| Name : R-metaggR
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| Version : 0.3.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.1.9
| Date : 2024-06-14 11:10:15
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| Group : Development/Libraries/Other
| Source RPM : R-metaggR-0.3.0-lp153.1.9.src.rpm
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| Size : 0.37 MB
| |
| Packager : (none)
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| Summary : Calculate the Knowledge-Weighted Estimate
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Description :
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.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
