Implementation of the Control Polygon Reduction and Control Net
    Reduction methods for finding parsimonious B-spline regression models.

Implements the three-step workflow for robust analysis of change in 
    two repeated measurements of continuous outcomes, described in Ning et al.
    (in press), "Robust estimation of the effect of an exposure on the change in
    a continuous outcome", BMC Medical Research Methodology.

Calculate date of birth, age, and gender, and generate anonymous
    sequence numbers from CPR numbers.
    <https://en.wikipedia.org/wiki/Personal_identification_number_(Denmark)>.

The primary function makeCPMSampler() generates a sampler function which performs the correlated pseudo-marginal method of Deligiannidis, Doucet and Pitt (2017) <arXiv:1511.04992>. If the 'rho=' argument of makeCPMSampler() is set to 0, then the generated sampler function performs the original pseudo-marginal method of Andrieu and Roberts (2009) <DOI:10.1214/07-AOS574>. The sampler function is constructed with the user's choice of prior, parameter proposal distribution, and the likelihood approximation scheme. Note that this algorithm is not automatically tuned--each one of these arguments must be carefully chosen.

Load Current Population Survey (CPS) microdata into R using the
    'Census Bureau Data' API
    (<https://www.census.gov/data/developers/data-sets.html>), including basic
    monthly CPS and CPS ASEC microdata.

Nonparametric change point estimation for survival data based on p-values of exact binomial tests.

Simulates time-to-event data
    with type I right censoring using two methods: the inverse CDF
    method and our proposed memoryless method. The latter method
    takes advantage of the memoryless property of survival and
    simulates a separate distribution between change-points. We
    include two parametric distributions: exponential and Weibull.
    Inverse CDF method draws on the work of Rainer Walke (2010), 
    <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.