Advanced Sampling Methods / by Raosaheb Latpate, Jayant Kshirsagar, Vinod Kumar Gupta, Girish Chandra.

Format:

Book

Author/Creator:

Latpate, Raosaheb, author.

Language:

English

Subjects (All):

Statistics.

Mathematical statistics--Data processing.

Mathematical statistics.

Statistical Theory and Methods.

Bayesian Inference.

Statistics and Computing.

Local Subjects:

Statistical Theory and Methods.

Bayesian Inference.

Statistics and Computing.

Physical Description:

1 online resource (XVII, 301 p. 23 illus., 13 illus. in color.)

Edition:

1st ed. 2021.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2021.

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.

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.

ISBN:

9789811606229

9811606226

OCLC:

1250347879