Paul A. Parker

Paul A. Parker

Assistant Professor

Department of Statistics

University of California, Santa Cruz

Biography

I am currently an assistant professor in the Department of Statistics at the University of California, Santa Cruz. Before this role, I obtained my Ph.D. in Statistics at the University of Missouri, where I was a recipient of the U.S. Census Bureau Dissertation Fellowship, and a recipient of the University of Missouri Population, Education and Health Center Interdisciplinary Doctoral Fellowship. My dissertation work was focused on Bayesian methods for modeling non-Gaussian unit-level survey data under informative sampling, with an emphasis on application to small area estimation. I am broadly interested in modeling dependent data (time-series, spatial, functional, etc.) for a variety of applications including official statistics, social sciences, and ecology. I am also interested in integration of modern machine learning and data science techniques to help improve statistical models.

Interests

  • Bayesian Methods
  • Official Statistics and Survey Methods
  • Dependent Data (Spatial, Time Series, Functional Data, etc.)
  • Business and Government Applications
  • Deep Learning
  • Data Science

Education

  • Ph.D. in Statistics, 2021

    University of Missouri

  • M.A. in Statistics, 2018

    University of Missouri

  • B.S. in Applied Mathematics, 2014

    University of Idaho

Experience

 
 
 
 
 

Assistant Professor

Department of Statistics

Jul 2021 – Present University of California, Santa Cruz
 
 
 
 
 

Graduate Research Assistant

NSF

Aug 2020 – Jul 2021 University of Missouri
 
 
 
 
 

Graduate Research Fellow

Census Bureau Dissertation Fellowship

Aug 2019 – Jul 2021 University of Missouri
 
 
 
 
 

Graduate Research Fellow

Population, Education and Health Center Fellowship

Aug 2018 – May 2019 University of Missouri
 
 
 
 
 

Graduate Research Assistant

NSF-Census Research Network

Aug 2017 – May 2019 University of Missouri
 
 
 
 
 

Graduate Instructor

Department of Statistics

Aug 2016 – Dec 2016 University of Missouri
 
 
 
 
 

Analyst, Advanced Analytics

Liberty Mutual Insurance

Jun 2014 – Aug 2016 Seattle, WA

Recent Publications

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The soil health assessment protocol and evaluation applied to soil organic carbon

Recent Posts

Conditional Probability Density Functions

[Note: This post was created as part of a lecture for STAT 131 at UCSC.] Recall that for two continuous random variables \(X\) and \(Y\), we work with the joint probability density function \(f(x,y)\).

Plotting PUMAs in R

If you work with Census Bureau data, you are probably familiar with Public Use Microdata Samples (PUMS) from the American Community Survey. These are individual records (either person or household) that allow data users more customized analysis than would be available with the ACS tabulated data products.

Exploring Stock Data

I have recently been intrested in modeling stock volatility. In order to make the process easier, I wanted a way to quickly download stock data in R, and after some quick searching on the web, I stumbled across the tidyquant package which is able to download stock data from Yahoo Finance, and then conveniently store the data as a tibble object.

CV

Find a PDF of my CV here.

Contact

  • Department of Statistics, University of California Santa Cruz, Santa Cruz, CA 95064