Utility functions to download and process data produced by the ALARM Project,
    including 2020 redistricting files Kenny and McCartan (2021) 
    <https://alarm-redist.org/posts/2021-08-10-census-2020/> and the 50-State 
    Redistricting Simulations of McCartan, Kenny, Simko, Garcia, Wang, Wu, 
    Kuriwaki, and Imai (2022) <doi:10.7910/DVN/SLCD3E>. The package extends 
    the data introduced in McCartan, Kenny, Simko, Garcia, Wang, Wu, Kuriwaki,
    and Imai (2022) <doi:10.1038/s41597-022-01808-2> to also include states with 
    only a single district. The package also includes the Japanese 2022 
    redistricting files from the 47-Prefecture Redistricting Simulations of 
    Miyazaki, Yamada, Yatsuhashi, and Imai (2022) <doi:10.7910/DVN/Z9UKSH>.

Penalized variable selection tools for the Cox 
    proportional hazards model with interval censored and possibly 
    left truncated data. It performs variable selection via 
    penalized nonparametric maximum likelihood estimation with an 
    adaptive lasso penalty. The optimal thresholding parameter can be 
    searched by the package based on the profile Bayesian information 
    criterion (BIC). The asymptotic validity of the methodology is 
    established in Li et al. (2019 <doi:10.1177/0962280219856238>). 
    The unpenalized nonparametric maximum likelihood estimation for 
    interval censored and possibly left truncated data is also 
    available.

Perform parallel factor analysis (PARAFAC: Hitchcock, 1927)
	<doi:10.1002/sapm192761164> on fluorescence excitation-emission
	matrices: handle scattering signal and inner filter effect, scale
	the dataset, fit the model; perform split-half validation or
	jack-knifing. Modified approaches such as Whittaker interpolation,
	randomised split-half, and fluorescence and scattering model
	estimation are also available. The package has a low dependency
	footprint and has been tested on a wide range of R versions.

Implements discrete time deterministic and stochastic age-structured population dynamics models described in Erguler and others (2016) <doi:10.1371/journal.pone.0149282> and Erguler and others (2017) <doi:10.1371/journal.pone.0174293>.