Hello Nick,

Once you have your lmc fitted, call the object $psill.

For example, if your lmc object is called g.fit with variables v , z call:

g.fit$model$v$psill[1] to get coefficient of v for 1st structure of the nested model.

g.fit$model$z$psill[1] to get coefficient of z for 1st structure of the nested model.

g.fit$model$v$psill[2] to get coefficient of v for 2nd structure of the nested model.

g.fit$model$z$psill[2] to get coefficient of z for 2nd structure of the nested model.

For cross-variogram, please see the list of g.fit$model to see the name of the object storing v*z cross-variogram model coefficients.

I hope this helps. There are other ways of doing this, anyway this one should work.

Regards,

Manuel

Manuel Luís Castro Ribeiro

CERENA- Centro de Recursos Naturais e Ambiente

Instituto Superior Técnico

Av. Rovisco Pais

1049-001 Lisboa

Portugal

Phone: +351 21 841 74 41

Mobile: +351 92 442 80 07

Web: www.cerena.pt

**From:** R-sig-Geo <[hidden email]> **On Behalf Of **Nick Hamm

**Sent:** quarta-feira, 29 de janeiro de 2020 04:22

**To:** r-sig-geo <[hidden email]>; [hidden email]

**Subject:** [R-sig-Geo] gstat / Linear model of coregionalization

Is anybody using gstat for computing cross-variograms and fitting cross variogram models? I have implemented this in a similar manner to the example code given in the gstat vignette (Section 10).

I would like to extract the coefficients (i.g., the b_{ij}^l of the linear model of coregionalization as given in Equation 4.37 of Goovaearts (1997) book (page 110).

\gamma_{ij} (h) = \sum_{l=0}^L b_{ij}^l g_l(h) \forall i, j

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