Data sets for book "Basic Statistics and Data Analysis" by
    Larry J. Kitchens.

Exposes the binary search functions of the C++ standard library (std::lower_bound, std::upper_bound) plus other convenience functions, allowing faster lookups on sorted vectors.

Performs goodness of fit test for the Birnbaum-Saunders distribution and provides the maximum likelihood estimate and the method-of-moments estimate. For more details, see Park and Wang (2013) <arXiv:2308.10150>. This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government (MSIT) (No. 2022R1A2C1091319, RS-2023-00242528).

Bayesian survival model using Weibull regression on both scale and shape parameters. Dependence of shape parameter on covariates permits deviation from proportional-hazard assumption, leading to dynamic - i.e. non-constant with time - hazard ratios between subjects. Bayesian Lasso shrinkage in the form of two Laplace priors - one for scale and one for shape coefficients - allows for many covariates to be included. Cross-validation helper functions can be used to tune the shrinkage parameters. Monte Carlo Markov Chain (MCMC) sampling using a Gibbs wrapper around Radford Neal's univariate slice sampler (R package MfUSampler) is used for coefficient estimation.

The function estimates the hazard function non parametrically from a survival object (possibly adjusted for covariates). 
	     The smoothed estimate is based on B-splines from the perspective of generalized linear mixed models. Left truncated and right censoring data are allowed. 
	     The package is based on the work in Rebora P (2014) <doi:10.32614/RJ-2014-028>.

A collection of integrated tools designed to seamlessly interact with each other for the analysis of biogenic silica 'bSi' in inland and marine sediments. These tools share common data representations and follow a consistent 'API' design. The primary goal of the 'bSi' package is to simplify the installation process, facilitate data loading, and enable the analysis of multiple samples for biogenic silica fluxes. This package is designed to enhance the efficiency and coherence of the entire 'bSi' analytic workflow, from data loading to model construction and visualization tailored towards reconstructing productivity in aquatic ecosystems.