Tools for working with a new versatile
	discrete distribution, the db ("discretised Beta")
	distribution.  This package provides density (probability),
	distribution, inverse distribution (quantile) and random
	data generation functions for the db family.  It provides
	functions to effect conveniently maximum likelihood
	estimation of parameters, and a variety of useful plotting
	functions.  It provides goodness of fit tests and functions
	to calculate the Fisher information, different estimates of
	the hessian of the log likelihood and Monte Carlo estimation
	of the covariance matrix of the maximum likelihood parameter
	estimates.  In addition it provides analogous tools for
	working with the beta-binomial distribution which has been
	proposed as a competitor to the db distribution.

Computes the double bootstrap as discussed in McKnight, McKean, and Huitema (2000) <doi:10.1037/1082-989X.5.1.87>. 
              The double bootstrap method provides a better fit for a linear model with autoregressive errors than ARIMA when the sample size is small.

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.