A blind spike program provides samples to a laboratory in order to  perform quality control (QC) checks. The samples provided are of a known quantity to the tester. The laboratory is typically uninformed of that the sample provided is a QC sample.

An implementation of the model in Steorts (2015) <DOI:10.1214/15-BA965SI>, which performs Bayesian entity resolution for categorical and text data, for any distance function defined by the user. In addition, the precision and recall are in the package to allow one to compare to any other comparable method such as logistic regression, Bayesian additive regression trees (BART), or random forests. The experiments are reproducible and illustrated using a simple vignette. LICENSE: GPL-3 + file license.

Identifies cell-cell communication hotspots in spatial
    transcriptomics data using bivariate Local Moran's I statistics
    on hexagonally binned cells. Provides functions for spatial
    weighting, ligand-receptor pair filtering, hotspot detection,
    and visualisation of sender-receiver cell-type interactions.

A method for the Bayesian functional linear regression model (scalar-on-function),
  including two estimators of the coefficient function and an estimator of its support.
  A representation of the posterior distribution is also available. Grollemund P-M., Abraham C., 
  Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.

Implements regression models for binary data on the absolute risk scale. These models are applicable to cohort and population-based case-control data.

Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting, implementing the methods of Chung, et al. (2013) <doi:10.1007/s11336-013-9328-2>. Extends package 'lme4' (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).

Data files and functions accompanying the book Korner-Nievergelt, Roth, von Felten, Guelat, Almasi, Korner-Nievergelt (2015) "Bayesian Data Analysis in Ecology using R, BUGS and Stan", Elsevier, New York.