isotone

the vector that will be fitted with the regression

if TRUE the curve is set to be increasing, else FALSE

increasing

if TRUE then faster C code is used rather than R

Ccode

It is applied in order to estimate the h() function in the Data-Driven Haar-Fisz algorithm

regression

Contains the normalizing and variance stabilizing
Data-Driven Haar-Fisz algorithm. Also contains related algorithms
for simulating from certain microarray gene intensity models and
evaluation of certain transformations. Contains cDNA and shipping
credit flow data.

Guy Nason

DDHFm

Variance Stabilization by Data-Driven Haar-Fisz (for
Microarrays)

Efthimios Motakis

Piotr Fryzlewicz

isotone function

<dl> <dt>x</dt>
<dd>the vector that will be fitted with the regression</dd> <dt>wt</dt>
<dd>a vector of weights</dd> <dt>increasing</dt>
<dd>if TRUE the curve is set to be increasing, else FALSE</dd> <dt>Ccode</dt>
<dd>if TRUE then faster C code is used rather than R</dd></dl>

Arguments

Bernard Silverman, with C modifications by GPN

Author

Performs Isotone regression using "pool-adjacent-violators" algorithm — isotone

<dl>

 <dt>x</dt>
<dd>the vector that will be fitted with the regression</dd>

 <dt>wt</dt>
<dd>a vector of weights</dd>

 <dt>increasing</dt>
<dd>if TRUE the curve is set to be increasing, else FALSE</dd>

 <dt>Ccode</dt>
<dd>if TRUE then faster C code is used rather than R</dd>

</dl>

isotone: Performs Isotone regression using "pool-adjacent-violators" algorithm

Description

Usage

Value

Arguments

Author

References