Provides functions to aid the identification of probable/possible
    duplicates in Plant Genetic Resources (PGR) collections using
    'passport databases' comprising of information records of each constituent
    sample. These include methods for cleaning the data, creation of a
    searchable Key Word in Context (KWIC) index of keywords associated with
    sample records and the identification of nearly identical records with
    similar information by fuzzy, phonetic and semantic matching of keywords.

Inference and visualize gene regulatory network based on single-cell RNA sequencing pseudo-time information.

Computes the generalized synthetic control estimator described in
    Powell (2017) <doi:10.7249/WR1142>.  Provides both point estimates, and hypothesis testing.

Create PostgreSQL statements/scripts from R, optionally executing the SQL statements.
    Common SQL operations are included, although not every configurable option is available at this time. 
    SQL output is intended to be compliant with PostgreSQL syntax specifications. PostgreSQL documentation is available here
    <https://www.postgresql.org/docs/current/index.html>.

The purpose of 'PH1XBAR' is to build a Phase I Shewhart control chart for the basic Shewhart, the variance components and the ARMA models in R for subgrouped and individual data. More details can be found: Yao and Chakraborti (2020) <doi: 10.1002/qre.2793>, and Yao and Chakraborti (2021) <doi: 10.1080/08982112.2021.1878220>.

An implementation of Bayesian single-arm phase II design methods for binary outcome based on posterior
  probability (Thall and Simon (1994) <doi:10.2307/2533377>) and predictive probability (Lee and Liu (2008) <doi:10.1177/1740774508089279>).

Calculate the Bayesian posterior/predictive probability and
    determine the sample size and stopping boundaries for single-arm Phase II design.

Provide multinomial design methods under intersection-union test (IUT) and union-intersection test (UIT) scheme for Phase II trial. The design types include : Minimax (minimize the maximum sample size), Optimal (minimize the expected sample size), Admissible (minimize the Bayesian risk) and Maxpower (maximize the exact power level).