For a symmetric \(2 \times 2\) matrix \(\Sigma\), consider the following problem: \[\begin{aligned} & \underset{x}{\text{minimize}} & & x^T \Sigma x \\ & \text{subject to} & & x \geq 0, \; \mathbf{1}^T x = 1 \end{aligned}\] Let \[\Sigma = \left[ \begin{array}{cc} a & c \\ c & b \end{array} \right]\] and note t... Read more 06 Nov 2018 - 1 minute read

The bias-variance tradeoff is usually discussed in terms of the mean squared error (MSE) of a predictor. However, it can also be applied to estimates of coefficients in a linear model. Below we examine how bias and variance figure into the MSE of coefficient estimates under a \(g\)-prior. Assume a linear model of the form \[Y = X \beta + \epsi... Read more 05 Nov 2018 - 4 minute read

The Cancer Data Science team and others at the Broad Institute came out with an article in Nature Communications today detailing a new method for normalizing and integrating multiple large RNAi screening datasets. Itâ€™s called DEMETER2, named after the Roman goddess of the harvest. DEMETER2 uses a hierarchical Bayesian model to estimate gene dep... Read more 02 Nov 2018 - less than 1 minute read

I am currently a first year PhD student in the Department of Statistical Science at Duke University. Prior to coming to Duke, I worked with Aviad Tsherniak on the Cancer Data Science team at the Broad Institue of MIT and Harvard. I contributed to the Cancer Dependency Map effort with a focus on data analysis for the PRISM profiling method. Befo... Read more 29 Oct 2018 - less than 1 minute read