duncan

The <code>duncan</code> data frame has 45 rows and columns. Data on the
prestige and other charachteristics of 45 U. S. occupations in 1950.

datasets

Fits generalised partial linear regression models using a Bayesian approach, where shape and
smoothness constraints are imposed on nonparametrically modelled predictors through shape-restricted splines, and
no constraints are imposed on optional parametrically modelled covariates. See Meyer et al. (2011) <doi/10.1080/10485252.2011.597852>
for more details. IMPORTANT: before installing 'bcgam', you need to install 'Rtools' (Windows) or 'Xcode' (Mac OS X). These are
required for the correct installation of 'nimble' (<https://r-nimble.org/download>).

Cristian Oliva-Aviles

bcgam

Bayesian Constrained Generalised Linear Models

Mary C. Meyer

duncan function

This data frame contains the following columns:<ul>
<li>type. Type of occupation. A factor with the following levels:
<code>prof</code>, professional and managerial; <code>wc</code>, white-collar;
<code>bc</code>, blue-collar.</li>
<li>income. Percent of males in occupation earning $3500 or more in 1950.</li>
<li>education. Percent of males in occupation in 1950 who where high-school graduates.</li>
<li>prestige. Percent of raters in NORC study rating occupation as excellent or 
good in prestige.</li>
</ul>

duncan: Duncan's occupational prestige data

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