gstat now uses Lapack / failing cokriging

Hi Edzer, thanks for your prompt reply. I tried reproducing your matrix r but got a different result, i.e. a valid covariance matrix. The cross-covariances are different. Using the same example as above, my code is as follows:

library(sp)
library(gstat)

# some data
x <- c(215, 330, 410, 470, 545)
y <- c(230, 310, 330, 340, 365)
fc <- c(0.211, 0.251, 0.281, 0.262, 0.242)
por <- c(0.438, 0.457, 0.419, 0.430, 0.468)
Allier <- data.frame(x, y, fc, por)
coordinates(Allier) = ~x+y

# gstat object for co-kriging using linear model of co-regionalization
g <- gstat(id=c("fc"), formula=fc~1, data=Allier,
            model=vgm(0.00247, "Sph", 480, 0.00166))
g <- gstat(g, id="por", formula=por~1, data=Allier,
            model=vgm(0.00239, "Sph", 480, 0.00118))
g <- gstat(g, id=c("fc", "por"),
            model=vgm(0.00151, "Sph", 480, -0.00124))


dists <- spDists(Allier)
r11 <- variogramLine(g$model$fc, dist_vector = dists, covariance = T)
r12 <- variogramLine(g$model$fc.por, dist_vector = dists, covariance = T)
r22 <- variogramLine(g$model$por, dist_vector = dists, covariance = T)
r <- cbind(r11, r12)
r <- rbind(r, cbind(r12, r22))

r

              [,1]         [,2]         [,3]         [,4]         [,5]         [,6]         [,7]
 [1,] 0.0041300000 0.0014193874 0.0008959951 0.0005655821 0.0002240733 0.0002700000 0.0008677227
 [2,] 0.0014193874 0.0041300000 0.0018397575 0.0013976206 0.0008790828 0.0008677227 0.0002700000
 [3,] 0.0008959951 0.0018397575 0.0041300000 0.0020030001 0.0014238096 0.0005477541 0.0011247100
 [4,] 0.0005655821 0.0013976206 0.0020030001 0.0041300000 0.0018652970 0.0003457607 0.0008544158
 [5,] 0.0002240733 0.0008790828 0.0014238096 0.0018652970 0.0041300000 0.0001369841 0.0005374150
 [6,] 0.0002700000 0.0008677227 0.0005477541 0.0003457607 0.0001369841 0.0035700000 0.0013734154
 [7,] 0.0008677227 0.0002700000 0.0011247100 0.0008544158 0.0005374150 0.0013734154 0.0035700000
 [8,] 0.0005477541 0.0011247100 0.0002700000 0.0012245061 0.0008704261 0.0008669750 0.0017801702
 [9,] 0.0003457607 0.0008544158 0.0012245061 0.0002700000 0.0011403233 0.0005472637 0.0013523535
[10,] 0.0001369841 0.0005374150 0.0008704261 0.0011403233 0.0002700000 0.0002168159 0.0008506105
              [,8]         [,9]        [,10]
 [1,] 0.0005477541 0.0003457607 0.0001369841
 [2,] 0.0011247100 0.0008544158 0.0005374150
 [3,] 0.0002700000 0.0012245061 0.0008704261
 [4,] 0.0012245061 0.0002700000 0.0011403233
 [5,] 0.0008704261 0.0011403233 0.0002700000
 [6,] 0.0008669750 0.0005472637 0.0002168159
 [7,] 0.0017801702 0.0013523535 0.0008506105
 [8,] 0.0035700000 0.0019381256 0.0013776943
 [9,] 0.0019381256 0.0035700000 0.0018048825
[10,] 0.0013776943 0.0018048825 0.0035700000

eigen(r)$values

 [1] 0.0124609506 0.0055040132 0.0046425761 0.0035980843 0.0031064016 0.0028989486 0.0028042439
 [8] 0.0018107335 0.0010254131 0.0006486352