[R-sig-Geo] About dnearneight and nb2listw function

[Roger Bivand]

On Thu, 31 Oct 2019, Letícia Dal' Canton wrote:

> In my Ph.D. I am comparing Lee and Anselin's methodology for estimating 
> bivariate spatial autocorrelation. Lee's methodology led me to the spdep 
> package. My questions are as follows:
>
> 1) The weight matrix W, which is part of the "nb2listw" function. First,
>    is it possible to view all elements of this matrix? Because I could
>    only visualize the elements whose autocorrelation is not null. That
>    would be enough, but I need to present this matrix and visualize the
>    autocorrelation between all points. That is, knowing what are the
>    coordinates of the points where the autocorrelation is nonzero and
>    also where it is null.

This is very unclear. Yes, nb2mat() gives a dense matrix, but you do not 
show how you "visualize the elements whose autocorrelation is not null". 
You need to add a reproducible example using a built-in data set. Note 
that the matrix showing the variance-covariance of the observations is 
dense by definition (I - \rho W)^{-1} - see Melanie Wall's 2004 article.

>
> 2) In the "dnearneight" function, is it possible to view the matrix of
>    neighbors? Because getting this matrix, would be able to standardize
>    and get the matrix of weights W without using the nb2list function.

You do not explain why this makes sense. Of course you can use nb2mat(), 
listw2mat() or coerce a listw object to a sparse matrix, but you need to 
motivate this (best with an example).

Roger

>
> Thankfully,
>
> Let???cia Dal' Canton.
>
> Matem???tica.
> Mestre em Engenharia Agr???cola.
> Doutoranda em Engenharia Agr???cola com linha de pesquisa em Estat???stica Espacial.
> Universidade Estadual do Oeste do Paran??? - UNIOESTE.
>
> Curr???culo Lattes: http://lattes.cnpq.br/1085422685501012.
> Contato: (45) 9 9962-7492.
>
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>
>

-- 
Roger Bivand
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