Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness

Modern surveys with large sample sizes and growing mixed-type questionnaires require robust and scalable analysis methods. In this work, we consider recovering a mixed dataframe matrix, obtained by complex survey sampling, with entries following different canonical exponential distributions and subj...

Celý popis

Podrobná bibliografie

Vydáno v:	Journal of computational and graphical statistics Ročník 33; číslo 4; s. 1320 - 1328
Hlavní autoři:	Mao, Xiaojun, Wang, Hengfang, Wang, Zhonglei, Yang, Shu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Taylor & Francis 01.10.2024 Taylor & Francis Ltd
Témata:	Algorithms Covariate matrix Error analysis Exponential family Fast iterative shrinkage-thresholding algorithm Regression models Sampling Upper bounds fast iterative shrinkage-thresholding algorithm exponential family covariate matrix
ISSN:	1061-8600, 1537-2715
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!