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Statistics Research Seminar

Topic: Truncated latent Gaussian copula model for zero-inflated data

 

Date:

Monday, January 13, 2020

 

Speaker:

Dr. Irina Gaynanova, Assistant Professor,

Texas A & M University

 

Tea and refreshments with faculty and speaker:

3:00pm to 3:45 pm in Weniger Room 245

 

Seminar:

4:00pm in Weniger Hall Room 149

 

Cost:

This seminar is open to the public

Abstract:

A great number of multivariate statistical methods, such as principal component analysis, discriminant analysis, canonical correlation analysis and graphical lasso to name a few, require the estimate of covariance or correlation matrix of variables as one of the inputs. It is typical to use Pearson sample correlation matrix, which works well at capturing dependencies between normally distributed variables. In this work we consider the problem of estimating dependencies between zero-inflated measurements, which arise in miRNA data, microbiome data, physical activity data, etc. We propose truncated latent Gaussian copula to model the data with excess zeroes, which allows us to derive a rank-based estimator of latent correlation matrix without the estimation of marginal transformation functions. We prove the consistency of corresponding estimator, and demonstrate its use for the analysis of associations between gene expression and microRNA data of breast cancer patients, and for inferring the conditional independence graph in quantitate gut microbiome data.

 

Monday, January 13 at 4:00pm to 4:50pm

Weniger Hall, 245
103 SW Memorial Place, Corvallis, OR 97331

Event Type

Lecture or Presentation

Event Topic

Research

Audience

Community, Faculty and Staff, Student, Future and New, Graduate, Alumni, Industry Partner, International, Online

County

Benton

Cost

Free and open to the public

Organization
College of Agricultural Sciences, Department of Statistics, College of Science
Contact Name

Mary Gardner

Contact Email

mary.gardner@oregonstate.edu

Contact Phone

5417373883

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