Package contains a simple SMTP client with minimal dependencies which 
        provides a portable solution for sending email, including file attachments and inline html reports, 
        from within R. SMTP Authentication and SSL/STARTTLS is implemented using curl.

Stacked ensemble for regression tasks based on 'mlr3' framework with a pipeline for preprocessing numeric and factor features and hyper-parameter tuning using grid or random search.

Implements a suite of sensitivity analysis tools 
  that extends the traditional omitted variable bias framework and makes it easier 
  to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.

Provides tools to conduct interpretable sensitivity analyses for weighted estimators,
    introduced in Huang (2024) <doi:10.1093/jrsssa/qnae012> and 
    Hartman and Huang (2024) <doi:10.1017/pan.2023.12>. 
    The package allows researchers to generate the set of recommended sensitivity summaries
    to evaluate the sensitivity in their underlying weighting estimators to omitted moderators or confounders. 
    The tools can be flexibly applied in causal inference settings (i.e., in external and internal validity contexts)
    or survey contexts.

Sensitivity analysis for trials with irregular and informative 
    assessment times, based on a new influence function-based, augmented 
    inverse intensity-weighted estimator.

Provides an interface to the 'Sensibo Sky' API which allows to remotely control non-smart air conditioning units.
  See <https://sensibo.com> for more informations.

An implementation of sensitivity analysis for phylogenetic comparative
 methods. The package is an umbrella of statistical and graphical methods that 
 estimate and report different types of uncertainty in PCM:
 (i) Species Sampling uncertainty (sample size; influential species and clades).
 (ii) Phylogenetic uncertainty (different topologies and/or branch lengths).
 (iii) Data uncertainty (intraspecific variation and measurement error).