Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.


A time-varying AR, bivariate DLM of functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is a relatively new neuroimaging technique. It is a low cost, portable, and non-invasive method to measure brain activity via the blood oxygen level dependent signal. Similar to fMRI, it measures changes in the level of blood oxygen in the brain. Its time resolution is much finer than fMRI, however its spatial resolution is much courser--similar to EEG or MEG. fNIRS is finding widespread use on young…


Unsupervised Self-Normalized Change-Point Testing for Time

We propose a new self-normalized method for testing change points in the time series setting. Self-normalization has been celebrated for its ability to avoid direct estimation of the nuisance asymptotic variance and its flexibility of being generalized to handle quantities other than the mean. However, it was developed and mainly studied for constructing confidence intervals for quantities associated with a stationary time series, and its…


William R. Myers

"Industry Day" https://www.linkedin.com/in/bill-myers-05425815/


Big Geospatial-temporal Data and Analytics as-a-Service

The rapid growth of geospatial-temporal data sources from satellites, drones, weather modeling, IoT sensors etc., accumulating at a pace of petabytes to exabytes annually, opens unprecedented opportunities for industrial applications. However, the sheer size and complexity of the data also raises considerable challenges for conventional tools, relational geospatial databases, and cloud geospatial data services based on file systems (manifested…


Bayesian Inference via Filtering Equations for Financial Ultra-High Frequency Data

We propose a general partially-observed framework of Markov processes with marked point process observations for ultra-high frequency (UHF) transaction price data, allowing other observable economic or market factors. We develop the corresponding Bayesian inference via filtering equations to quantify parameter and model uncertainty.  Specifically, we derive filtering equations to characterize the evolution of the statistical foundation such…


Detecting planets: jointly modeling radial velocity and stellar activity time series

The radial velocity technique is one of the two main approaches for detecting planets outside our solar system, or exoplanets as they are known in astronomy. When a planet orbits a star it causes the star to move and this induces a Doppler shift (i.e. the star light appears redder or bluer than expected), and it is this effect that the radial velocity method attempts to detect. Unfortunately, these Doppler signals are typically contaminated by…


New Robust Econometric Tests for a Dynamic Predictive Regression

Testing for predictability of asset returns has been a long history in economics and finance. Recently, based on a simple predictive regression, Kostakis, Magdalinos and Stamatogiannis (2015,  Review of Financial Studies) derived a Wald type test based on the context of the extended instrumental variable (IVX) methodology for testing predictability of stock returns and Demetrescu (2014) showed that the local power of the standard IVX-based…


Recent Advances in Elastic Functional Data Analysis

Functional data analysis (FDA) is fast becoming an important research area, due to its broad applications in many branches of science. An essential component in FDA is the registration of points across functional objects. Without proper registration the results are often inferior and difficult to interpret. The current practice in FDA community is to treat registration as a pre-processing step, using off-the-shelf alignment procedures, and…


Colloquium: Hadley Wickham


An Integrative Statistical Framework for Multi-Modal Omics Data

It is becoming increasingly common for patients to be profiled across multiple molecular compartments -genomic, transcriptomic, proteomic, metab​olomic, etc. We develop a framework that leverages recent developments in the estimation of high-dimensional multi-layered graphical models that provide insights on regulatory mechanisms across molecular compartments (layers), as well as on molecular interactions within each layer and are also capable…
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