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	<longdescription>
		Bayesian Analyses for One- and Two-Sample Inference and
		Regression Methods // Perform fundamental analyses using
		Bayesian parametric and non-parametric inference (regression,
		anova, 1 and 2 sample inference, non-parametric tests, etc.).
		(Practically) no Markov chain Monte Carlo (MCMC) is used; all
		exact finite sample inference is completed via closed form
		solutions or else through posterior sampling automated to
		ensure precision in interval estimate bounds. Diagnostic plots
		for model assessment, and key inferential quantities (point and
		interval estimates, probability of direction, region of
		practical equivalence, and Bayes factors) and model
		visualizations are provided. Bayes factors are computed either
		by the Savage Dickey ratio given in Dickey (1971)
		doi:10.1214/aoms/1177693507 or by Chib's method as given in
		doi:10.1080/01621459.1995.10476635. Interpretations are from
		Kass and Raftery (1995) doi:10.1080/01621459.1995.10476572.
		ROPE bounds are based on discussions in Kruschke (2018)
		doi:10.1177/2515245918771304. Methods for determining the
		number of posterior samples required are described in Doss et
		al. (2014) doi:10.1214/14-EJS957. Bayesian model averaging is
		done in part by Feldkircher and Zeugner (2015)
		doi:10.18637/jss.v068.i04. Methods for contingency table
		analysis is described in Gunel et al. (1974)
		doi:10.1093/biomet/61.3.545. Variational Bayes (VB) methods are
		described in Salimans and Knowles (2013) doi:10.1214/13-BA858.
		Mediation analysis uses the framework described in Imai et al.
		(2010) doi:10.1037/a0020761. The loss-likelihood bootstrap used
		in the non-parametric regression modeling is described in
		Lyddon et al. (2019) doi:10.1093/biomet/asz006. Non-parametric
		survival methods are described in Qing et al. (2023)
		doi:10.1002/pst.2256. Methods used for the Bayesian Wilcoxon
		signed-rank analysis is given in Chechile (2018)
		doi:10.1080/03610926.2017.1388402 and for the Bayesian Wilcoxon
		rank sum analysis in Chechile (2020)
		doi:10.1080/03610926.2018.1549247.  Correlation analysis
		methods are carried out by Barch and Chechile (2023)
		doi:10.32614/CRAN.package.DFBA, and described in Lindley and
		Phillips (1976) doi:10.1080/00031305.1976.10479154 and Chechile
		and Barch (2021) doi:10.1016/j.jmp.2021.102638.  See also
		Chechile (2020, ISBN: 9780262044585).
	</longdescription>
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