Estimates group-level means and standard deviations from
    binned (coarsened) count data, where the within-bin scores are
    unobserved.  The package implements three methods that share a
    common output structure: bin_means() (a fast estimator that
    assumes within-district normality and uses pooled bin proportions
    to derive bin-conditional truncated-normal expectations),
    mle_hetop() (maximum likelihood for the heteroskedastic ordered
    probit model of Reardon, Shear, Castellano and Ho 2017
    <doi:10.3102/1076998616666279>), and fh_hetop() (the Bayesian
    Fay-Herriot variant of Lockwood, Castellano and Shear 2018
    <doi:10.3102/1076998618795124>).  The mle_hetop() and fh_hetop()
    functions are forked from the 'HETOP' package by J. R. Lockwood
    ('CRAN', last released 2019).  mle_hetop() has been modified to
    speed up the runtime via a vectorized inner loop and to remove
    two user-facing arguments (fixedcuts and svals) that some users
    found confusing; cutpoints and starting values are now derived
    internally from the data.

Binford's hunter-gatherer data includes more than 200 variables
    coding aspects of hunter-gatherer subsistence, mobility, and social organization
    for 339 ethnographically documented groups of hunter-gatherers.

Provides maximum likelihood estimates of the 
    performance parameters that drive a binomial distribution of observed 
    errors, and takes full advantage of zero error observations. High performance 
    communications systems typically have inherent noise sources and other 
    performance limitations that need to be estimated. Measurements made at 
    high signal to noise ratios typically result in zero 
    errors due to limitation in available measurement time. Package includes 
    theoretical performance functions for common modulation schemes (Proakis, 
    "Digital Communications" (1995, <ISBN:0-07-051726-6>)), polarization shifted 
    QPSK (Agrell & Karlsson (2009, <DOI:10.1109/JLT.2009.2029064>)), and utility 
    functions to work with the performance functions.