c(person(given = "Ville",
family = "Satopää",
email = "ville.satopaa@gmail.com",
role = c("aut", "cre", "cph")),
person(given = "Asa",
family = "Palley",
role = "aut"))
According to a phenomenon known as "the wisdom of the crowds,"
combining point estimates from multiple judges often provides a
more accurate aggregate estimate than using a point estimate from
a single judge. However, if the judges use shared information in
their estimates, the simple average will over-emphasize this common
component at the expense of the judges’ private information.
Asa Palley & Ville Satopää (2021) "Boosting the Wisdom of Crowds
Within a Single Judgment Problem: Selective Averaging Based on Peer Predictions"
<https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3504286> proposes
a procedure for calculating a weighted average of the judges’ individual
estimates such that resulting aggregate estimate appropriately combines
the judges' collective information within a single estimation problem.
The authors use both simulation and data from six experimental studies
to illustrate that the weighting procedure outperforms existing averaging-like
methods, such as the equally weighted average, trimmed average, and median.
This aggregate estimate -- know as "the knowledge-weighted estimate" --
inputs a) judges' estimates of a continuous outcome (E) and
b) predictions of others' average estimate of this outcome (P).
In this R-package, the function knowledge_weighted_estimate(E,P)
implements the knowledge-weighted estimate. Its use is illustrated
with a simple stylized example and on real-world experimental data.
Ville Satopää [aut, cre, cph],
Asa Palley [aut]

Metaheuristic Optimization Framework for Preprocessing
Combinations
Automation of preprocessing often requires computationally costly
preprocessing combinations. This package helps to find near-best combinations
faster. Sub heuristics supported are random and grid restarts, taboo list,
decreasing probability for accepting inferior solutions and location of
previously best solution candidate is compared to. The package is intended
to be used with package 'preprocomb' and takes its 'GridClass' object as input.