map_6class_to_5class

The MLP outputs probabilities for 6 categories:
(whi, bla, his, asi, aian, oth) -- see <code>EBISG_RACE_COLS</code> in the
Python helper. wru uses 5 categories: (whi, bla, his, asi, oth).
This function sums <code>aian</code> and <code>oth</code> into <code>oth</code>.

internal

Predicts individual race/ethnicity using surname, first name,
middle name, geolocation, and other attributes, such as gender and
age. The method utilizes Bayes' Rule (with optional measurement error
correction) to compute the posterior probability of each racial
category for any given individual. The package implements methods
described in Imai and Khanna (2016) "Improving Ecological Inference by
Predicting Individual Ethnicity from Voter Registration Records"
Political Analysis <DOI:10.1093/pan/mpw001> and Imai, Olivella, and
Rosenman (2022) "Addressing census data problems in race imputation
via fully Bayesian Improved Surname Geocoding and name supplements"
<DOI:10.1126/sciadv.adc9824>. The package also incorporates the data
described in Rosenman, Olivella, and Imai (2023) "Race and ethnicity
data for first, middle, and surnames"
<DOI:10.1038/s41597-023-02202-2>.

Brandon Bertelsen

Who are You? Bayesian Prediction of Racial Category Using
Surname, First Name, Middle Name, and Geolocation

Kabir Khanna

Santiago Olivella

Evan Rosenman

Alexander Rossell Hayes

Kosuke Imai

Noah Dasanaike

map_6class_to_5class function

<dl><dt>probs_6</dt>
<dd>A matrix with 6 columns named whi, bla, his, asi, aian, oth.</dd></dl>

Arguments

Map 6-class eBISG output to wru's 5-class system — map_6class_to_5class

<dl>

<dt>probs_6</dt>
<dd>A matrix with 6 columns named whi, bla, his, asi, aian, oth.</dd>

</dl>

map_6class_to_5class: Map 6-class eBISG output to wru's 5-class system

Description

Usage

Value

Arguments