Linear regression functions using Huber and bisquare psi functions. Optimal weights are calculated using IRLS algorithm.

Functions for Robust Bayesian Small Area Estimation.

Data sets are often corrupted by outliers. When data are multivariate outliers can be classified as case-wise or cell-wise. The latters are particularly challenge to handle. We implement a robust estimation procedure for Seemingly Unrelated Regression Models which is able to cope well with both type of outliers. Giovanni Saraceno, Fatemah Alqallaf, Claudio Agostinelli (2021) <arXiv:2107.00975>.

Robust Estimation of Variance Component Models by classic and composite robust procedures. The composite procedures are robust against outliers generated by the Independent Contamination Model.

Robustness -- 'eXperimental', 'eXtraneous', or 'eXtraordinary'
  Functionality for Robust Statistics.  Hence methods which are not well established,
  often related to methods in package 'robustbase'.  Amazingly, 'BACON()', originally by
  Billor, Hadi, and Velleman (2000) <doi:10.1016/S0167-9473(99)00101-2>
  has become established in places.  The "barrow wheel" `rbwheel()` is from
  Stahel and Mächler (2009) <doi:10.1111/j.1467-9868.2009.00706.x>.

Helps users in quickly visualizing risk-of-bias 
    assessments performed as part of a systematic review. It allows users to 
    create weighted bar-plots of the distribution of risk-of-bias judgments 
    within each bias domain, in addition to traffic-light plots of the 
    specific domain-level judgments for each study. The resulting figures are 
    of publication quality and are formatted according the risk-of-bias 
    assessment tool use to perform the assessments. Currently, the supported 
    tools are ROB2.0 (for randomized controlled trials; Sterne et al (2019)  
    <doi:10.1136/bmj.l4898>), ROBINS-I (for non-randomised studies of 
    interventions; Sterne et al (2016) <doi:10.1136/bmj.i4919>), and QUADAS-2 
    (for diagnostic accuracy studies; Whiting et al (2011) 
    <doi:10.7326/0003-4819-155-8-201110180-00009>).