Post-selection inference in linear regression models,
    constructing simultaneous confidence intervals across a user-specified universe of models.
    Implements the methodology described in Kuchibhotla, Kolassa, and Kuffner (2022) "Post-Selection Inference"
    <doi:10.1146/annurev-statistics-100421-044639> to ensure valid inference after model
    selection, with applications in high-dimensional settings like Lasso selection.

Collection of tutorials for working with 'Positron' 
    and for learning how to apply generative AI when coding with R. 
    Covers scripts, 'Quarto' documents, 'Git', 'GitHub', and 
    'Quarto' websites. Makes extensive use of the tools in the 
    'tutorial.helpers' package.

Personalize drug regimens using individual pharmacokinetic (PK) and 
    pharmacokinetic-pharmacodynamic (PK-PD) profiles. By combining therapeutic 
    drug monitoring (TDM) data with a population model, 'posologyr' offers 
    accurate posterior estimates and helps compute optimal individualized dosing
    regimens. The empirical Bayes estimates are computed following the method 
    described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.

Computes the exact probability density function of X/Y conditioned on positive quadrant for series of  bivariate distributions,for more details see Nadarajah,Song and Si (2019) <DOI:10.1080/03610926.2019.1576893>.

Calculates, via simulation, power and appropriate stopping
  alpha boundaries (and/or futility bounds) for sequential analyses (i.e.,
  group sequential design) as well as for multiple hypotheses (multiple tests
  included in an analysis), given any specified global error rate. This enables
  the sequential use of practically any significance test, as long as the
  underlying data can be simulated in advance to a reasonable approximation.
  Lukács (2022) <doi:10.21105/joss.04643>.

Computes the Physiological and Operative Severity Score for the
    enUmeration of Mortality and morbidity (POSSUM), its Portsmouth
    modification (P-POSSUM), and the colorectal (CR-POSSUM), vascular
    (V-POSSUM) and ruptured aortic aneurysm (RAAA-POSSUM) variants,
    risk-adjustment systems used in surgical audit. Functions map
    physiological and operative variables to their
    component scores and return the predicted probabilities of morbidity and
    mortality from the published logistic equations. The coefficients follow
    Copeland and others (1991) <doi:10.1002/bjs.1800780327> for POSSUM,
    Prytherch and others (1998) <doi:10.1046/j.1365-2168.1998.00840.x> for
    P-POSSUM, Tekkis and others (2004) <doi:10.1002/bjs.4430> for the
    colorectal variant (CR-POSSUM), and Neary and others (2003)
    <doi:10.1002/bjs.4041> for the vascular variant (V-POSSUM). The
    package is intended for audit and research; it is not a
    validated medical device and must not be used as the sole basis for
    clinical decisions.