checkNewLocationsForSpatpcaObject

Internal function: Validate new locations for a spatpca object

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

checkNewLocationsForSpatpcaObject function

<dl><dt>spatpca_object</dt>
<dd>An <code>spatpca</code> class object</dd>
<dt>x_new</dt>
<dd>New location matrix.</dd></dl>

Arguments

Internal function: Validate new locations for a spatpca object — checkNewLocationsForSpatpcaObject

<dl>

<dt>spatpca_object</dt>
<dd>An <code>spatpca</code> class object</dd>


<dt>x_new</dt>
<dd>New location matrix.</dd>

</dl>

checkNewLocationsForSpatpcaObject: Internal function: Validate new locations for a spatpca object

Description

Usage

Value

Arguments