[gov3009-l] Applied Statistics Workshop: Tamar Sofer on Wed., February 15
kkashin at fas.harvard.edu
Mon Feb 13 02:59:28 EST 2012
Please join us for the Applied Statistics Workshop (Gov 3009) this
Wednesday, February 15 from 12.00 - 1.30 pm in CGIS Knafel Room 354. Tamar
Sofer, a Ph.D. student from the Department of Biostatistics at Harvard
University, will give a presentation entitled "Sparse Joint Estimation of
Covariates-Dependent Covariance Matrices". As always, a light lunch will be
We propose an estimation method for the principal components/covariance
> structures of a set of outcomes, while modeling the effect of covariates.
> We assume a linear mixed model formulation on the outcomes as response to
> covariates, a model corresponding to spiked covariance matrices. Since the
> subject-specific covariance matrices and the effects of covariates are
> believed to be sparse, we penalize coefficients using an oracle penalty
> function. Under some assumptions on the parameters and the likelihood, we
> show that the maximum likelihood estimator of the parameters is
> asymptotically consistent and is uniformly sparse ("sparsistent"), even
> when the number of parameters is small. We propose using the Bayesian
> Information Criterion (BIC) for tuning parameter selection and show that it
> is consistent for model selection. Using a simple iterated least squares
> procedure we are able to recover the model parameters with high accuracy.
> The method is implemented to study the effect of smoking on the covariances
> of gene methylations in the asthma pathway in smokers and non-smokers US
> veterans from the Normative Aging Study (NAS).
An up-to-date schedule for the workshop is available at
Ph.D. Student in Government
E-mail: kkashin at fas.harvard.edu
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