Joint frailty models have been widely used to study the associations between recurrent events and a survival outcome. However, existing joint frailty models only consider one or a few recurrent events
    and cannot deal with high-dimensional recurrent events. This package can be used to fit our recently developed penalized joint frailty model that can handle high-dimensional recurrent events. 
    Specifically, an adaptive lasso penalty is imposed on the parameters for the effects of the recurrent events on the survival outcome, which allows for variable selection. 
    Also, our algorithm is computationally efficient, which is based on the Gaussian variational approximation method.

Estimation of pharmacokinetic parameters using non-compartmental theory.

Calculate and compare the prediction probability (PK) values for Anesthetic Depth Indicators.
    The PK values are widely used for measuring the performance of anesthetic depth and were first 
    proposed by the group of Dr. Warren D. Smith in the paper 
    Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) <doi:10.1097/00000542-199601000-00005> and
    Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) <doi:10.1002/(SICI)1097-0258(19960615)15:11%3C1199::AID-SIM218%3E3.0.CO;2-Y>.
    The authors provided two 'Microsoft Excel' files in xls format for calculating and comparing PK values.
    This package provides an easy-to-use API for calculating and comparing PK values in R.

Automate pharmacokinetic/pharmacodynamic bioanalytical procedures based on best practices and regulatory recommendations.
    The package impose regulatory constrains and sanity checking for common bioanalytical procedures. 
    Additionally, 'PKbioanalysis' provides a relational infrastructure for plate management and injection sequence.

Pharmacokinetics is the study of drug absorption, distribution, 
   metabolism, and excretion. The pharmacokinetics model explains that how the 
   drug concentration change as the drug moves through the different compartments
   of the body. For pharmacokinetic modeling and analysis, it is essential
   to understand the basic pharmacokinetic parameters. All parameters are 
   considered, but only some of parameters are used in the model. Therefore, 
   we need to convert the estimated parameters to the other parameters after 
   fitting the specific pharmacokinetic model. This package is developed to help
   this converting work. For more detailed explanation of pharmacokinetic 
   parameters, see "Gabrielsson and Weiner" (2007), "ISBN-10: 9197651001";
   "Benet and Zia-Amirhosseini" (1995) <DOI: 10.1177/019262339502300203>; 
   "Mould and Upton" (2012) <DOI: 10.1038/psp.2012.4>;
   "Mould and Upton" (2013) <DOI: 10.1038/psp.2013.14>.