Forecasters predicting the chances of a future event may disagree due to
differing evidence or noise. To harness the collective evidence of the crowd,
Ville Satopää (2021) "Regularized Aggregation of One-off Probability Predictions"
<https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3769945> proposes a Bayesian
aggregator that is regularized by analyzing the forecasters' disagreement and ascribing
over-dispersion to noise. This aggregator requires no user intervention and can be computed
efficiently even for a large numbers of predictions. The author evaluates
the aggregator on subjective probability predictions collected during
a four-year forecasting tournament sponsored by the US intelligence community.
The aggregator improves the accuracy of simple averaging by around 20% and
other state-of-the-art aggregators by 10-25%. The advantage stems almost
exclusively from improved calibration. This aggregator -- know as "the revealed
aggregator" -- inputs a) forecasters' probability predictions (p) of a future binary event
and b) the forecasters' common prior (p0) of the future event. In this R-package,
the function sample_aggregator(p,p0,...) allows the user to calculate the revealed
aggregator. Its use is illustrated with a simple example.

Visualize Combined Action Response Surfaces and Report BRAID
Analyses
Provides functions to generate, format, and style surface plots for visualizing combined action data.  Also provides functions for reporting on a BRAID analysis, including plotting curve-shifts, calculating IAE values, and producing full BRAID analysis reports.

Fitting Dose Response with the BRAID Combined Action Model
Contains functions for evaluating, analyzing, and fitting combined action dose response surfaces with the Bivariate Response to Additive Interacting Dose (BRAID) model of combined action.

A set of tools for performing graph theory analysis of brain MRI
data. It is best suited to data from a Freesurfer analysis (cortical
thickness, volumes, local gyrification index, surface area), but also works
with e.g., tractography data from FSL. It contains a graphical user
interface for graph visualization and data exploration.
R (>= 3.0.0), igraph (>= 1.0.0), RGtk2, cairoDevice
abind, boot, data.table, foreach, ggplot2, Hmisc, methods,
oro.nifti, parallel, plyr, scales