bladder

A dataset of 500 observations corresponding to 500 probes of the aCGH profile of a bladder cancer patient.
The original data are provided by <cite>Stransky et al. (2006)</cite>. This dataset consists of probes 1 through 500 of individual 1.

datasets

Perform one-dimensional spline regression with automatic knot selection.
This package uses a penalized approach to select the most relevant knots.
B-splines of any degree can be fitted. More details in 'Goepp et al. (2018)',
"Spline Regression with Automatic Knot Selection", <arXiv:1808.01770>.

Vivien Goepp

aspline

Spline Regression with Adaptive Knot Selection

Gr<c3><a9>gory Nuel

bladder function

A data frame with 500 observations and 2 variables:<dl class="dl-horizontal">
 <dt>x</dt><dd>probe number</dd>
 <dt>y</dt><dd>aCGH profile value</dd>
</dl>

Format

Bladder Cancer aCGH profile data — bladder

A data frame with 500 observations and 2 variables:<dl class='dl-horizontal'>
 <dt>x</dt><dd>probe number</dd>
 <dt>y</dt><dd>aCGH profile value</dd>
</dl>

bladder: Bladder Cancer aCGH profile data

Description

Usage

Arguments

Format