setGamma

Internal function: Set tuning parameter - gamma

internal

Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigen-functions
by using the alternating direction method of multipliers algorithm (Wang and Huang, 2017, <DOI:10.1080/10618600.2016.1157483>). The
method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D.

Wen-Ting Wang

SpatPCA

Regularized Principal Component Analysis for Spatial Data

Hsin-Cheng Huang

setGamma function

<dl><dt>gamma</dt>
<dd>Vector of a nonnegative hyper parameter sequence for tuning eigenvalues. Default is NULL.</dd>
<dt>Y</dt>
<dd>Data matrix</dd></dl>

Arguments

Internal function: Set tuning parameter - gamma — setGamma

<dl>

<dt>gamma</dt>
<dd>Vector of a nonnegative hyper parameter sequence for tuning eigenvalues. Default is NULL.</dd>


<dt>Y</dt>
<dd>Data matrix</dd>

</dl>

setGamma: Internal function: Set tuning parameter - gamma

Description

Usage

Value

Arguments