solar

Variance-covariance matrix for British Columbia solar radiation data

data

Methods for fitting nonstationary Gaussian process models by spatial deformation, as introduced by Sampson and Guttorp (1992) <doi:10.1080/01621459.1992.10475181>, and by dimension expansion, as introduced by Bornn et al. (2012) <doi:10.1080/01621459.2011.646919>. Low-rank thin-plate regression splines, as developed in Wood, S.N. (2003) <doi:10.1111/1467-9868.00374>, are used to either transform co-ordinates or create new latent dimensions.

Ben Youngman

deform

Spatial Deformation and Dimension Expansion Gaussian Processes

solar function

A <code>list</code> with three elements, which are:
<dl>
 <dt>x</dt>
<dd>a 12-row 2-column matrix of longitude-latitude coordinates for 12 stations</dd> <dt>z</dt>
<dd>a 12-row 12-column variance-covariance matrix</dd> <dt>n</dt>
<dd>an integer giving the original sample size</dd>
</dl>

Format

Variance-covariance matrix for British Columbia solar radiation data — solar

A <code>list</code> with three elements, which are:
<dl>
 <dt>x</dt>
<dd>a 12-row 2-column matrix of longitude-latitude coordinates for 12 stations</dd>

 <dt>z</dt>
<dd>a 12-row 12-column variance-covariance matrix</dd>

 <dt>n</dt>
<dd>an integer giving the original sample size</dd>


</dl>

solar: Variance-covariance matrix for British Columbia solar radiation data

Description

Arguments

Format