Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Marten Wegkamp"'
Autor:
Xin Bing, Tyler Lovelace, Florentina Bunea, Marten Wegkamp, Sudhir Pai Kasturi, Harinder Singh, Panayiotis V. Benos, Jishnu Das
Publikováno v:
Patterns, Vol 3, Iss 5, Pp 100473- (2022)
Summary: High-dimensional cellular and molecular profiling of biological samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate prioritized causal inferences. Current methods are limited by high dimen
Externí odkaz:
https://doaj.org/article/5dd6368ebad64446982ba499f1247b52
Autor:
Javad Rahimikollu, Hanxi Xiao, Anna E. Rosengart, Tracy Tabib, Paul Zdinak, Kun He, Xin Bing, Florentina Bunea, Marten Wegkamp, Amanda C. Poholek, Alok V Joglekar, Robert A Lafyatis, Jishnu Das
Modern multi-omic technologies can generate deep multi-scale profiles. However, differences in data modalities, multicollinearity of the data, and large numbers of irrelevant features make the analyses and integration of high-dimensional omic dataset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cec6bc44336b7a8ce433f6ebd5892e10
https://doi.org/10.1101/2022.11.25.518001
https://doi.org/10.1101/2022.11.25.518001
Autor:
Xin Bing, Tyler Lovelace, Florentina Bunea, Marten Wegkamp, Sudhir Pai Kasturi, Harinder Singh, Panayiotis V. Benos, Jishnu Das
Publikováno v:
Patterns (New York, N.Y.). 3(5)
High-dimensional cellular and molecular profiling of biological samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate prioritized causal inferences. Current methods are limited by high dimensionality
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46a57260d31fdaeab9f5d3510b9f64da
https://pubmed.ncbi.nlm.nih.gov/35607614
https://pubmed.ncbi.nlm.nih.gov/35607614
Autor:
Harinder Singh, Jishnu Das, Panayiotis V. Benos, Xin Bing, Tyler Lovelace, Marten Wegkamp, Florentina Bunea
High-dimensional cellular and molecular profiling of human samples highlights the need for analytical approaches that can integrate multi-omic datasets to generate predictive biomarkers and prioritized causal inferences. Current methods are limited b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de806c6169237e4670141e2e53ba0fd1
https://doi.org/10.1101/2021.05.03.442513
https://doi.org/10.1101/2021.05.03.442513
Publikováno v:
Ann. Statist. 48, no. 4 (2020), 2055-2081
This work introduces a novel estimation method, called LOVE, of the entries and structure of a loading matrix $A$ in a latent factor model $X=AZ+E$, for an observable random vector $X\in \mathbb{R}^{p}$, with correlated unobservable factors $Z\in \ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7ba6d755d50d925e941fcd52a6ae72f
https://projecteuclid.org/euclid.aos/1597370664
https://projecteuclid.org/euclid.aos/1597370664
Detecting approximate replicate components of a high-dimensional random vector with latent structure
High-dimensional feature vectors are likely to contain sets of measurements that are approximate replicates of one another. In complex applications, or automated data collection, these feature sets are not known a priori, and need to be determined. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99591adef000802a35ff8c214a7c45dd
Autor:
Marten Wegkamp, Xin Bing
Publikováno v:
Ann. Statist. 47, no. 6 (2019), 3157-3184
We consider the multivariate response regression problem with a regression coefficient matrix of low, unknown rank. In this setting, we analyze a new criterion for selecting the optimal reduced rank. This criterion differs notably from the one propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38531a998a48438e4eacc4191e725d6e
https://doi.org/10.1214/18-aos1774
https://doi.org/10.1214/18-aos1774
Autor:
Marten Wegkamp, Dragan Radulovic
Publikováno v:
Journal of Statistical Planning and Inference. 194:75-84
We offer an umbrella type result which extends weak convergence of classical empirical processes on the line to that of more general processes indexed by functions of bounded variation. This extension is not contingent on the type of dependence of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::319c0c9f2b084c0db6a440416846064f
https://doi.org/10.1016/j.jspi.2017.09.006
https://doi.org/10.1016/j.jspi.2017.09.006
Autor:
Marten Wegkamp, Jacob Bien
Publikováno v:
Journal of Statistical Planning and Inference. 143:1859-1862
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c35b88c81082274799bc24a3eec4e19
https://doi.org/10.1016/j.jspi.2013.05.020
https://doi.org/10.1016/j.jspi.2013.05.020
Autor:
Jean-David Fermanian, Marten Wegkamp
Publikováno v:
Journal of Multivariate Analysis. 110:19-29
For the study of dynamic dependence structures, the authors introduce the concept of a pseudo-copula, which extends Patton’s definition of a conditional copula. They state the equivalent of Sklar’s theorem for pseudo-copulas. They establish the a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d3813a0d956ce3cd03a0a55931edaea
https://doi.org/10.1016/j.jmva.2012.02.018
https://doi.org/10.1016/j.jmva.2012.02.018