6 papers · 1 filter
Fast Semiparametric Density Regression with Weight-localized Predictive Recursion
Jonathan Lin, Surya Tokdar
Predictive recursion (PR) is a fast algorithm for nonparametric estimation of a mixing density, with connections to sequential Bayesian updating under a Dirichlet process prior and…
Density Discontinuity Regression
Surya T Tokdar, Rik Sen, Haoliang Zheng +1
Many policies hinge on a continuous variable exceeding a threshold, prompting strategic behavior by agents to stay on the favorable side. This creates density discontinuities at cu…
Modeling Neural Switching via Drift-Diffusion Models
Nicholas Marco, Jennifer M. Groh, Surya T. Tokdar
Neural encoding is a field in neuroscience that focuses on characterizing how information from stimuli is encoded in the spiking activity of neurons. When more than one stimulus is…
Stochastic Block Covariance Matrix Estimation
Yunran Chen, Surya T Tokdar, Jennifer M Groh
Motivated by a neuroscience application we study the problem of statistical estimation of a high-dimensional covariance matrix with a block structure. The block model embeds a stru…
A Bayesian decision-theoretic approach to sparse estimation
Aihua Li, Surya T. Tokdar, Jason Xu
We extend the work of Hahn and Carvalho (2015) and develop a doubly-regularized sparse regression estimator by synthesizing Bayesian regularization with penalized least squares wit…
High-dimensional Bayesian Fourier Analysis For Detecting Circadian Gene Expressions
Silvia Montagna, Irina Irincheeva, Surya T. Tokdar
In genomic applications, there is often interest in identifying genes whose time-course expression trajectories exhibit periodic oscillations with a period of approximately 24 hour…