Estimate population average treatment effects from a primary data source 
  with borrowing from supplemental sources. Causal estimation is done with either a 
  Bayesian linear model or with Bayesian additive regression trees (BART) to adjust 
  for confounding. Borrowing is done with multisource exchangeability models (MEMs). For 
  information on BART, see Chipman, George, & McCulloch (2010) <doi:10.1214/09-AOAS285>. 
  For information on MEMs, see Kaizer, Koopmeiners, & 
  Hobbs (2018) <doi:10.1093/biostatistics/kxx031>.

An all relevant feature selection wrapper algorithm.
 It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

Computes exact bounds of Spearman's footrule in the presence of missing data, and performs independence test based on the bounds with controlled Type I error regardless of the values of missing data. Suitable only for distinct, univariate data where no ties is allowed.

Classical Boson Sampling using the algorithm of
 Clifford and Clifford (2017) <arXiv:1706.01260>. Also provides functions for
 generating random unitary matrices, evaluation of matrix permanents (both
 real and complex) and evaluation of complex permanent minors.

Reads and plots phylogenetic placements.

The Biomarker Optimal Segmentation System R package, 'bossR', is designed for precision medicine, helping to identify individual traits using biomarkers. It focuses on determining the most effective cutoff value for a continuous biomarker, which is crucial for categorizing patients into two groups with distinctly different clinical outcomes. The package simultaneously finds the optimal cutoff from given candidate values and tests its significance. Simulation studies demonstrate that 'bossR' offers statistical power and false positive control non-inferior to the permutation approach (considered the gold standard in this field), while being hundreds of times faster.

Fork-safe, raw access to the 'Amazon Web Services' ('AWS') 'SDK' via the 'boto3' 'Python' module, and convenient helper functions to query the 'Simple Storage Service' ('S3') and 'Key Management Service' ('KMS'), partial support for 'IAM', the 'Systems Manager Parameter Store' and 'Secrets Manager'.