Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these	calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled.

Functions to be used in conjunction with the 'Sequential' package that allows for planning of observational database studies that will be analyzed with exact sequential analysis. This package supports Poisson- and binomial-based data. The primary function, seq_wrapper(...), accepts parameters for simulation of a simple exposure pattern and for the 'Sequential' package setup and analysis functions. The exposure matrix is used to simulate the true and false positive and negative populations (Green (1983) <doi:10.1093/oxfordjournals.aje.a113521>, Brenner (1993) <doi:10.1093/oxfordjournals.aje.a116805>). Functions are then run from the 'Sequential' package on these populations, which allows for the exploration of outcome misclassification in data.

Multi-generational pedigree inference from incomplete data on
    hundreds of SNPs, including parentage assignment and sibship clustering.
    See Huisman (2017) (<DOI:10.1111/1755-0998.12665>) for more information.

Apache Drill is a low-latency distributed query engine designed to enable 
    data exploration and analysis on both relational and non-relational data stores, 
    scaling to petabytes of data. Methods are provided that enable working with Apache 
    Drill instances via the REST API, DBI methods
    and using 'dplyr'/'dbplyr' idioms. Helper functions are included to facilitate
    using official Drill Docker images/containers.

Enables reading and writing binary and ASCII data to 
             RS232/RS422/RS485 or any other virtual serial interface of the
             computer.