{
"item_title" : "Biased Sampling, Over-Identified Parameter Problems and Beyond",
"item_author" : [" Jing Qin "],
"item_description" : "Chapter 1. Some Examples on Biased Sampling Problems.- Chapter 2. Some Results in Parametric Likelihood and Estimating Functions.- Chapter 3. Nonparametric Maximum Likelihood Estimation and Empirical Likelihood Method.- Chapter 4. General Results in Multiple Samples Biased Sampling Problems with Applications in Case and Control and Genetic Epidemiology.- Chapter 5. Outcome Dependent Sampling Problems.- Chapter 6. Missing Data Problem and Causal Inference.- Chapter 7. Applications of Exponential Tilting Models in Finite Mixture Models.- Chapter 8. Applications of Empirical Likelihood Methods in Survey Sampling.- Chapter 9. Some Other Topics.",
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Overview
Chapter 1. Some Examples on Biased Sampling Problems.- Chapter 2. Some Results in Parametric Likelihood and Estimating Functions.- Chapter 3. Nonparametric Maximum Likelihood Estimation and Empirical Likelihood Method.- Chapter 4. General Results in Multiple Samples Biased Sampling Problems with Applications in Case and Control and Genetic Epidemiology.- Chapter 5. Outcome Dependent Sampling Problems.- Chapter 6. Missing Data Problem and Causal Inference.- Chapter 7. Applications of Exponential Tilting Models in Finite Mixture Models.- Chapter 8. Applications of Empirical Likelihood Methods in Survey Sampling.- Chapter 9. Some Other Topics.
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Details
- ISBN-13: 9789811352492
- ISBN-10: 9811352496
- Publisher: Springer
- Publish Date: December 2018
- Dimensions: 9.21 x 6.14 x 1.29 inches
- Shipping Weight: 1.95 pounds
- Page Count: 624
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