Pages that link to "Item:Q1175384"
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The following pages link to Large sample theory of estimation in biased sampling regression models. I (Q1175384):
Displaying 12 items.
- Large-sample study of the kernel density estimators under multiplicative censoring (Q450027) (← links)
- Assessing large sample bias in misspecified model scenarios with reference to exposure model misspecification in errors-in-variable regression: a new computational approach (Q619781) (← links)
- Generalized method of moments (GMM) based inference with stratified samples when the aggregate shares are known (Q738085) (← links)
- Large sample theory of empirical distributions in biased sampling models (Q1118284) (← links)
- Large sample results under biased sampling when covariables are present. (Q1423183) (← links)
- Biased sampling, over-identified parameter problems and beyond (Q1674243) (← links)
- Large sample theory of maximum likelihood estimates in semiparametric biased sampling models. (Q1848773) (← links)
- Understanding the sampling bias: a case study on NBA drafts (Q2241466) (← links)
- MOMENT-BASED INFERENCE WITH STRATIFIED DATA (Q3081460) (← links)
- Fitting regression models with response-biased samples (Q3174230) (← links)
- Semiparametric Regression in Size-Biased Sampling (Q3561812) (← links)
- Testing Independence Under Biased Sampling (Q6110733) (← links)