as well as easy application of model averaging technique to the data.

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Estimation of Abundance of Asiatic Elephants in Elephant Reserves of Kerala State, India,peared to be better method than the others. The total estimated elephant population using dung survey for all the reserves was 7490 with 95% confidence limit of 6280–9053. However, more studies to obtain defecation and decay rates in varying climatic conditions will help improving the accuracy of the estimates of the elephant population.

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Statistics in Indian Forestry: A Historical Perspective, time has been extended from forest administration to forestry research (primarily silviculture, trade in forest products, biodiversity conservation, etc.). This chapter traces the history of quantification of forest resources and the use of statistical methods for the development of forestry sector in India.

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Calibration Approach-Based Estimators for Finite Population Mean in Multistage Stratified Random Salibration estimators over the usual estimator of the population mean without using auxiliary information in two-stage stratified random sampling. It has been found that the two-step calibration estimator has outperformed than the other calibration estimators and the usual estimator without using auxiliary information.

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Book 2020 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

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