pen_hi

dpen_hi

ddpen_hi

penalize large values of parameter: penalty, 1st deriative, 2nd derivative

Functions for fitting and doing predictions with
Gaussian process models using Vecchia's (1988) approximation.
Package also includes functions for reordering input locations,
finding ordered nearest neighbors (with help from 'FNN' package),
grouping operations, and conditional simulations.
Covariance functions for spatial and spatial-temporal data
on Euclidean domains and spheres are provided. The original
approximation is due to Vecchia (1988)
<http://www.jstor.org/stable/2345768>, and the reordering and
grouping methods are from Guinness (2018)
<doi:10.1080/00401706.2018.1437476>.
Model fitting employs a Fisher scoring algorithm described
in Guinness (2019) <arXiv:1905.08374>.

Joseph Guinness

GpGp

Fast Gaussian Process Computation Using Vecchia's Approximation

Matthias Katzfuss

Youssef Fahmy

pen_hi function

<dl><dt>x</dt>
<dd>argument to penalty</dd>
<dt>tt</dt>
<dd>scale parameter of penalty</dd>
<dt>aa</dt>
<dd>location parameter of penalty</dd></dl>

Arguments

penalize large values of parameter: penalty, 1st deriative, 2nd derivative — pen_hi

<dl>

<dt>x</dt>
<dd>argument to penalty</dd>


<dt>tt</dt>
<dd>scale parameter of penalty</dd>


<dt>aa</dt>
<dd>location parameter of penalty</dd>

</dl>

pen_hi: penalize large values of parameter: penalty, 1st deriative, 2nd derivative

Description

Usage

Arguments