Estimate the lower and upper bound of asymptomatic cases in an 
    epidemic using the capture/recapture methods from Böhning et al. (2020) 
    <doi:10.1016/j.ijid.2020.06.009> and Rocchetti et al. (2020)
    <doi:10.1101/2020.07.14.20153445>. Note there is currently some discussion
    about the validity of the methods implemented in this package. You should
    read carefully the original articles, alongside this answer from Li et al.
    (2022) <doi:10.48550/arXiv.2209.11334> before using this package in your
    project.

Write sequential-looking code that pauses and resumes.
             gen() creates a generator, an iterator that returns a
             value and pauses each time it reaches a yield() call.
             async() creates a promise, which runs until it reaches
             a call to await(), then resumes when information is available.
             These work similarly to generator and async constructs
             from 'Python' or 'JavaScript'. Objects produced are
             compatible with the 'iterators' and 'promises' packages.
             Version 0.3 supports on.exit, single-step debugging,
             stream() for making asynchronous iterators, and
             delimited goto() in switch() calls.

Estimation of regression models for sparse asynchronous 
    longitudinal observations, where time-dependent response and covariates 
    are mismatched and observed intermittently within subjects. Kernel 
    weighted estimating equations are used for generalized linear models 
    with either time-invariant or time-dependent coefficients. Cao, H.,
    Li, J., and Fine, J. P. (2016) <doi:10.1214/16-EJS1141>. Cao, H., 
    Zeng, D., and Fine, J. P. (2015) <doi:10.1111/rssb.12086>.

Provides a collection of psychometric methods to process item metadata
 and use target assessment and measurement blueprint constraints to assemble a test form. Currently two automatic
 test assembly (ata) approaches are enabled. For example, the weighted (positive) deviations method, wdm(), proposed
 by Swanson and Stocking (1993) <doi:10.1177/014662169301700205> was implemented in its full specification allowing
 for both item selection as well as test form refinement. The linear constraint programming approach, atalp(), uses the 
 linear equation solver by Berkelaar et. al (2014) <http://lpsolve.sourceforge.net/5.5/>
 to enable a variety of approaches to select items.