书目详细信息
： Sampling theory for the ecological and natural resource sciences /
书目信息 机读格式(MARC)
| ISBN： | 9780198815792 |
|---|---|
| 编目源： | YDX YDX BDX UKMGB OCLCO OCLCF OCLCQ YDX OCLCQ PUL UNBCA YDXIT YAM DLC |
| 语种代码： | eng |
| 个人名称： | Hankin, David G., |
| 题名： | Sampling theory for the ecological and natural resource sciences / David G. Hankin, Michael S. Mohr, and Ken B. Newman. |
| 版本说明： | First edition. |
| 出版发行项： | Oxford ; New York, NY : Oxford University Press, 2019. |
| 载体形态： | xv, 343 pages : illustrations (some color), maps (some color) ; 25 cm |
| 书目附注： | Includes bibliographical references (pages 329-336) and index. |
| 格式化内容附注： | 1. Introduction -- 2. Basic concepts -- 3. Equal probability sampling -- 4. Systematic sampling -- 5. Stratified sampling -- 6. Single-stage cluster sampling : clusters of equal size -- 7. Ratio and regression estimation -- 8. Unequal probability sampling -- 9. Multi-stage sampling -- 10. Multi-phase sampling -- 11. Adaptive sampling -- 12. Spatially balanced sampling -- 13. Sampling through time -- A. Mathematical foundations. |
| 格式化内容附注： | Cover; Sampling Theory: For the Ecological and Natural Resource Sciences; Copyright; Dedication; Preface; Contents; CHAPTER 1: Introduction; 1.1 The design-based paradigm; 1.2 Text content and orientation; 1.3 What distinguishes this text?; 1.4 Recommendations for instructors; 1.5 Sampling theory: A brief history; CHAPTER 2: Basic concepts; 2.1 Terminology; 2.2 Components of a sampling strategy; 2.3 Selection methods; 2.4 Properties of estimators; 2.5 Sampling distribution of an estimator; 2.6 Judgment sampling versus random sampling; CHAPTER 3: Equal probability sampling. |
| 格式化内容附注： | 3.1 Without replacement sampling; 3.1.1 Estimation of the population mean, proportion, and total; 3.1.2 Sampling variance; 3.1.3 Estimation of sampling variance; 3.1.4 Bernoulli sampling; 3.2 With replacement sampling; 3.2.1 Estimation of the population mean, proportion, and total; 3.2.2 Sampling variance and variance estimation; 3.2.3 Rao-Blackwell theorem; 3.3 Relative performance of alternative sampling strategies; 3.3.1 Measures of relative performance; 3.3.2 An example: SRS/mean-per-unit estimation versus SWR; 3.4 Sample size to achieve desired level of precision. |
| 格式化内容附注： | 3.4.1 Approximate normality of sampling distributions3.4.2 Confidence interval construction; 3.4.3 Sample size determination; 3.5 Nonresponse and oversampling; 3.6 Sampling in R; 3.6.1 SRS and SWR; 3.6.2 Sample Spaces; 3.7 Chapter comments; Problems; CHAPTER 4: Systematic sampling; 4.1 Linear systematic sampling; 4.1.1 N /k is integer-valued; Relative efficiency; 4.1.2 N/k is not integer-valued; Unbiased estimation; 4.2 Selection methods that guarantee fixed n; 4.2.1 Circular systematic sampling; 4.2.2 Fractiona linterval random start; 4.3 Estimation of sampling variance |
| 格式化内容附注： | 4.3.1 Biased estimationSRS proxy; Estimation in presence of linear trend; 4.3.2 Unbiased estimation; m samples selected independently; m samples selected without replacement; 4.4 Unpredictable trend in sampling variance with n; 4.5 Warning: Pathological settings; 4.6 Nonresponse and oversampling; 4.7 Chapter comments; Problems; CHAPTER 5: Stratified sampling; 5.1 Estimation of the population mean; 5.1.1 Expected value; 5.1.2 Sampling variance; 5.1.3 Numerical examples; 5.2 Estimation of the population proportion; 5.3 Estimation of the population total; 5.4 Estimation of sampling variance |
| 格式化内容附注： | 5.5 Allocation of the sample across strata5.5.1 Optimal allocation: Graphical analysis; 5.5.2 Optimal allocation: Analytical analysis; Use of Lagrange multipliers; 5.5.3 Comments on optimal allocation; 5.6 Sample size determination; 5.7 Relative efficiency; 5.7.1 Proportional allocation; 5.7.2 Estimation of finite population variance; 5.8 Effective degrees of freedom; 5.9 Post-stratification; 5.9.1 Unconditional sampling variance; 5.9.2 Conditional sampling variance; 5.10 Chapter comments; Problems; CHAPTER 6: Single-stage cluster sampling: Clusters of equal size 6.1 Estimation of the population mean |