Read examples with interlinear glosses from files
    or from text and print them in a way compatible with both
    Latex and HTML outputs.

Provides a framework for creating plots with glowing points.

R Interface to C API of GLPK, depends on GLPK Version >= 4.42.

Likelihood ratio tests for genome-wide association and genome-wide linkage analysis under heterogeneity.

Provides a fully automated workflow for calibrating and analyzing
    light-level geolocation ('GLS') data from seabirds and other wildlife. The
    'glscalibrator' package auto-discovers birds from directory structures,
    automatically detects calibration periods from the first days of deployment,
    processes multiple individuals in batch mode, and generates standardized
    outputs including position estimates, diagnostic plots, and quality control
    metrics. Implements the established threshold workflow internally, following
    the methods described in 'SGAT' (Wotherspoon et al. (2016)
    <https://github.com/SWotherspoon/SGAT>), 'GeoLight' (Lisovski et al. (2012)
    <doi:10.1111/j.2041-210X.2012.00185.x>), and 'TwGeos' (Lisovski et al.
    (2019) <https://github.com/slisovski/TwGeos>).

When the response variable Y takes one of R > 1 values, the function 'glsm()' computes the maximum likelihood estimates (MLEs) of the parameters under four models: null, complete, saturated, and logistic. It also calculates the log-likelihood values for each model. This method assumes independent, non-identically distributed variables. For grouped data with a multinomial outcome, where observations are divided into J populations, the function 'glsm()' provides estimation for any number K of explanatory variables.

Performs linear regression with correlated predictors, responses and correlated measurement errors in predictors and responses, correcting for biased caused by these.

An implementation of interpreted string literals, inspired by
    Python's Literal String Interpolation
    <https://www.python.org/dev/peps/pep-0498/> and Docstrings
    <https://www.python.org/dev/peps/pep-0257/> and Julia's Triple-Quoted
    String Literals
    <https://docs.julialang.org/en/v1.3/manual/strings/#Triple-Quoted-String-Literals-1>.