Biased Sampling, Over-identified Parameter Problems and Beyond
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Biased Sampling, Over-identified Parameter Problems and Beyond
Qin, Jing
Springer Verlag, Singapore
06/2017
624
Dura
Inglês
9789811048548
15 a 20 dias
Descrição não disponível.
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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Biased Sampling Problems;Finite Mixture Models;Genetic Epidemiology;Parametric Likelihood;Survey Sampling
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
