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Advanced sampling methods / Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra.

By: Contributor(s): Material type: TextLanguage: English Publication details: Singapore : Springer, 2021.Description: 1 online resourceISBN:
  • 9789811606229
  • 9811606226
Subject(s): DDC classification:
  • 519.52 23 LAT
Online resources:
Contents:
1. Introduction -- 2. Simple Random Sampling -- 3. Stratied Random Sampling -- 4. Cluster Sampling -- 5. Double Sampling -- 6. Probability Proportional to Size Sampling -- 7. Systematic Sampling -- 8. Resampling Techniques -- 9. Adaptive Cluster Sampling -- 10. Two-Stage Adaptive Cluster Sampling -- 11. Adaptive Cluster Double Sampling -- 12. Inverse Adaptive Cluster Sampling -- 13. Two Stage Inverse Adaptive Cluster Sampling -- 14. Stratified Inverse Adaptive Cluster Sampling -- 15. Negative Adaptive Cluster Sampling -- 16. Negative Adaptive Cluster Double Sampling -- 17. Two- Stage Negative Adaptive Cluster Sampling -- 18. Balanced and Unbalanced Ranked Set Sampling -- 19. Ranked Set Sampling in Other Parameter Estimation and Non-Parametric Inference -- 20. Important Versions of Ranked Set Sampling -- 21. Sampling Errors.
Summary: This book discusses all major topics on survey sampling and estimation. It covers traditional as well as advanced sampling methods related to the spatial populations. The book presents real-world applications of major sampling methods and illustrates them with the R software. As a large sample size is not cost-efficient, this book introduces a new method by using the domain knowledge of the negative correlation between the variable of interest and the auxiliary variable in order to control the size of a sample. In addition, the book focuses on adaptive cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications in ecology, environmental science, health science, forestry, bio-sciences, and humanities. This book is targeted as a text for undergraduate and graduate students of statistics, as well as researchers in various disciplines.
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Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
General Books CUTN Central Library Sciences Non-fiction 519.52 LAT (Browse shelf(Opens below)) Available 49592

Includes bibliographical references.

1. Introduction -- 2. Simple Random Sampling -- 3. Stratied Random Sampling -- 4. Cluster Sampling -- 5. Double Sampling -- 6. Probability Proportional to Size Sampling -- 7. Systematic Sampling -- 8. Resampling Techniques -- 9. Adaptive Cluster Sampling -- 10. Two-Stage Adaptive Cluster Sampling -- 11. Adaptive Cluster Double Sampling -- 12. Inverse Adaptive Cluster Sampling -- 13. Two Stage Inverse Adaptive Cluster Sampling -- 14. Stratified Inverse Adaptive Cluster Sampling -- 15. Negative Adaptive Cluster Sampling -- 16. Negative Adaptive Cluster Double Sampling -- 17. Two- Stage Negative Adaptive Cluster Sampling -- 18. Balanced and Unbalanced Ranked Set Sampling -- 19. Ranked Set Sampling in Other Parameter Estimation and Non-Parametric Inference -- 20. Important Versions of Ranked Set Sampling -- 21. Sampling Errors.

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This book discusses all major topics on survey sampling and estimation. It covers traditional as well as advanced sampling methods related to the spatial populations. The book presents real-world applications of major sampling methods and illustrates them with the R software. As a large sample size is not cost-efficient, this book introduces a new method by using the domain knowledge of the negative correlation between the variable of interest and the auxiliary variable in order to control the size of a sample. In addition, the book focuses on adaptive cluster sampling, rank-set sampling and their applications in real life. Advance methods discussed in the book have tremendous applications in ecology, environmental science, health science, forestry, bio-sciences, and humanities. This book is targeted as a text for undergraduate and graduate students of statistics, as well as researchers in various disciplines.

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