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Slideshow

Tags: Colloquium Series

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

Large and complex data have been generated routinely from various sources, for instance, time course biological studies and social media. Classic nonparametric models, such as smoothing spline ANOVA models, are not well equipped to analyze such large and complex data. To overcome these challenges, I propose novel nonparametric methods under a reproducing kernel Hilbert space framework to (1) significantly reduce daunting computational costs of…
With the rapid development of technology, increasing amount of data has been produced from many fields of science, such as biology, neuroscience, and engineering. The inadequate sample is no longer a bottleneck of modern statistical research. More often, we are facing data of extremely high dimensionality or coming from remarkably different sources. How to effectively extract information from the large-scale and high-dimensional data or data…
We discuss optimal designs for the panel mixed logit model. The panel mixed logit model is usually used for the analysis of discrete choice experiments. The information matrix used in design criteria does not have a closed form expression and it is computationally difficult to evaluate the information matrix numerically. We derive the information matrix and use the obtained form to propose three methods to approximate the information matrix. The…
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…
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…
"Industry Day" https://www.linkedin.com/in/bill-myers-05425815/
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…
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…
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…
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…

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