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Erschienen in:
2017 | OriginalPaper | Buchkapitel
21. Inference for Density Ratio Model with Continuous Covariates
verfasst von : Jing Qin
Erschienen in: Biased Sampling, Over-identified Parameter Problems and Beyond
Verlag: Springer Singapore
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Abstract
We have discussed different density ratio models for two-sample or multiple-sample problems in Chaps. 10, 11, 17 and 18. A natural generalization is to study a density ratio model for continuous covariates. In this chapter we discuss two approaches. (1) the pairwise conditional likelihood method to eliminate the baseline “carrier density” or nuisance parameters, and (2) the profile maximum likelihood method. Also we will consider conditional independent tests in general semiparametric models and in partially specified exponential graphical models with high dimensional parameters.