lmeInfo is an R package that provides analytic derivatives and information matrices for fitted linear mixed effects (lme) models and generalized least squares (gls) models estimated using nlme::lme() and nlme::gls(), respectively. The package includes functions for estimating the sampling variance-covariance of variance component parameters using the inverse Fisher information. The package does not currently provide methods for calculating degrees of freedom that are standard in other software packages (such as SAS) but this is a top priority on the roadmap for the project. An intern would be responsible for:
Developing functions that calculate degrees of freedom for the supported models, following known formulas.
Writing unit tests and examples to verify correct implementation.
Intern needs:
R programming, matrix algebra, knowledge of statistical theory at advanced undergraduate level.
Application Requirements:
Review the available projects by visiting the various project pages.
Interns should apply through the UW Student Jobs portal. Applicants who are not currently admitted or enrolled as a UW-Madison Student or without a UW NetID can login as well as create an account. Please note, you must apply to each project individually that you want to be considered for.
Application materials submitted through the UW Student Jobs portal should include:
A one-page cover letter that highlights your qualifications based on skills identified in the project listing and your interest in open source broadly.
A resume that includes your name, school email address, phone number, field(s) of study (major, minor, degree, certificate), relevant coursework, extracurricular activities, expected graduation date, relevant sample work (ex: GitHub link, personal website, etc.) and any relevant work or research experience.
The names and contact information of three references.
Submit a resume, cover letter, and three references as part of your application.
Interviews will be arranged for selected candidates on a rolling basis after applications close.
