[R-sig-Geo] rGeo vs. gstat; Question on geostatistical method for specific experimental design

[Paulo Justiniano Ribeiro Jr]

Following Edzer comments my impression is that you are trying to use
the spatial correlation in the analysis of an experiment.

There are indeed some attemps in the literature using geostatistical 
models.
In this case there is no prediction involved but  just a non-independent
variance matrix for the error terms of your model.

For some designs this can be achieve using likfit() in geoR or functions 
in the packlage nlme

best
P.J.




On Wed, 19 Oct 2005, Edzer J. Pebesma wrote:

> Schlatter Christian wrote:
>
>> Dear Edzer, dear list members
>>
>> Thank you very much for your comments. It made me investigate quite well.
>>
>> The answer to the question "rGeo vs. gstat" is answered by your very helpful article of the DSC 2003 meeting in Vienna (chapter "introduction"): http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Proceedings/Pebesma.pdf
>>
>> As I'm new and not yet so familiar with the customs of [R-sig-Geo], I did not feel about asking about my personal statistical problems but more about general statistical questions.
>>
>> But as you asked for more detail I will gladly describe them (please let me know if this should not be the place for it):
>>
>> We are looking at parasitism rates in cabbage pests eggs (Lepidoptera: mainly Mamestra brassicae, Pieris rapae) in relation to distance effects from flowering strips. Specifically the following question: In what relation is the parasitism rate to the distance from the flower source (which in the case are sown flower strips).
>>
>> Many practical restrictions led to a somehow "compromisical" experimental design consisting of four blocks in one cabbage field (two with flower strips, two without). Each block has two grids of 6x 8 plants (distance in between each plant: 3m) on each side of the flower strip (cp. Image), 96 plants per block. On each plant we collected pest eggs to determine parasitism rate. (Addtionaly we sampled on 4 different days).
>>
>> The main problem is the low parasitism rate in the field (only about 15-20% of all eggs have been parasitized), consequently many 0 values.
>>
>> My idea was to calculate for each of the four blocks variogram parameters and to compare them afterwards (as we had two study sites, we have 8 blocks all in all, making 4 with flowers and 4 without). With so many "0" samples difficult to manage.
>>
>> Now I found in Edzers article and the gstat manual the possibility of block kriging. Without knowing exactly what it is, I suppose there is the possibility to keep all four blocks together and defining the blocks with the rectangular block-defining possibility.
>>
>> Is this a valid procedure?
>>
>>
> Before you apply block kriging I would strongly encourage you to
> read an appropriate text book about what block kriging is. Blocks
> in geostatistics usually refer to specific spatially contiguous regions, not
> a combined effect of blocking in experimental design. Kriging refers
> to spatial prediction, not the estimation of effect size.
>
> Best regards,
> --
> Edzer
>
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Paulo Justiniano Ribeiro Jr
LEG (Laboratório de Estatística e Geoinformação)
Departamento de Estatística
Universidade Federal do Paraná
Caixa Postal 19.081
CEP 81.531-990
Curitiba, PR  -  Brasil
Tel: (+55) 41 3361 3573
Fax: (+55) 41 3361 3141
e-mail: paulojus at est.ufpr.br
http://www.est.ufpr.br/~paulojus