Use when adding a calendar event, such as a seminar, for publication on the department website and other VCU web properties.

Add an Event

If possible, begin by opening an existing event and copying it so there is less manual entry required.
1. Click on the title of an event to edit it. If all the events you have entered have passed, click the "View Archived Events" button if necessary to access the list of historical events.
2. Click the "Modify" button on the "Event Review" screen.
3. Click the "Save as New" button. Note that changes to the existing information do not seem to stick when the copy is created, so save your effort.
4. Click the "Events Calendar Manager" link on the resulting page to return to the list of events and change it.
5. Click on the title of the new (copied) event.
6. Click the "Modify" button on the "Event Review" screen.
7. Update the information appropriately, using "Continue" to move forward. Values listed below are typical values used for seminar announcements and may not be appropriate for all events:
  1. Event Title: "Geostatistical Modeling of Positive Definite Matrices, with Applications to Diffusion Tensor Imaging" or if the title is not yet known, "Biostatistics Seminar: Justin X. Celent, Ph.D."
  2. Digital Signage Event Title: due to the 50 character limit, it may be most productive to use the "Biostatistics Seminar: Justin X. Celent, Ph.D." notation.
  3. Begin Date
  4. End Date
  5. Begin Time
  6. End Time
  7. Campus: Off-Campus
  8. Building: One Capitol Square
  9. Room: 305
  10. School/Unit: Medicine
  11. Department: Biostatistics (This can be left alone if it is correct in the textbox.)
  12. URL: https://biostatistics.vcu.edu/
  13. Audience: Typically:
    1. School of Medicine
    2. VCU Faculty
    3. VCU Staff
    4. VCU Students
  14. Description: Typically cut-and pasted from the seminar announcement, beginning with the speaker's full name, credentials, position, and affiliation:
    Dipankar Bandyopadhyay, Ph.D.
    Professor
    Department of Biostatistics
    Virginia Commonwealth University
    Geostatistical modeling has been extensively applied to model continuous point-referenced neuroimaging data, because of its potential in producing efficient and valid statistical inference. However, diffusion tensor imaging (DTI), a neuroimaging technique, produces voxel-level positive definite (p.d) matrices as responses, which available geostatistical modeling tools are unable to handle efficiently. In this talk, we propose the spatial Wishart process, a spatial stochastic process, where each p.d matrix-variate responses marginally follows a Wishart distribution, with the spatial dependence induced by latent Gaussian processes. This process is valid on an uncountable collection of spatial locations, and is almost surely continuous. Our inferential framework is decisively Bayesian, relying on popular Markov chain Monte Carlo tools. Due to the lack of a closed-form density, we introduce approximations, leading to a computationally scalable working model. Motivated by a DTI dataset on cocaine users, we further extend the model to accommodate spatial matrix-variate regression. Both simulation studies and the real data application demonstrate the improved performance of our model, compared to available univariate (spatial) alternatives.
  15. Submitter's Information
  16. Special Accommodations
  17. Visibility: Public
  18. Primary Category: Research
  19. Secondary Category: MCV Campus
8. Click "Save" to submit the event for review.
9. Return later (after allowing time for approval) to ensure the event has published as desired on the department seminar and events page.