the predictor variable. Missing values are allowed.

degrees of freedom; one can specify <code>df</code> rather than
 <code>knots</code>; <code>bs()</code> then chooses <code>df-degree</code> (minus one
 if there is an intercept) knots at suitable quantiles of <code>x</code>
 (which will ignore missing values). The default, <code>NULL</code>,
 takes the number of inner knots as <code>length(knots)</code>. If that is
 zero as per default, that corresponds to <code>df = degree - intercept</code>.

the internal breakpoints that define the
 spline. The default is <code>NULL</code>, which results in a basis for
 ordinary polynomial regression. Typical values are the mean or
 median for one knot, quantiles for more knots. See also
 <code>Boundary.knots</code>.

knots

degree of the piecewise polynomial---default is <code>3</code> for
 cubic splines.

degree

if <code>TRUE</code>, an intercept is included in the
 basis; default is <code>FALSE</code>.

intercept

boundary points at which to anchor the B-spline
 basis (default the range of the non-<code><a rd-options="" href="/link/NA?package=JointAI&version=1.0.2" data-mini-rdoc="JointAI::NA">NA</a></code> data). If both
 <code>knots</code> and <code>Boundary.knots</code> are supplied, the basis
 parameters do not depend on <code>x</code>. Data can extend beyond
 <code>Boundary.knots</code>.

Boundary.knots

This function just calls <code>bs()</code> from the
<a href="https://CRAN.R-project.org/package=splines">splines</a>
package.

internal

Joint analysis and imputation of incomplete data in the Bayesian
framework, using (generalized) linear (mixed) models and extensions there of,
survival models, or joint models for longitudinal and survival data.
Incomplete covariates, if present, are automatically imputed.
The package performs some preprocessing of the data and creates a 'JAGS'
model, which will then automatically be passed to 'JAGS'
<http://mcmc-jags.sourceforge.net/> with the help of
the package 'rjags'.

Nicole Erler

JointAI

Joint Analysis and Imputation of Incomplete Data

Nicole S. Erler

bs function

boundary points at which to anchor the B-spline
 basis (default the range of the non-<code><a rd-options='' href='NA'>NA</a></code> data). If both
 <code>knots</code> and <code>Boundary.knots</code> are supplied, the basis
 parameters do not depend on <code>x</code>. Data can extend beyond
 <code>Boundary.knots</code>.

This function just calls <code>bs()</code> from the
<a href='https://CRAN.R-project.org/package=splines'>splines</a>
package.

bs: Generate a Basis Matrix for Natural Cubic Splines

Description

Usage

Arguments