Contains functions that check for formatting of the Subject Phenotype data set and data dictionary as specified by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.

Fast fitting of generalised linear models on moderately large datasets, by taking an initial sample, fitting in memory, then evaluating the score function for the full data in the database. Thomas Lumley <doi:10.1080/10618600.2019.1610312>.

Provides an implementation of a mixture of hidden Markov models 
    (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering 
    (DBHC) algorithm. The DBHC algorithm is an HMM Clustering 
    algorithm that finds a mixture of discrete-output HMMs while using 
    heuristics based on Bayesian Information Criterion (BIC) to search for the 
    optimal number of HMM states and the optimal number of clusters.

Client for programmatic access to the South Florida Water
  Management District's 'DBHYDRO' database at 
  <https://www.sfwmd.gov/science-data/dbhydro>, with functions
  for accessing hydrologic and water quality data.

A database interface definition for communication between R
    and relational database management systems.  All classes in this
    package are virtual and need to be extended by the various R/DBMS
    implementations.

Query database tables over a 'DBI' connection using 'data.table' syntax.
  Attach database schemas to the search path. Automatically merge using foreign
  key constraints.

A helper that tests DBI back ends for conformity to the
    interface.

Doubly censored data, as described in Chang and Yang (1987) <doi: 10.1214/aos/1176350608>), are commonly seen in many fields. We use EM algorithm to compute the non-parametric MLE (NPMLE) of the cummulative probability function/survival function and the two censoring distributions. One can also specify a constraint F(T)=C, it will return the constrained NPMLE and the -2 log empirical likelihood ratio for this constraint. This can be used to test the hypothesis about the constraint and, by inverting the test, find confidence intervals for probability or quantile via empirical likelihood ratio theorem. Influence functions of hat F may also be calculated, but currently, the it may be slow.