A native 'R' client library for querying the 'Prometheus' 
    time-series database, using the 'PromQL' query language.

Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation. Calculations of propagated uncertainties are based on matrix calculus including covariance structure according to Arras 1998 <doi:10.3929/ethz-a-010113668> (first order), Wang & Iyer 2005 <doi:10.1088/0026-1394/42/5/011> (second order) and BIPM Supplement 1 (Monte Carlo) <doi:10.59161/JCGM101-2008>.

Computes two-sample confidence intervals for single, paired and independent proportions.

Implementation of propensity clustering and
        decomposition as described in Ranola et al. (2013) <doi:10.1186/1752-0509-7-21>. 
        Propensity decomposition can be viewed on the
        one hand as a generalization of the eigenvector-based
        approximation of correlation networks, and on the other hand as
        a generalization of random multigraph models and
        conformity-based decompositions.

Carrying out inferences about any linear combination of proportions and the ratio of two proportions.

The Prognostic Regression Offsets with Propagation of
    ERrors (for Treatment Effect Estimation) package facilitates
    direct adjustment for experiments and observational studies that
    is compatible with a range of study designs and covariance
    adjustment strategies. It uses explicit specification of clusters,
    blocks and treatment allocations to furnish probability of
    assignment-based weights targeting any of several average
    treatment effect parameters, and for standard error calculations
    reflecting these design parameters. For covariance adjustment of
    its Hajek and (one-way) fixed effects estimates, it enables
    offsetting the outcome against predictions from a dedicated
    covariance model, with standard error calculations propagating
    error as appropriate from the covariance model.

Allows to parse 'Java' properties files in the context of
  'R Service Bus' applications.