Contradictory results between different heteroskedasticity tests

Hi all,

I'm getting contradictory results from bptest and ncvTest on a model
calculated by GLS as:

olslm = lm(log(rr)~log(aloi)*reg*inv, data)
varlm = lm(I(residuals(olslm)^2)~log(aloi)*reg*inv, data)
glslm = lm(log(rr)~log(aloi)*reg*inv, data, weights=1/fitted(varlm))

Testing both olslm and glslm with both ncvTest and bptest gives:

ncvTest(olslm)

Non-constant Variance Score Test
Variance formula: ~ fitted.values
Chisquare = 46.88206    Df = 1     p = 7.538963e-12

ncvTest(glslm)

Non-constant Variance Score Test
Variance formula: ~ fitted.values
Chisquare = 0.001466426    Df = 1     p = 0.9694533

bptest(olslm)

studentized Breusch-Pagan test
data:  olslm
BP = 213.1477, df = 7, p-value < 2.2e-16

bptest(glslm)

studentized Breusch-Pagan test
data:  glslm
BP = 213.1477, df = 7, p-value < 2.2e-16

Please notice the last output. It seems as if bptest is not
considering the weights given to lm. What am I doing wrong here?

Best regards
--
Carlos