Research Interest
Environmental Statistics: Development and application of statistical methods in the environmental sciences.
Functional Data Analysis: Statistical analysis of data samples consisting of random functions or surfaces.
Computational Statistics: Development and application of computational and graphical approaches to solving statistical problems.
Data Mining Methods: Analysis of observational data to find unsuspected relationships.
Nonparametric Regression: Regression analysis in which the model does not take a parametric form but is driven by the data.
R Package and Shiny App Development
When time permits, I focus on developing R packages and R Shiny applications that enhance the accessibility and applicability of statistical methods. Some of my current projects include:
CSUBstats: An R packaged developed for use with Training modules on selected statistical methods and future educational resources.
SWEViz: A Shiny app designed for visualizing snowpack (SWE) data across the Sierra Nevada.
Interested in conducting research?
Are you interested in environmental statistics, data analysis, or building interactive tools like Shiny apps? If you have a dataset, a research question, or an idea for a data-driven application, feel free to contact me. I would be happy to explore potential research collaborations.
Publications and Works in Progress
Publications
Visit ORCID for a list of my publications
Works in Progress
Montoya, E.L. “More efficient smoothing parameter selection for regularized functional principal component using generalized degrees of freedom” (working title)
Montoya, E.L. “A test for monotonic association in a functional single index model” (working title)
Montoya, E.L., W. Meiring, and Dozier, J.”Quantifying the Variation in the Annual Progression of Snow Accumulation and Melt in the Sierra Nevada: A Functional Data Analysis Approach.” (working title)