weight_outlier {aggreCAT} | R Documentation |
Weighting method: Down weighting outliers
Description
This method down-weights outliers.
Usage
weight_outlier(expert_judgements)
Arguments
expert_judgements |
A dataframe in the form of data_ratings |
Details
This function is used by LinearWAgg to calculate weights for the aggregation type
"OutWAgg"
. Outliers are given less weight by using the squared difference between the
median of an individual's best estimates across all claims and their best estimate
for the claim being assessed:
\[d_{i,c} = \left(median{{B_{i,c}}_{_{i=1,...,N}}} - B_{i,c}\right)^2\]
Weights are given by 1 minus the proportion of the individual's squared difference relative to the maximum squared difference for the claim across all individuals:
\[w\_out_{i} = 1 - \frac{d_{i,c}}{\max({d_c})})\]Value
A tibble in the form of the input expert_judgements
argument with additional columns
supplying the calculated weight for each row's observation.
[Package aggreCAT version 1.0.0 Index]