sample_me

Collapsed Gibbs sampler for hWRU. Internal function

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

sample_me function

<dl><dt>last_name</dt>
<dd>Integer vector of last name identifiers for each record (zero indexed; as all that follow). Must match columns numbers in M_rs.</dd>
<dt>first_name</dt>
<dd>See last_name</dd>
<dt>mid_name</dt>
<dd>See last_name</dd>
<dt>geo</dt>
<dd>Integer vector of geographic units for each record. Must match column number in N_rg</dd>
<dt>N_rg</dt>
<dd>Integer matrix of race | geography counts in census (geograpgies in columns).</dd>
<dt>pi_s</dt>
<dd>Numeric matrix of race | surname prior probabilities.</dd>
<dt>pi_f</dt>
<dd>Same as <code>pi_s</code>, but for first names.</dd>
<dt>pi_m</dt>
<dd>Same as <code>pi_s</code>, but for middle names.</dd>
<dt>pi_nr</dt>
<dd>Matrix of marginal probability distribution over missing names; non-keyword names default to this distribution.</dd>
<dt>which_names</dt>
<dd>Integer; 0=surname only. 1=surname + first name. 2= surname, first, and middle names.</dd>
<dt>samples</dt>
<dd>Integer number of samples to take after (in total)</dd>
<dt>burnin</dt>
<dd>Integer number of samples to discard as burn-in of Markov chain</dd>
<dt>race_init</dt>
<dd>Integer vector of initial race assignments</dd>
<dt>verbose</dt>
<dd>Boolean; should informative messages be printed?</dd></dl>

Arguments

Collapsed Gibbs sampler for hWRU. Internal function — sample_me

<dl>

<dt>last_name</dt>
<dd>Integer vector of last name identifiers for each record (zero indexed; as all that follow). Must match columns numbers in M_rs.</dd>


<dt>first_name</dt>
<dd>See last_name</dd>


<dt>mid_name</dt>
<dd>See last_name</dd>


<dt>geo</dt>
<dd>Integer vector of geographic units for each record. Must match column number in N_rg</dd>


<dt>N_rg</dt>
<dd>Integer matrix of race | geography counts in census (geograpgies in columns).</dd>


<dt>pi_s</dt>
<dd>Numeric matrix of race | surname prior probabilities.</dd>


<dt>pi_f</dt>
<dd>Same as <code>pi_s</code>, but for first names.</dd>


<dt>pi_m</dt>
<dd>Same as <code>pi_s</code>, but for middle names.</dd>


<dt>pi_nr</dt>
<dd>Matrix of marginal probability distribution over missing names; non-keyword names default to this distribution.</dd>


<dt>which_names</dt>
<dd>Integer; 0=surname only. 1=surname + first name. 2= surname, first, and middle names.</dd>


<dt>samples</dt>
<dd>Integer number of samples to take after (in total)</dd>


<dt>burnin</dt>
<dd>Integer number of samples to discard as burn-in of Markov chain</dd>


<dt>race_init</dt>
<dd>Integer vector of initial race assignments</dd>


<dt>verbose</dt>
<dd>Boolean; should informative messages be printed?</dd>

</dl>

sample_me: Collapsed Gibbs sampler for hWRU. Internal function

Description

Usage

Arguments