error in errorsarlm

1. change method to Matrix

 System calculation is specific, the condition is =5.14146e-17 (translated
from Chinese)

Warning messages:

Warning not a problem, but the error suggests scaling problems in the
covariance matrix of the coefficients. The X variables are most likely
measured in inappropriate metrics (some coefficients of size 1000, others of
size 0.0001, for example).

==>  using standardized regression, the warning disappeared as you advised.

 However, another set of warning appears:

 Warning messages:
1: In determinant(x, TRUE) : This version of the Matrix package returns
|determinant(L)| instead of determinant(A), i.e., a
*DIFFERENT* value.
If still necessary, do change your code, following
http://matrix.r-forge.r-project.org

2: In powerWeights(W = W, rho = lambda, order = con$pWOrder, X = B,  :
 not converged within order iterations
3: In powerWeights(W = t(W), rho = lambda, order = con$pWOrder, X = C,  :
 not converged within order iterations

Please kindly advise how to modify the code below from determinant L to
determinant A and why ?

2. great distance circle

And make sure that you do use Great Circle distances - you are not doing so
now.
With 200 neighbours, you have no viable spatial process, really.

=> longlat = TRUE returns no valid observation ...
    similar error messages have been researched in the archived mail
    but no identical case found...
   Please kindly suggest when longlat=TRUE,
   whether the unit of both longitude and latitude is degree.decimal..
   (confused with the manual explanation "measured in kilometer")

   Also, does "no viable spatial process" mean
  no spatial interaction within the range should be taken into
consideration ?

  Thank you

  Elaine


code
datam <-read.csv("c:/migration/M_R_SummerM20100722.csv",header=T,
row.names=1)

# std method   scale
 datam.sd<-scale(datam)
 datam.std<-as.data.frame(datam.sd)
 summary (datam.std)
 mean(datam.std)

 # obtain standard deviation
 sd(datam.std)

 mig.std
<-lm(datam.std$SummerM_ratio~datam.std$coast+datam.std$topo_mean+datam.std$prec_mean+datam.std$temp_ran+datam.std$evi_ran,data=datam.std)
 summary(mig.std)

 #SAR

 library(ncf)
 library(spdep)

 # Define coordinates, neighbours, and spatial weights
 coords<-cbind(datam$lon,datam$lat)
 coords<-as.matrix(coords)

 #Define neighbourhood (here distance 5)
 nb5<-dnearneigh(coords,0,5,longlat=TRUE)


 #Spatial weights, illustrated with coding style "W" (row standardized)
 nb5.w<-nb2listw(nb5, glist=NULL, style="W", zero.policy=TRUE)


  +++error in nb2listw(nb5, glist = NULL, style = "W", zero.policy = TRUE)
:
 No valid observations  +++
 (then modified as  nb5<-dnearneigh(coords,0,5) and Matrix went on
smoothly )

 # Spatial SAR error model
 sem.nb5.w <-
errorsarlm(datam.std$SummerM_ratio~datam.std$coast+datam.std$topo_mean+datam.std$prec_mean+datam.std$temp_ran+datam.std$evi_ran,data=datam.std,
listw=nb5.w, na.action=na.omit, method="Matrix", zero.policy=TRUE)

+++warning

1: In determinant(x, TRUE) : This version of the Matrix package returns

|determinant(L)| instead of determinant(A), i.e., a

*DIFFERENT* value.

If still necessary, do change your code, following
http://matrix.r-forge.r-project.org



2: In powerWeights(W = W, rho = lambda, order = con$pWOrder, X = B,  :

 not converged within order iterations

3: In powerWeights(W = t(W), rho = lambda, order = con$pWOrder, X = C,  :

 not converged within order iterations  ++++