Forms likelihood-based confidence intervals
    (LBCIs) for parameters in structural equation modeling,
    introduced in Cheung and Pesigan (2023)
    <doi:10.1080/10705511.2023.2183860>. Currently
    implements the algorithm illustrated by Pek and Wu
    (2018) <doi:10.1037/met0000163>, and supports the robust
    LBCI proposed by Falk (2018)
    <doi:10.1080/10705511.2017.1367254>.

Monte Carlo confidence intervals for free and defined parameters
    in models fitted in the structural equation modeling package 'lavaan'
    can be generated using the 'semmcci' package.
    'semmcci' has three main functions, namely, MC(), MCMI(), and MCStd().
    The output of 'lavaan' is passed as the first argument
    to the MC() function or the MCMI() function to generate Monte Carlo confidence intervals.
    Monte Carlo confidence intervals for the standardized estimates
    can also be generated by passing the output of the MC() function or the MCMI() function
    to the MCStd() function.
    A description of the package and code examples
    are presented in Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.

Provides Markov Chain Monte Carlo (MCMC) routine for the 
             structural equation modelling described in 
             Maity et. al. (2020) <doi:10.1093/bioinformatics/btaa286>. This MCMC sampler is 
             useful when one attempts to perform an integrative survival analysis for multiple 
             platforms of the Omics data where the response is time to event and the 
             predictors are different omics expressions for different platforms.

Provides methods for constructing and maintaining a database of presentations in R. The presentations are either ones that the user gives or gave or presentations at a particular event or event series. The package also provides a plot method for the interactive mapping of the presentations using 'leaflet' by grouping them according to country, city, year and other presentation attributes. The markers on the map come with popups providing presentation details (title, institution, event, links to materials and events, and so on).