A LIKELIHOOD RATIO FRAMEWORK FOR HIGH-DIMENSIONAL SEMIPARAMETRIC REGRESSION
A LIKELIHOOD RATIO FRAMEWORK FOR HIGH-DIMENSIONAL SEMIPARAMETRIC REGRESSION
About this item
Full title
Author / Creator
Ning, Yang , Zhao, Tianqi and Liu, Han
Publisher
Hayward: Institute of Mathematical Statistics
Journal title
Language
English
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Publication information
Publisher
Hayward: Institute of Mathematical Statistics
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More information
Scope and Contents
Contents
We propose a new inferential framework for high-dimensional semiparametric generalized linear models. This framework addresses a variety of challenging problems in high-dimensional data analysis, including incomplete data, selection bias and heterogeneity. Our work has three main contributions: (i) We develop a regularized statistical chromatograph...
Alternative Titles
Full title
A LIKELIHOOD RATIO FRAMEWORK FOR HIGH-DIMENSIONAL SEMIPARAMETRIC REGRESSION
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_1983661045
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_1983661045
Other Identifiers
ISSN
0090-5364
E-ISSN
2168-8966
DOI
10.1214/16-AOS1483
