Performs a test of goodness of fit. The only method implemented so far is based on randomized quantile residuals (Dunn &amp; Smyth, 1996).

htest

Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.

Franois Rousset

spaMM

Mixed-Effect Models, with or without Spatial Random Effects

François Rousset

Jean-Baptiste Ferdy

Alexandre Courtiol

gof function

<dl> <dt>object</dt>
<dd>A fit object inheriting from class <code>"HLfit"</code>, as returned by spaMM's main fitting functions.</dd> <dt>method</dt>
<dd>Character string; a method of test of goodness of fit.</dd> <dt>...</dt>
<dd>Further arguments possibly passed to internal methods.</dd></dl>

Arguments

Goodness of fit test — gof

<dl>

 <dt>object</dt>
<dd>A fit object inheriting from class <code>"HLfit"</code>, as returned by spaMM's main fitting functions.</dd>

 <dt>method</dt>
<dd>Character string; a method of test of goodness of fit.</dd>

 <dt>...</dt>
<dd>Further arguments possibly passed to internal methods.</dd>

</dl>

gof: Goodness of fit test

Description

Usage

Value

Arguments

References

Examples