A convenient toolbox to import data exported from Electronic Data Capture (EDC) software 'TrialMaster'.

This is the course package for the exercise portion of the "Ecological Data Collection and Processing" course.

Compute a cyclist's Eddington number, including efficiently
    computing cumulative E over a vector. A cyclist's Eddington number
    <https://en.wikipedia.org/wiki/Arthur_Eddington#Eddington_number_for_cycling>
    is the maximum number satisfying the condition such that a cyclist has
    ridden E miles or greater on E distinct days. The algorithm in this package
    is an improvement over the conventional approach because both summary
    statistics and cumulative statistics can be computed in linear time, since
    it does not require initial sorting of the data. These functions may also be
    used for computing h-indices for authors, a metric described by Hirsch (2005)
    <doi:10.1073/pnas.0507655102>. Both are specific applications of computing
    the side length of a Durfee square <https://en.wikipedia.org/wiki/Durfee_square>.

Exploratory and descriptive analysis of event based data. Provides methods for describing and selecting process data, and for preparing event log data for process mining. Builds on the S3-class for event logs implemented in the package 'bupaR'.

Detects sustained change in digital bio-marker data using
    simultaneous confidence bands. Accounts for noise using an auto-regressive
    model. Based on Buehlmann (1998) "Sieve bootstrap for smoothing in
    nonstationary time series" <doi:10.1214/aos/1030563978>.

Import physiologic data stored in
    the European Data Format (EDF and EDF+) into R.
    Both EDF and EDF+ files are supported. Discontinuous
    EDF+ files are not yet supported.

Provides easy access to tidy education finance data using Bellwether's methodology 
    to combine NCES F-33 Survey, Census Bureau Small Area Income Poverty Estimates (SAIPE),
    and community data from the ACS 5-Year Estimates. The package simplifies
    downloading, caching, and filtering education finance data by year and state,
    enabling researchers and analysts to explore K-12 education funding patterns,
    revenue sources, expenditure categories, and demographic factors across 
    U.S. school districts.