DATA1

Synthetic data from a single–index model \(y = f(X'\theta) + \varepsilon\)
with \(f(u) = u^2 \exp(u)\) and \(\varepsilon \sim N(0,\sigma^2)\).
The index vector is \(\theta = (2,1,1,1) / \| (2,1,1,1) \|_2\) and
\(\sigma = 0.5\).

datasets

Provides tools for fitting Bayesian single index models with
flexible choices of priors for both the index and the link function.
The package implements model estimation and posterior inference using
efficient MCMC algorithms built on the 'nimble' framework, allowing
users to specify, extend, and simulate models in a unified and
reproducible manner. The following methods are implemented in the
package: Antoniadis et al. (2004)
<https://www.jstor.org/stable/24307224>, Wang (2009)
<doi:10.1016/j.csda.2008.12.010>, Choi et al. (2011)
<doi:10.1080/10485251003768019>, Dhara et al. (2019)
<doi:10.1214/19-BA1170>, McGee et al. (2023) <doi:10.1111/biom.13569>.

Seowoo Jung

BayesSIM

Integrated Interface of Bayesian Single Index Models using
'nimble'

Eun-kyung Lee

DATA1 function

<dl>
 <dt>X</dt>
<dd>Numeric matrix of size 200 \(\times\) 4, entries i.i.d. \(Unif(-1, 1)\)</dd>
.
 <dt>y</dt>
<dd>Numeric vector of length 200.</dd>
</dl>

Format

Simulated Single–Index Data (n = 200, p = 4) — DATA1

<dl>
 <dt>X</dt>
<dd>Numeric matrix of size 200 \(\times\) 4, entries i.i.d. \(Unif(-1, 1)\)</dd>
.
 <dt>y</dt>
<dd>Numeric vector of length 200.</dd>


</dl>

DATA1: Simulated Single–Index Data (n = 200, p = 4)

Description

Usage

Arguments

Format

Examples